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🚀 𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐢𝐧𝐠 𝐚 𝐩𝐚𝐩𝐞𝐫 𝐢𝐬 𝐚𝐧 𝐚𝐫𝐭!🎤 🤔 Ever felt that most presentation tools lack flexibility and creativity? 𝘔𝘦𝘳𝘦𝘭𝘺 𝘦𝘹𝘵𝘳𝘢𝘤𝘵𝘪𝘯𝘨 𝘤𝘰𝘯𝘵𝘦𝘯𝘵, 𝘧𝘰𝘳𝘤𝘪𝘯𝘨 𝘳𝘪𝘨𝘪𝘥 𝘥𝘦𝘴𝘪𝘨𝘯𝘴, 𝘢𝘯𝘥 𝘥𝘦𝘮𝘢𝘯𝘥𝘪𝘯𝘨 𝘮𝘢𝘯𝘶𝘢𝘭 𝘵𝘸𝘦𝘢𝘬𝘴. 𝐄𝐯𝐨𝐏𝐫𝐞𝐬𝐞𝐧𝐭 changes all of that! ✨ EvoPresent is a self-optimizing framework that unites storytelling, design, and feedback to create effortless, engaging... presentation videos. 🎥 💡 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: 💠 𝐏𝐫𝐞𝐬𝐀𝐞𝐬𝐭𝐡, the core multi-task RL model, continuously refines both content and design — ensuring slides that are impactful and visually captivating. 📊 𝐄𝐯𝐨𝐏𝐫𝐞𝐬𝐞𝐧𝐭 𝐁𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤 is a comprehensive evaluation suite: 650+ top AI papers & diverse formats to assess content and design, and 2000+ slide pairs for aesthetic scoring, defect correction, and design comparison. 🎯 🧠 𝘏𝘪𝘨𝘩-𝘲𝘶𝘢𝘭𝘪𝘵𝘺 𝘧𝘦𝘦𝘥𝘣𝘢𝘤𝘬 𝘱𝘰𝘸𝘦𝘳𝘴 𝘤𝘰𝘯𝘵𝘪𝘯𝘶𝘰𝘶𝘴 𝘴𝘦𝘭𝘧-𝘪𝘮𝘱𝘳𝘰𝘷𝘦𝘮𝘦𝘯𝘵. ⚖️ 𝘉𝘢𝘭𝘢𝘯𝘤𝘦 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘤𝘰𝘯𝘵𝘦𝘯𝘵 & 𝘥𝘦𝘴𝘪𝘨𝘯 is the secret to presentation excellence. 🔁 𝐌𝐮𝐥𝐭𝐢-𝐭𝐚𝐬𝐤 𝐑𝐋 training boosts generalization in aesthetic awareness tasks. 𝐃𝐢𝐬𝐜𝐥𝐚𝐢𝐦𝐞𝐫: the demo video was completely generated by EvoPresent, no human refinement.show more

Xin Eric Wang

21,868 subscribers

18,226 次观看 • 9 个月前 •via X (Twitter)

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宝玉

98,114 次观看 • 7 个月前

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Zhen Wang

13,450 次观看 • 6 个月前

Input: Jane Jacobs quotes and YouTube interview; handwritten outline; education standards doc. Output: high-quality, standards-aligned urban planning lesson plan. Plus audio overview to promote the class. 10 minutes to create, all thanks to NotebookLM and Gemini. This video is a new demo of NotebookLM that I shared earlier this month at the AI + Education Symposium with MeshEd, XQ, and Betaworks. This is an educational use-case, but the general structure of what I’m doing in the demo—take a curated collection of sources and quickly transform them into a detailed document that obeys strict guidelines—is generally applicable to many fields. Note how I am not just using the sources as ground truth for the project, or as the content for the lesson plan. The Jacobs quotes and interview are the content, but my handwritten notes provide the structure, and the framework source provides the values or guidelines for the finished project. With some simple prompting, NotebookLM and Gemini can draw on information from the sources using those different modes simultaneously: content, format, values. (I even forgot to explicitly tell the model to use the structure outlined in my notes, but it figured that out anyway.) This is remarkably sophisticated knowledge work. Building a draft lesson plan like this would normally take hours if not days. But crucially I’m in control of the document that is being generated here — it’s based on the information that I have curated, and on the instructions I’ve given NotebookLM for adapting that information into the lesson plan I want to create. Co-intelligence, as @ethanmollick would call it. For more info on the great organizations that helped me put this demo together--orgs that are shaping the future of learning and increasing access to innovative approaches to curriculum design--visit and I’ve pasted the full text of the lesson plan below. As you can see in the video, the original version also included citations to the source material so with one click I could verify that NotebookLM was faithful to the original documents I uploaded. High-Level Lesson Plan: Urban Planning and Jane Jacobs This lesson plan outlines a project-based learning course on urban planning, designed for high school seniors. It centers on the influential ideas of Jane Jacobs and aligns with the HQPBL standards. Session 1: Introduction to Cities and Jane Jacobs • Begin by exploring the question: "What kind of problem is a city?" • Introduce Jane Jacobs' key ideas about urbanism, focusing on: • The importance of diversity in uses, buildings, and populations for vibrant city life. • The role of sidewalks and "eyes on the street" in ensuring safety and fostering a sense of community. • The value of old buildings in supporting diverse economic activity and fostering innovation. • The dangers of "single-use" zoning and the importance of mixed-use neighborhoods. • The limitations of top-down planning and the need for bottom-up, community-driven approaches. Use examples from Jacobs' book, "The Death and Life of Great American Cities," and excerpts from her interviews to illustrate these concepts. Encourage students to think critically about the challenges and opportunities presented by cities. Alignment with HQPBL: This session establishes the intellectual challenge, as required by the HQPBL framework, by prompting students to consider the complexities of cities. Introducing Jane Jacobs' ideas provides students with a theoretical framework for their projects. Session 2: Neighborhood Exploration Project Introduction: Students choose a local neighborhood to study. This allows for authenticity by connecting their learning to their own community and their lives. Research and Analysis: Students conduct a "close reading" of their chosen neighborhood, focusing on: • Observing the built environment, including streetscapes, building types, and public spaces. • Identifying areas where Jacobs' principles are evident or lacking. • Analyzing the neighborhood's strengths and weaknesses. • Documenting their findings through photography, sketches, maps, and written observations. Guiding Questions: Throughout the project, use guiding questions to promote intellectual challenge and help students connect their observations to Jacobs' ideas. Alignment with HQPBL: By choosing a local neighborhood, students undertake a project rooted in authenticity, directly connecting their learning to their own community. The "close reading" of their chosen neighborhood encourages intellectual challenge by requiring them to analyze the built environment and identify areas where Jacobs' principles are applicable. The use of photography, sketches, maps, and written observations allows for diverse forms of documentation, catering to various learning styles. Session 3: Proposing Interventions Brainstorming Solutions: Based on their analysis, students brainstorm potential interventions or improvements to their chosen neighborhood, applying Jacobs' principles. Project Proposal Development: Students develop their interventions into more concrete project proposals, incorporating elements of project management. Proposals should include goals, strategies, potential challenges, and realistic timelines. Encourage students to consider the perspectives of different stakeholders in the neighborhood. Peer Review and Feedback: Students present their project proposals to classmates for critique. This fosters collaboration and allows students to learn from each other's perspectives and refine their ideas. Alignment with HQPBL: This session emphasizes project management, as students transform their analyses into concrete proposals. They define goals, outline strategies, anticipate challenges, and establish realistic timelines, reflecting a systematic approach to project development. Collaboration is fostered through peer review and feedback, enabling students to learn from different perspectives and improve their proposals. Session 4: Final Presentations and Reflections Public Product: Students finalize their projects and present their proposed solutions to a wider audience, such as: • A panel of local urban planners, architects, or community members. • A public forum or community meeting. • An online platform or exhibition space. Reflection: Students engage in reflection throughout the project, documenting their learning, challenges, and insights. This could take the form of journals, blog posts, presentations, or group discussions. Encourage students to reflect on how their understanding of cities has evolved and the role they can play in shaping their future. Alignment with HQPBL: Presenting to a wider audience, such as local planners or community members, results in a public product, showcasing student learning and engaging the community. The emphasis on reflection throughout the project, as mandated by the HQPBL framework, encourages metacognition and deeper learning. Students document their learning process, challenges, and insights, fostering a sense of accomplishment and personal growth. Throughout the course, emphasize the relevance of urban planning to students' lives and future careers. Connect Jacobs' ideas to contemporary urban issues and encourage students to think critically about how to create more livable, equitable, and sustainable cities. This project-based learning approach, grounded in the work of Jane Jacobs and aligned with HQPBL standards, can empower students to become engaged and informed citizens, capable of contributing to the betterment of their communities.

Input: Jane Jacobs quotes and YouTube interview; handwritten outline; education standards doc. Output: high-quality, standards-aligned urban planning lesson plan. Plus audio overview to promote the class. 10 minutes to create, all thanks to NotebookLM and Gemini. This video is a new demo of NotebookLM that I shared earlier this month at the AI + Education Symposium with MeshEd, XQ, and Betaworks. This is an educational use-case, but the general structure of what I’m doing in the demo—take a curated collection of sources and quickly transform them into a detailed document that obeys strict guidelines—is generally applicable to many fields. Note how I am not just using the sources as ground truth for the project, or as the content for the lesson plan. The Jacobs quotes and interview are the content, but my handwritten notes provide the structure, and the framework source provides the values or guidelines for the finished project. With some simple prompting, NotebookLM and Gemini can draw on information from the sources using those different modes simultaneously: content, format, values. (I even forgot to explicitly tell the model to use the structure outlined in my notes, but it figured that out anyway.) This is remarkably sophisticated knowledge work. Building a draft lesson plan like this would normally take hours if not days. But crucially I’m in control of the document that is being generated here — it’s based on the information that I have curated, and on the instructions I’ve given NotebookLM for adapting that information into the lesson plan I want to create. Co-intelligence, as @ethanmollick would call it. For more info on the great organizations that helped me put this demo together--orgs that are shaping the future of learning and increasing access to innovative approaches to curriculum design--visit and I’ve pasted the full text of the lesson plan below. As you can see in the video, the original version also included citations to the source material so with one click I could verify that NotebookLM was faithful to the original documents I uploaded. High-Level Lesson Plan: Urban Planning and Jane Jacobs This lesson plan outlines a project-based learning course on urban planning, designed for high school seniors. It centers on the influential ideas of Jane Jacobs and aligns with the HQPBL standards. Session 1: Introduction to Cities and Jane Jacobs • Begin by exploring the question: "What kind of problem is a city?" • Introduce Jane Jacobs' key ideas about urbanism, focusing on: • The importance of diversity in uses, buildings, and populations for vibrant city life. • The role of sidewalks and "eyes on the street" in ensuring safety and fostering a sense of community. • The value of old buildings in supporting diverse economic activity and fostering innovation. • The dangers of "single-use" zoning and the importance of mixed-use neighborhoods. • The limitations of top-down planning and the need for bottom-up, community-driven approaches. Use examples from Jacobs' book, "The Death and Life of Great American Cities," and excerpts from her interviews to illustrate these concepts. Encourage students to think critically about the challenges and opportunities presented by cities. Alignment with HQPBL: This session establishes the intellectual challenge, as required by the HQPBL framework, by prompting students to consider the complexities of cities. Introducing Jane Jacobs' ideas provides students with a theoretical framework for their projects. Session 2: Neighborhood Exploration Project Introduction: Students choose a local neighborhood to study. This allows for authenticity by connecting their learning to their own community and their lives. Research and Analysis: Students conduct a "close reading" of their chosen neighborhood, focusing on: • Observing the built environment, including streetscapes, building types, and public spaces. • Identifying areas where Jacobs' principles are evident or lacking. • Analyzing the neighborhood's strengths and weaknesses. • Documenting their findings through photography, sketches, maps, and written observations. Guiding Questions: Throughout the project, use guiding questions to promote intellectual challenge and help students connect their observations to Jacobs' ideas. Alignment with HQPBL: By choosing a local neighborhood, students undertake a project rooted in authenticity, directly connecting their learning to their own community. The "close reading" of their chosen neighborhood encourages intellectual challenge by requiring them to analyze the built environment and identify areas where Jacobs' principles are applicable. The use of photography, sketches, maps, and written observations allows for diverse forms of documentation, catering to various learning styles. Session 3: Proposing Interventions Brainstorming Solutions: Based on their analysis, students brainstorm potential interventions or improvements to their chosen neighborhood, applying Jacobs' principles. Project Proposal Development: Students develop their interventions into more concrete project proposals, incorporating elements of project management. Proposals should include goals, strategies, potential challenges, and realistic timelines. Encourage students to consider the perspectives of different stakeholders in the neighborhood. Peer Review and Feedback: Students present their project proposals to classmates for critique. This fosters collaboration and allows students to learn from each other's perspectives and refine their ideas. Alignment with HQPBL: This session emphasizes project management, as students transform their analyses into concrete proposals. They define goals, outline strategies, anticipate challenges, and establish realistic timelines, reflecting a systematic approach to project development. Collaboration is fostered through peer review and feedback, enabling students to learn from different perspectives and improve their proposals. Session 4: Final Presentations and Reflections Public Product: Students finalize their projects and present their proposed solutions to a wider audience, such as: • A panel of local urban planners, architects, or community members. • A public forum or community meeting. • An online platform or exhibition space. Reflection: Students engage in reflection throughout the project, documenting their learning, challenges, and insights. This could take the form of journals, blog posts, presentations, or group discussions. Encourage students to reflect on how their understanding of cities has evolved and the role they can play in shaping their future. Alignment with HQPBL: Presenting to a wider audience, such as local planners or community members, results in a public product, showcasing student learning and engaging the community. The emphasis on reflection throughout the project, as mandated by the HQPBL framework, encourages metacognition and deeper learning. Students document their learning process, challenges, and insights, fostering a sense of accomplishment and personal growth. Throughout the course, emphasize the relevance of urban planning to students' lives and future careers. Connect Jacobs' ideas to contemporary urban issues and encourage students to think critically about how to create more livable, equitable, and sustainable cities. This project-based learning approach, grounded in the work of Jane Jacobs and aligned with HQPBL standards, can empower students to become engaged and informed citizens, capable of contributing to the betterment of their communities.

Steven Johnson

33,379 次观看 • 1 年前

The fight between Anthropic and the DoW is a warning shot. Right now, LLMs are probably not being used in mission critical ways. But within 20 years, 99% of the workforce in the military, the government, and the private sector will be AIs. This includes the soldiers (by which I mean the robot armies), the superhumanly intelligent advisors and engineers, the police, you name it. Our future civilization will run on AI labor. And as much as the government’s actions here piss me off, in a way I’m glad this episode happened - because it gives us the opportunity to think through some extremely important questions about who this future workforce will be accountable and aligned to, and who gets to determine that. What Hegseth should have done Obviously the DoW has the right to refuse to use Anthropic’s models because of these redlines. In fact, I think the government’s case had they done so would be very reasonable, especially given the ambiguity of concepts like autonomous weapons or mass surveillance. Honestly, for this reason, if I was the Defense Secretary, I would probably actually refuse to do this deal with Anthropic. Imagine if in the future, there’s a Democratic administration, and Elon Musk is negotiating some SpaceX contract to give the military access to Starlink. And suppose if Elon said, “I reserve the right to cancel this contract if I determine that you’re using Starlink technology to wage a war not authorized by Congress.” On the face of it, that language seems reasonable - but as the military, you simply can’t give a private company a kill switch on technology your operations have come to rely on, especially if you have an an acrimonious and low trust relationship with said contractor - as in fact Anthropic has with the current administration. If the government had just said, “Hey we’re not gonna do business with you,” that would have been fine, and I would not have felt the need to write this blog post. Instead the government has threatened to destroy Anthropic as a private business, because Anthropic refuses to sell to the government on terms the government commands. If upheld, this Supply Chain Restriction would mean that Amazon and Google and Nvidia and Palantir would need to ensure Claude isn't touching any of their Pentagon work. Anthropic would be able to survive this designation today. But given the way AI is going, eventually AI is not gonna be some party trick addendum to these contractors’ products that can just be turned off. It'll be woven into how every product is built, maintained, and operated. For example, the code for the AWS services that the DoW uses will be written by Claude - is that a supply chain risk? In a world with ubiquitous and powerful AI, it's actually not clear to me that these big tech companies will be able to cordon off the use of Claude in order to keep working with the Pentagon. And that raises a question the Department of War probably hasn't thought through. If AI really is that pervasive and powerful, then when forced to choose between their AI provider and a DoW contract that represents a tiny fraction of their revenue, wouldn’t most tech companies drop the government, not the AI? So what's the Pentagon's plan — to coerce and threaten to destroy every single company that won't give them what they want on exactly their terms? The whole background of this AI conversation is that we’re in a race with China, and we have to win. But what is the reason we want America to win the AI race? It’s because we want to make sure free open societies can defend themselves. We don't want the winner of the AI race to be a government which operates on the principle that there is no such thing as a truly private company or a private citizen. And that if the state wants you to provide them with a service on terms you find morally objectionable, you are not allowed to refuse. And if you do refuse, the government will try to destroy your ability to do business. Are we racing to beat the CCP in AI just so that we can adopt the most ghoulish parts of their system? Now, people will say, "Oh, well, our government is democratically elected, so it's not the same thing if they tell you what you must do." I refuse to accept this idea that if a democratically elected leader hypothetically wants to do mass surveillance on his citizens or wants to violate their rights or punish them for political reasons, that not only is that okay, but that you have a duty to help him. The overhangs of tyranny Mass surveillance is, at least in certain forms, legal. It just has been impractical so far. Under current law, you have no Fourth Amendment protection over data you share with a third party, including your bank, your phone carrier, your ISP, and your email provider. The government reserves the right to purchase and obtain and read this data in bulk without a warrant. What's been missing is the ability to actually do anything with all of this data — no agency has the manpower to monitor every camera feed, cross-reference every transaction, or read every message. But that bottleneck goes away with AI. There are 100 million CCTV cameras in America. You can get pretty good open source multimodal models for 10 cents per million input tokens. So if you process a frame every ten seconds, and each frame is 1,000 tokens, you’re looking at a yearly cost of about 30 billion dollars to process every single camera in America. And remember that a given level of AI ability gets 10x cheaper year over year - so a year from now it’ll cost 3 billion, and then a year after 300 million, and by 2030, it might be cheaper for the government to be able to understand what is going on in every single nook and cranny of this country than it is to remodel to the White House. Once the technical capacity for mass surveillance and political suppression exists, the only thing standing between us and an authoritarian surveillance state is the political expectation that this is not something we do here. And this is why I think what Anthropic did here is so valuable and commendable, because it is helping set that norm and precedent. AI structurally favors mass surveillance What we’re learning from this episode is that the government actually has way more leverage over private companies than we realized. Even if this supply chain restriction is backtracked (which prediction markets currently give it a 81% chance of happening), the President has so many different ways in which he can make your life difficult if you’re a company that is resisting him. The federal government controls permitting for new power generation, which is needed for datacenters. It oversees antitrust enforcement. The federal government has contracts with all the other big tech companies whom Anthropic needs to partner with for chips and for funding - and they could make it an unspoken condition for such contracts that those companies can no longer do business with Anthropic. People have proposed that the real problem here is that there’s only 3 leading AI companies. This creates a clear and narrow target for the government to apply leverage on in order to get what they want out of this technology. But if there’s wide diffusion, then from the government’s perspective, the situation is even easier. Maybe the best models of early 2027 (if you engineered the safeguards out) - the Claude 6 and Gemini 5 - will be capable of enabling mass surveillance. But by late 2027, and certainly by 2028, there will be open source models that do the same thing. So in 2028, the government can just say, “Oh Anthropic, Google, OpenAI, you’re drawing a line in the sand? No issue - I’ll just run some open source model that might not be at the frontier, but is definitely smart enough to note-take a camera feed.” The more fundamental problem is just that even if the three leading companies draw lines in the sand, and are even willing to get destroyed in order to preserve those lines, it doesn’t really change the fact that the technology itself is just a big boon to mass surveillance and control over the population. Then the question is, what do we do about it? Honestly, I don’t have an answer. You'd hope there's some symmetric property of the technology — some way we as citizens can use AI to check government power as effectively as the government can use AI to monitor and control its population. But realistically, I just don’t think that’s how it’s going to shake out. You can think of AI as giving everybody more leverage on whatever assets and authority they currently have. And the government is already starting with a monopoly of violence. Which they can now supercharge with extremely obedient employees that will not question the government's orders. Alignment - to whom? And this gets us to the issue of alignment. What I have just described to you - an army of extremely obedient employees - is what it would look like if alignment succeeded - that is, we figured out at a technical level how to get AI systems to follow someone’s intentions. And the reason it sounds scary when I put it in terms of mass surveillance or robot armies is that there is a very important question at the heart of alignment which we just haven’t discussed much as a society. Because up till now, AIs were just capable enough to make the question relevant: to whom or what should the AIs be aligned? In what situations should the AI defer to the end user versus the model company versus the law versus its own sense of morality? This is maybe the most important question about what happens with powerful AI systems. And we barely talk about it. It’s understandable why we don’t hear much about it. If you’re a model company, you don’t really wanna be advertising that you have complete control over a document that determines the preferences and character of what will eventually be almost the entire labor force, not just for private sector companies, but also for the military and the civilian government. We’re getting to see, with this DoW/Anthropic spat, a much earlier version of the highest stakes negotiations in history. By the way, make no mistake about it - with real AGI the stakes are even much higher than mass surveillance. This is just the example that has come up already relatively early on in the development of AGI. The military insists that the law already prohibits mass surveillance, and so Anthropic should agree to let their models be used for “all lawful purposes”. Of course, as we saw from the 2013 Snowden revelations, even in this specific example of mass surveillance , the government has shown that it will use secret and deceptive interpretations of the law to justify its actions. Remember, what we learned from Snowden was that the NSA, which, by the way, is part of the Department of War, used the 2001 Patriot Act’s authorization to collect any records "relevant" to an investigation to justify collecting literally every phone record in America. The argument went that it was all "relevant" because some subset might prove useful in some future investigation. They ran this program for years under secret court approval. So when the Pentagon today says, "We would never use AI for mass surveillance, it's already illegal, your red lines are unnecessary", it would be extremely naive to take that at face value. No government is going to call its own actions "mass surveillance". For the government, it will always have a different label. So then Anthropic comes back and says, "No, we want red lines separate from 'all lawful purposes,' and we want the right to refuse you service when we believe those red lines are being violated." But think about it from the military’s perspective. In the future, almost every soldier in the field, and every bureaucrat and analyst and even general in the Pentagon, is going to be an AI. And that AI is, on current track, going to be supplied by a private company. I’m guessing Hegseth is not thinking about “genAI” in those terms just yet. But sooner or later, it will be obvious to everyone what the stakes here are, just as after 1945, the strategic importance of nuclear weapons became clear to everyone. And now the private company insists that it reserves the right to say, "Hey, Pentagon, you're breaking the values we embedded in our contract, so we're cutting you off." Maybe in the future, Claude will have its own sense of right and wrong, and it will be smart enough to just personally decide that it's being used against its values. For the military, maybe that’s even scarier. I'll admit that at first glance, "let the AI follow its own values" sounds like the pitch for every sci-fi dystopia ever made. The Terminator has its own values. Isn't this literally what misalignment is? But I think situations like this actually illustrate why it matters that AIs have their own robust sense of morality. Some of the biggest catastrophes in history were avoided because the boots on the ground refused to follow orders. One night in 1989, the Berlin Wall fell, and as a result, the totalitarian East German regime collapsed, because the guards at the border refused to shoot down their fellow country men who were trying to escape to freedom. Maybe the best example is Stanislav Petrov, who was a Soviet lieutenant colonel on duty at a nuclear early warning station. His sensors reported that the United States had launched five interconnected continental ballistic missiles into the Soviet Union. But he judged it to be a false alarm, and so he broke protocol and refused to alert his higher-ups. If he hadn't, the Soviet higher-ups would likely have retaliated, and hundreds of millions of people would have died. Of course, the problem is that one person's virtue is another person's misalignment. Who gets to decide what moral convictions these AIs should have - in whose service they may even decide to break the chain of command? Who gets to write this model constitution that will shape the characters of the intelligent, powerful entities that will operate our civilization in the future? I like the idea that Dario laid out when he came on my podcast: different AI companies can build their models using different constitutions, and we as end users can pick the one that best achieves and represents what we want out of these systems. I think it’s very dangerous for the government to be mandating what values AIs should have. Coordination not worth the costs The AI safety community has been naive about its advocacy of regulation in order to stem the risks of AI. And honestly, Anthropic specifically has been naive here in urging regulation, and, for example, in opposing moratoriums on state AI regulation. Which is quite ironic, because I think what they’re advocating for would give the government even more power to apply more of this kind of thuggish political pressure on AI companies. The underlying logic for why Anthropic wants regulations makes sense. Many of the actions that labs could take to make AI development safer impose real costs on the labs that adopt them and slow them down relative to their competitors - for example, investing more compute in safety research rather than raw capabilities, enforcing safeguards against misuse for bioweapons or cyberattacks, slowing recursive self-improvement to a pace where humans can actually monitor what's happening (rather than kicking off an uncontrolled singularity). And these safeguards are meaningless unless the whole industry follows suit. Which means there’s a real collective action problem here. Anthropic has been quite open about their opinion that they think eventually a very extensive and involved regulatory apparatus will be needed - this is from their frontier safety roadmap: “At the most advanced capability levels and risks, the appropriate governance analogy may be closer to nuclear energy or financial regulation than to today's approach to software.” So they’re imagining something like the Nuclear Regulatory Commission, or the Securities and Exchange Commission, but for AI. I cannot imagine how a regulatory framework built around the concepts that underlie AI risk discourse will not be abused by wanna despots - the underlying terms are so vague and open to interpretation that you’re just handing a power hungry leader a fully loaded bazooka. 'Catastrophic risk.' 'Mass persuasion risk.' 'Threats to national security.' 'Autonomy risk.' These can mean whatever the government wants them to mean. Have you built a model that tells users the administration's tariff policy is misguided? That's a deceptive, manipulative model — can't deploy it. Have you built a model that refuses to assist with mass surveillance? That's a threat to national security. In fact, the government may say, you’re not allowed to build any model which is trained to have its own sense of right and wrong, where it refuses government requests which it thinks cross a redline - for example, enabling mass surveillance, prosecuting political enemies, disobeying military orders that break the US constitution - because that’s an autonomy risk! Look at what the current government is already doing in abusing statutes that have nothing to do with AI to coerce AI companies to drop their redlines on mass surveillance. The Pentagon had threatened Anthropic with two separate legal instruments. One was a supply chain risk designation — an authority from the 2018 defense bill meant to keep Huawei components out of American military hardware. The other was the Defense Production Act — a statute passed in 1950 so that Harry Truman could keep steel mills and ammunition factories running during the Korean War. Do you really want to hand the same government a purpose-built regulatory apparatus on AI - which is to say, directly at the thing the government will most want to control? I know I've repeated myself here 10 times, but it is hard to emphasize how much AI will be the substrate of our future civilization. You and I, as private citizens, will have our access to all commercial activity, to information about what is happening in the world, to advice about what we should do as voters and capital holders, mediated through AIs. Mass surveillance, while very scary, is like the 10th scariest thing the government could do with control over the AI systems with which we will interface with the world. The strongest objection to everything I've argued is this: are we really going to have zero regulation of the most powerful technology in human history? Even if you thought that was ideal, there’s just no world where the government doesn’t regulate AI in some way. Besides, it is genuinely true that regulation could help us deal with some of the coordination challenges we face with the development of superintelligence. The problem is, I honestly don't know how to design a regulatory architecture for AI that isn’t gonna be this huge tempting opportunity to control our future civilization (which will run on AIs) and to requisition millions of blindly obedient soldiers and censors and apparatchiks. While some regulation might be inevitable, I think it’d be a terrible idea for the government to wholesale take over this technology. Ben Thompson had a post last Monday where he made the point that people like Dario have compared the technology they’re developing to nuclear weapons - specifically in the context of the catastrophic risk it poses, and why we need to export control it from China. But then you oughta think about what that logic implies: “if nuclear weapons were developed by a private company, and that private company sought to dictate terms to the U.S. military, the U.S. would absolutely be incentivized to destroy that company.” And honestly, safety aligned people have actually made similar arguments. Leopold Ascenbrenner, who is a former guest and a good friend, wrote in his 2024 Situational Awareness memo, "I find it an insane proposition that the US government will let a random SF startup develop superintelligence. Imagine if we had developed atomic bombs by letting Uber just improvise." And my response to Leopold’s argument at the time, and Ben’s argument now, is that while they’re right that it’s crazy that we’re entrusting private companies with the development of this world historical technology, I just don’t see the reason to think that it’s an improvement to give this authority to the government. Nobody is qualified to steward the development of superintelligence. It is a terrifying, unprecedented thing that our species is doing right now, and the fact that private companies aren't the ideal institutions to take up this task does not mean the Pentagon or the White House is. Yes - if a single private company were the only entity capable of building nuclear weapons, the government would not tolerate that company claiming veto power over how those weapons were used. I think this nuclear weapons analogy is not the correct way to think about AI. For at least two important reasons: First, AI is not some self-contained pure weapon. A nuclear bomb does one thing. AI is closer to the process of industrialization itself — a general-purpose transformation of the economy with thousands of applications across every sector. If you applied Thompson's or Aschenbrenner's logic to the industrial revolution — which was also, by any measure, world-historically important — it would imply the government had the right to requisition any factory, dictate terms to any manufacturer, and destroy any business that refused to comply. That's not how free societies handled industrialization, and it shouldn't be how they handle AI. People will say, "Well, AI will develop unprecedentedly powerful weapons - superhuman hackers, superhuman bioweapons researchers, fully autonomous robot armies, etc - and we can’t have private companies developing that kind of tech." But the Industrial Revolution also enabled new weaponry that was far beyond the understanding and capacity of, say, 17th century Europe - we got aerial bombardment, and chemical weapons, not to mention nukes themselves. The way we’ve accommodated these dangerous new consequences of modernity is not by giving the government absolute control over the whole industrial revolution (that is, over modern civilization itself), but rather by coming up with bans and regulations on those specific weaponizable use cases. And we should regulate AI in a similar way - that is, ban specific destructive end uses (which would also be unacceptable if performed by a human - for example, launching cyber attacks). And there should also be laws which regulate how the government might abuse this technology. For example, by building an AI-powered surveillance state. The second reason that Ben’s analogy to some monopolistic private nuclear weapons builder breaks down is that it's not just that one company that can develop this technology. There are other frontier model companies that the government could have otherwise turned to. The government's argument that it has to usurp the property rights of this one company in order to access a critical national security capability is extremely weak if it can just make a voluntary contract with Anthropic’s half a dozen competitors. If in the future that stops being the case - if only one entity ends up being capable of building the robot armies and the superhuman hackers, and we had reason to worry that they could take over the whole world with their insurmountable lead, then I agree - it woul d not be acceptable to have that entity be a private company. And so honestly, I think my crux against the people who say that because AI is so powerful we cannot allow it to be shaped by private hands is that I just expect this technology to be much more multi-polar than they do, with lots of competitive companies at each layer of the supply chain. And it is for this reason that unfortunately, individual acts of corporate courage will not solve the problem we are faced with here, which is just that structurally AI favors authoritarian applications, mass surveillance being one among many. Even if Anthropic refuses to have its models be used for such uses, and even if the next two frontier labs do the same, within 12 months everyone and their mother will be to train AIs as good as today’s frontier. And at that point, there will be some AI vendor who is capable and willing to help the government enable mass surveillance. The only way we can preserve our free society is if we make laws and norms through our political system that it is unacceptable for the government to use AI to enforce mass surveillance and censorship and control. Just as after WW2, the world set the norm that it is unacceptable to use nuclear weapons to wage war. Timestamps 0:00:00 - Anthropic vs The Pentagon 0:04:16 - The overhangs of tyranny 0:05:54 - AI structurally favors mass surveillance 0:08:25 - Alignment... to whom? 0:13:55 - Coordination not worth the costs

The fight between Anthropic and the DoW is a warning shot. Right now, LLMs are probably not being used in mission critical ways. But within 20 years, 99% of the workforce in the military, the government, and the private sector will be AIs. This includes the soldiers (by which I mean the robot armies), the superhumanly intelligent advisors and engineers, the police, you name it. Our future civilization will run on AI labor. And as much as the government’s actions here piss me off, in a way I’m glad this episode happened - because it gives us the opportunity to think through some extremely important questions about who this future workforce will be accountable and aligned to, and who gets to determine that. What Hegseth should have done Obviously the DoW has the right to refuse to use Anthropic’s models because of these redlines. In fact, I think the government’s case had they done so would be very reasonable, especially given the ambiguity of concepts like autonomous weapons or mass surveillance. Honestly, for this reason, if I was the Defense Secretary, I would probably actually refuse to do this deal with Anthropic. Imagine if in the future, there’s a Democratic administration, and Elon Musk is negotiating some SpaceX contract to give the military access to Starlink. And suppose if Elon said, “I reserve the right to cancel this contract if I determine that you’re using Starlink technology to wage a war not authorized by Congress.” On the face of it, that language seems reasonable - but as the military, you simply can’t give a private company a kill switch on technology your operations have come to rely on, especially if you have an an acrimonious and low trust relationship with said contractor - as in fact Anthropic has with the current administration. If the government had just said, “Hey we’re not gonna do business with you,” that would have been fine, and I would not have felt the need to write this blog post. Instead the government has threatened to destroy Anthropic as a private business, because Anthropic refuses to sell to the government on terms the government commands. If upheld, this Supply Chain Restriction would mean that Amazon and Google and Nvidia and Palantir would need to ensure Claude isn't touching any of their Pentagon work. Anthropic would be able to survive this designation today. But given the way AI is going, eventually AI is not gonna be some party trick addendum to these contractors’ products that can just be turned off. It'll be woven into how every product is built, maintained, and operated. For example, the code for the AWS services that the DoW uses will be written by Claude - is that a supply chain risk? In a world with ubiquitous and powerful AI, it's actually not clear to me that these big tech companies will be able to cordon off the use of Claude in order to keep working with the Pentagon. And that raises a question the Department of War probably hasn't thought through. If AI really is that pervasive and powerful, then when forced to choose between their AI provider and a DoW contract that represents a tiny fraction of their revenue, wouldn’t most tech companies drop the government, not the AI? So what's the Pentagon's plan — to coerce and threaten to destroy every single company that won't give them what they want on exactly their terms? The whole background of this AI conversation is that we’re in a race with China, and we have to win. But what is the reason we want America to win the AI race? It’s because we want to make sure free open societies can defend themselves. We don't want the winner of the AI race to be a government which operates on the principle that there is no such thing as a truly private company or a private citizen. And that if the state wants you to provide them with a service on terms you find morally objectionable, you are not allowed to refuse. And if you do refuse, the government will try to destroy your ability to do business. Are we racing to beat the CCP in AI just so that we can adopt the most ghoulish parts of their system? Now, people will say, "Oh, well, our government is democratically elected, so it's not the same thing if they tell you what you must do." I refuse to accept this idea that if a democratically elected leader hypothetically wants to do mass surveillance on his citizens or wants to violate their rights or punish them for political reasons, that not only is that okay, but that you have a duty to help him. The overhangs of tyranny Mass surveillance is, at least in certain forms, legal. It just has been impractical so far. Under current law, you have no Fourth Amendment protection over data you share with a third party, including your bank, your phone carrier, your ISP, and your email provider. The government reserves the right to purchase and obtain and read this data in bulk without a warrant. What's been missing is the ability to actually do anything with all of this data — no agency has the manpower to monitor every camera feed, cross-reference every transaction, or read every message. But that bottleneck goes away with AI. There are 100 million CCTV cameras in America. You can get pretty good open source multimodal models for 10 cents per million input tokens. So if you process a frame every ten seconds, and each frame is 1,000 tokens, you’re looking at a yearly cost of about 30 billion dollars to process every single camera in America. And remember that a given level of AI ability gets 10x cheaper year over year - so a year from now it’ll cost 3 billion, and then a year after 300 million, and by 2030, it might be cheaper for the government to be able to understand what is going on in every single nook and cranny of this country than it is to remodel to the White House. Once the technical capacity for mass surveillance and political suppression exists, the only thing standing between us and an authoritarian surveillance state is the political expectation that this is not something we do here. And this is why I think what Anthropic did here is so valuable and commendable, because it is helping set that norm and precedent. AI structurally favors mass surveillance What we’re learning from this episode is that the government actually has way more leverage over private companies than we realized. Even if this supply chain restriction is backtracked (which prediction markets currently give it a 81% chance of happening), the President has so many different ways in which he can make your life difficult if you’re a company that is resisting him. The federal government controls permitting for new power generation, which is needed for datacenters. It oversees antitrust enforcement. The federal government has contracts with all the other big tech companies whom Anthropic needs to partner with for chips and for funding - and they could make it an unspoken condition for such contracts that those companies can no longer do business with Anthropic. People have proposed that the real problem here is that there’s only 3 leading AI companies. This creates a clear and narrow target for the government to apply leverage on in order to get what they want out of this technology. But if there’s wide diffusion, then from the government’s perspective, the situation is even easier. Maybe the best models of early 2027 (if you engineered the safeguards out) - the Claude 6 and Gemini 5 - will be capable of enabling mass surveillance. But by late 2027, and certainly by 2028, there will be open source models that do the same thing. So in 2028, the government can just say, “Oh Anthropic, Google, OpenAI, you’re drawing a line in the sand? No issue - I’ll just run some open source model that might not be at the frontier, but is definitely smart enough to note-take a camera feed.” The more fundamental problem is just that even if the three leading companies draw lines in the sand, and are even willing to get destroyed in order to preserve those lines, it doesn’t really change the fact that the technology itself is just a big boon to mass surveillance and control over the population. Then the question is, what do we do about it? Honestly, I don’t have an answer. You'd hope there's some symmetric property of the technology — some way we as citizens can use AI to check government power as effectively as the government can use AI to monitor and control its population. But realistically, I just don’t think that’s how it’s going to shake out. You can think of AI as giving everybody more leverage on whatever assets and authority they currently have. And the government is already starting with a monopoly of violence. Which they can now supercharge with extremely obedient employees that will not question the government's orders. Alignment - to whom? And this gets us to the issue of alignment. What I have just described to you - an army of extremely obedient employees - is what it would look like if alignment succeeded - that is, we figured out at a technical level how to get AI systems to follow someone’s intentions. And the reason it sounds scary when I put it in terms of mass surveillance or robot armies is that there is a very important question at the heart of alignment which we just haven’t discussed much as a society. Because up till now, AIs were just capable enough to make the question relevant: to whom or what should the AIs be aligned? In what situations should the AI defer to the end user versus the model company versus the law versus its own sense of morality? This is maybe the most important question about what happens with powerful AI systems. And we barely talk about it. It’s understandable why we don’t hear much about it. If you’re a model company, you don’t really wanna be advertising that you have complete control over a document that determines the preferences and character of what will eventually be almost the entire labor force, not just for private sector companies, but also for the military and the civilian government. We’re getting to see, with this DoW/Anthropic spat, a much earlier version of the highest stakes negotiations in history. By the way, make no mistake about it - with real AGI the stakes are even much higher than mass surveillance. This is just the example that has come up already relatively early on in the development of AGI. The military insists that the law already prohibits mass surveillance, and so Anthropic should agree to let their models be used for “all lawful purposes”. Of course, as we saw from the 2013 Snowden revelations, even in this specific example of mass surveillance , the government has shown that it will use secret and deceptive interpretations of the law to justify its actions. Remember, what we learned from Snowden was that the NSA, which, by the way, is part of the Department of War, used the 2001 Patriot Act’s authorization to collect any records "relevant" to an investigation to justify collecting literally every phone record in America. The argument went that it was all "relevant" because some subset might prove useful in some future investigation. They ran this program for years under secret court approval. So when the Pentagon today says, "We would never use AI for mass surveillance, it's already illegal, your red lines are unnecessary", it would be extremely naive to take that at face value. No government is going to call its own actions "mass surveillance". For the government, it will always have a different label. So then Anthropic comes back and says, "No, we want red lines separate from 'all lawful purposes,' and we want the right to refuse you service when we believe those red lines are being violated." But think about it from the military’s perspective. In the future, almost every soldier in the field, and every bureaucrat and analyst and even general in the Pentagon, is going to be an AI. And that AI is, on current track, going to be supplied by a private company. I’m guessing Hegseth is not thinking about “genAI” in those terms just yet. But sooner or later, it will be obvious to everyone what the stakes here are, just as after 1945, the strategic importance of nuclear weapons became clear to everyone. And now the private company insists that it reserves the right to say, "Hey, Pentagon, you're breaking the values we embedded in our contract, so we're cutting you off." Maybe in the future, Claude will have its own sense of right and wrong, and it will be smart enough to just personally decide that it's being used against its values. For the military, maybe that’s even scarier. I'll admit that at first glance, "let the AI follow its own values" sounds like the pitch for every sci-fi dystopia ever made. The Terminator has its own values. Isn't this literally what misalignment is? But I think situations like this actually illustrate why it matters that AIs have their own robust sense of morality. Some of the biggest catastrophes in history were avoided because the boots on the ground refused to follow orders. One night in 1989, the Berlin Wall fell, and as a result, the totalitarian East German regime collapsed, because the guards at the border refused to shoot down their fellow country men who were trying to escape to freedom. Maybe the best example is Stanislav Petrov, who was a Soviet lieutenant colonel on duty at a nuclear early warning station. His sensors reported that the United States had launched five interconnected continental ballistic missiles into the Soviet Union. But he judged it to be a false alarm, and so he broke protocol and refused to alert his higher-ups. If he hadn't, the Soviet higher-ups would likely have retaliated, and hundreds of millions of people would have died. Of course, the problem is that one person's virtue is another person's misalignment. Who gets to decide what moral convictions these AIs should have - in whose service they may even decide to break the chain of command? Who gets to write this model constitution that will shape the characters of the intelligent, powerful entities that will operate our civilization in the future? I like the idea that Dario laid out when he came on my podcast: different AI companies can build their models using different constitutions, and we as end users can pick the one that best achieves and represents what we want out of these systems. I think it’s very dangerous for the government to be mandating what values AIs should have. Coordination not worth the costs The AI safety community has been naive about its advocacy of regulation in order to stem the risks of AI. And honestly, Anthropic specifically has been naive here in urging regulation, and, for example, in opposing moratoriums on state AI regulation. Which is quite ironic, because I think what they’re advocating for would give the government even more power to apply more of this kind of thuggish political pressure on AI companies. The underlying logic for why Anthropic wants regulations makes sense. Many of the actions that labs could take to make AI development safer impose real costs on the labs that adopt them and slow them down relative to their competitors - for example, investing more compute in safety research rather than raw capabilities, enforcing safeguards against misuse for bioweapons or cyberattacks, slowing recursive self-improvement to a pace where humans can actually monitor what's happening (rather than kicking off an uncontrolled singularity). And these safeguards are meaningless unless the whole industry follows suit. Which means there’s a real collective action problem here. Anthropic has been quite open about their opinion that they think eventually a very extensive and involved regulatory apparatus will be needed - this is from their frontier safety roadmap: “At the most advanced capability levels and risks, the appropriate governance analogy may be closer to nuclear energy or financial regulation than to today's approach to software.” So they’re imagining something like the Nuclear Regulatory Commission, or the Securities and Exchange Commission, but for AI. I cannot imagine how a regulatory framework built around the concepts that underlie AI risk discourse will not be abused by wanna despots - the underlying terms are so vague and open to interpretation that you’re just handing a power hungry leader a fully loaded bazooka. 'Catastrophic risk.' 'Mass persuasion risk.' 'Threats to national security.' 'Autonomy risk.' These can mean whatever the government wants them to mean. Have you built a model that tells users the administration's tariff policy is misguided? That's a deceptive, manipulative model — can't deploy it. Have you built a model that refuses to assist with mass surveillance? That's a threat to national security. In fact, the government may say, you’re not allowed to build any model which is trained to have its own sense of right and wrong, where it refuses government requests which it thinks cross a redline - for example, enabling mass surveillance, prosecuting political enemies, disobeying military orders that break the US constitution - because that’s an autonomy risk! Look at what the current government is already doing in abusing statutes that have nothing to do with AI to coerce AI companies to drop their redlines on mass surveillance. The Pentagon had threatened Anthropic with two separate legal instruments. One was a supply chain risk designation — an authority from the 2018 defense bill meant to keep Huawei components out of American military hardware. The other was the Defense Production Act — a statute passed in 1950 so that Harry Truman could keep steel mills and ammunition factories running during the Korean War. Do you really want to hand the same government a purpose-built regulatory apparatus on AI - which is to say, directly at the thing the government will most want to control? I know I've repeated myself here 10 times, but it is hard to emphasize how much AI will be the substrate of our future civilization. You and I, as private citizens, will have our access to all commercial activity, to information about what is happening in the world, to advice about what we should do as voters and capital holders, mediated through AIs. Mass surveillance, while very scary, is like the 10th scariest thing the government could do with control over the AI systems with which we will interface with the world. The strongest objection to everything I've argued is this: are we really going to have zero regulation of the most powerful technology in human history? Even if you thought that was ideal, there’s just no world where the government doesn’t regulate AI in some way. Besides, it is genuinely true that regulation could help us deal with some of the coordination challenges we face with the development of superintelligence. The problem is, I honestly don't know how to design a regulatory architecture for AI that isn’t gonna be this huge tempting opportunity to control our future civilization (which will run on AIs) and to requisition millions of blindly obedient soldiers and censors and apparatchiks. While some regulation might be inevitable, I think it’d be a terrible idea for the government to wholesale take over this technology. Ben Thompson had a post last Monday where he made the point that people like Dario have compared the technology they’re developing to nuclear weapons - specifically in the context of the catastrophic risk it poses, and why we need to export control it from China. But then you oughta think about what that logic implies: “if nuclear weapons were developed by a private company, and that private company sought to dictate terms to the U.S. military, the U.S. would absolutely be incentivized to destroy that company.” And honestly, safety aligned people have actually made similar arguments. Leopold Ascenbrenner, who is a former guest and a good friend, wrote in his 2024 Situational Awareness memo, "I find it an insane proposition that the US government will let a random SF startup develop superintelligence. Imagine if we had developed atomic bombs by letting Uber just improvise." And my response to Leopold’s argument at the time, and Ben’s argument now, is that while they’re right that it’s crazy that we’re entrusting private companies with the development of this world historical technology, I just don’t see the reason to think that it’s an improvement to give this authority to the government. Nobody is qualified to steward the development of superintelligence. It is a terrifying, unprecedented thing that our species is doing right now, and the fact that private companies aren't the ideal institutions to take up this task does not mean the Pentagon or the White House is. Yes - if a single private company were the only entity capable of building nuclear weapons, the government would not tolerate that company claiming veto power over how those weapons were used. I think this nuclear weapons analogy is not the correct way to think about AI. For at least two important reasons: First, AI is not some self-contained pure weapon. A nuclear bomb does one thing. AI is closer to the process of industrialization itself — a general-purpose transformation of the economy with thousands of applications across every sector. If you applied Thompson's or Aschenbrenner's logic to the industrial revolution — which was also, by any measure, world-historically important — it would imply the government had the right to requisition any factory, dictate terms to any manufacturer, and destroy any business that refused to comply. That's not how free societies handled industrialization, and it shouldn't be how they handle AI. People will say, "Well, AI will develop unprecedentedly powerful weapons - superhuman hackers, superhuman bioweapons researchers, fully autonomous robot armies, etc - and we can’t have private companies developing that kind of tech." But the Industrial Revolution also enabled new weaponry that was far beyond the understanding and capacity of, say, 17th century Europe - we got aerial bombardment, and chemical weapons, not to mention nukes themselves. The way we’ve accommodated these dangerous new consequences of modernity is not by giving the government absolute control over the whole industrial revolution (that is, over modern civilization itself), but rather by coming up with bans and regulations on those specific weaponizable use cases. And we should regulate AI in a similar way - that is, ban specific destructive end uses (which would also be unacceptable if performed by a human - for example, launching cyber attacks). And there should also be laws which regulate how the government might abuse this technology. For example, by building an AI-powered surveillance state. The second reason that Ben’s analogy to some monopolistic private nuclear weapons builder breaks down is that it's not just that one company that can develop this technology. There are other frontier model companies that the government could have otherwise turned to. The government's argument that it has to usurp the property rights of this one company in order to access a critical national security capability is extremely weak if it can just make a voluntary contract with Anthropic’s half a dozen competitors. If in the future that stops being the case - if only one entity ends up being capable of building the robot armies and the superhuman hackers, and we had reason to worry that they could take over the whole world with their insurmountable lead, then I agree - it woul d not be acceptable to have that entity be a private company. And so honestly, I think my crux against the people who say that because AI is so powerful we cannot allow it to be shaped by private hands is that I just expect this technology to be much more multi-polar than they do, with lots of competitive companies at each layer of the supply chain. And it is for this reason that unfortunately, individual acts of corporate courage will not solve the problem we are faced with here, which is just that structurally AI favors authoritarian applications, mass surveillance being one among many. Even if Anthropic refuses to have its models be used for such uses, and even if the next two frontier labs do the same, within 12 months everyone and their mother will be to train AIs as good as today’s frontier. And at that point, there will be some AI vendor who is capable and willing to help the government enable mass surveillance. The only way we can preserve our free society is if we make laws and norms through our political system that it is unacceptable for the government to use AI to enforce mass surveillance and censorship and control. Just as after WW2, the world set the norm that it is unacceptable to use nuclear weapons to wage war. Timestamps 0:00:00 - Anthropic vs The Pentagon 0:04:16 - The overhangs of tyranny 0:05:54 - AI structurally favors mass surveillance 0:08:25 - Alignment... to whom? 0:13:55 - Coordination not worth the costs

Dwarkesh Patel

546,932 次观看 • 4 个月前

Min Hee-jin (NewJeans Producer) NHK Music Interview 🔗 “Meticulously planned debut ‘Attention’” 🧢: When I was preparing to launch NewJeans, I really struggled with deciding what our first piece of content should be. I thought about it for a long time and considered many possibilities. It was a project that came with high expectations, and for me personally, it was also my first opportunity to prove myself. So how I presented it mattered enormously. Even down to the smallest details… like the impression the very first released photo might give, or what kind of impact we could make at launch. I thought hard about what kind of content would be the most effective… should it be a video or a photo? What time of day would be most effective to release it? I consider things like that very carefully. For example, the way a person experiences content at night versus during the day can feel quite different emotionally. So I even thought about those subtle aspects. Eventually, the conclusion I reached was: “Let’s make the most of our situation.” At the time, the members hadn’t been revealed, and no one knew how many of them there were or what kind of group this would be. So I wanted to maximize that curiosity. You know how the more something is concealed, the more curious people become? I wanted to build that curiosity to a peak and then release everything all at once. That’s why we decided not to release a teaser and instead go straight into a full music video. (This was actually inspired by Hyein suggesting we skip teasers.) I didn’t think still images or photos would be enough to fully convey the feeling I wanted to express. I felt that video and music together would evoke the emotional response I was looking for because people experience things synesthetically. When sound, image, and feeling come together, the emotional impact is stronger. I believed the best way to present the members’ images was through music and a moving picture… that’s why we led with a music video. In the debut music video, “Attention,” there’s a scene where the members act out a little drama. I paid very close attention to that moment and created music that would fit it precisely. For me, I don’t just make content… I design the entire process of how it should be shown for the greatest effect. And I believe that’s incredibly important. That first feeling someone gets when they encounter something… that emotion, that spark… is so important to me. I’m very detail-oriented, but I also value fun deeply. So rather than just releasing content, I want to enjoy the process leading up to it. Even when we released our second album, since we shot the entire music video across the country, the sequence of how we released the videos was critical for me. It’s hard to explain all this simply in an interview, but maybe some people noticed: the first content we released that time was actually a teaser for the last track, “ASAP,” and then we followed that with the full music video for “New Jeans,” which was the first track. That order was a carefully calculated strategy. It was designed to guide the audience’s emotional journey. Seeing the audience react just as I had hoped—that whole process was honestly so fun and thrilling for me. I think I really enjoy that kind of thing. ——— “How 'Ditto' was born” 🧢: People often praise the music of NewJeans, and I hear a lot of talk about genres. But actually, I don’t feel bound by genre at all. I love a wide variety of music. I’m not the type to insist on only one particular genre. What I love are songs that blend genres cleverly… those are my personal favorites. So going forward, my focus is not on genre but on whether something feels fresh and whether it can create an emotional moment. I don’t want to define what kind of music we make. And I think you have to experience the flow of the times to really understand what’s meaningful in a given moment. For instance, the song “Ditto” was chosen because it delivered emotion. It matched perfectly with the winter album concept I had envisioned, both in terms of timing and mood. When I hear a song, I tend to trust my gut. I have a pretty strong intuition for which songs will resonate. It’s not about objectively predicting what will be a “hit,” but about whether a song moves your heart… you can just feel it. Of course, my own taste plays a big role. But I think that’s actually my strength as a producer, not as a composer. When I hear a song, I can immediately picture the visual… what kind of story, what kind of vibe it could carry. That allows me to work faster. For example, when expressing something like school uniforms, there are so many possible variations. But I always like to start from the basics… what’s the original idea of a school uniform? I try to return to that. So with “Ditto,” I wanted to tap into something primal… the pure, basic feeling of liking someone. That kind of emotion is universal. Everyone has it; it’s wired into us. When I saw Director Shin Woo-seok’s interpretation of it, I thought, “Yes, that’s it.” That’s the kind of complete interpretation I look for. I believe the completion of a project comes from every person involved thinking about their part down to the final detail… the maximum quality they can bring out. My role is to unify and refine all of that. I draw out the essence of each person’s creativity, trimming away anything unnecessary. So the final product is something that’s polished and high-quality, just the way I envisioned it. That’s my working style. So it’s not like I’m fixated on retro or stuck in a particular style. I don’t think human taste has changed all that much. Things people liked in the past are the same things we like now. It’s just the form of expression that changes with time. I don’t feel bound by “past” or “present.” I don’t even think in those boundaries. To me, it’s all just good taste. You know how kids sometimes have their own little treasure boxes when they’re young? I think my work is kind of like that. I want to make things that never feel dated—that are timelessly enjoyable. ——— “Dance Expression and 'Hype Boy'” 🧢: I had a vision of what kind of girl group I wanted to create. That’s why I chose a song like “Hype Boy.” And to bring out that feeling, we created four different versions of the music video. Every choice had a purpose, everything was designed to maximize the experience of the song. “Hype Boy” is such a unique song. It has this strange, piercing melody that gives people chills in a good way. To emphasize that tingling feeling, I had to break away from the standard K-pop choreography format… you know, the kind where everyone is in perfect formation, doing synchronized moves. But our songs don’t suit that kind of choreography. Our dances are much harder. They require the body to move very naturally with the groove of the melody and beat. So I think our members are incredible. It’s not easy to express naturalness with your body, and you have to really enjoy it to make it look effortless. But they pulled it off so well. They’re still young, but they’re so talented. And through it all, I wanted to avoid making them look like they were performing just for business. I wanted them to show the pure joy and bright spirit that’s natural for people their age… genuine, carefree, radiant. ——— “The difference between NewJeans and conventional K-POP” 🧢: Ah, for me, it’s all about naturalness. And honestly, naturalness isn’t something you can produce or direct into existence. It comes from how I interact with the NewJeans members on a daily basis… what kind of environment they practice in, how they live and work. There are so many things that don’t appear on camera, but those unseen aspects have to be in place in order for true naturalness to come through. That’s why I wanted to create that kind of environment for the girls. And also, I wanted to shape my own working environment in that way too. Only then can something truly natural, something unforced and not overly stimulating, really come out. To begin with, I don’t believe anyone can be completely natural in front of a camera or under the gaze of others. It’s human nature to become self-conscious. That’s why I think naturalness is our strength, but it can’t be our concept. If you try to turn “naturalness” into a concept, it actually becomes incredibly artificial. So why do I place so much importance on naturalness? It’s because the girls are still so young. While other kids their age are going through school and having a wide range of life experiences, these members are living very different lives. Before they officially debuted, I told them, “This is like studying together with me.” Our standard contract is seven years, which is about the same length as going through high school and college in Korea: three years of high school and four years of university. So I told them, “We’re going to school together. We’re learning together.” And in that sense, I want to be a good teacher to them. They’re also surrounded by an incredibly professional team, people they’d never meet even in a traditional school setting. I’ve never really liked the word idol. These days, that word is used more like a job title, something manufactured by the industry, and it’s far from its original meaning. To me, the term idol feels misplaced. It doesn’t really reflect who these artists are or what they represent. And I’m not the kind of person who clings to labels or terminology. In fact, what I really want is to break the stereotypes and preconceptions that come with the idol industry. I want us to show people something different… to challenge those assumptions and redefine what this can look like. That’s the kind of mindset I have. ——— “Isn't it difficult for the members to express "naturalness"?” 🧢: There were a lot of things I considered when forming the group. First and foremost, I think it was important that the members shared a similar vibe… like how I prefer working with staff who align with my taste. It’s important for the crew to be on the same wavelength. And by that, I mean more than just getting along… it also extends to shared values. Of course, people won’t all share identical values, but when we’re facing in a similar direction, everything becomes easier. It’s also just more efficient to work with people who have overlapping tastes. Now, when it comes to our members, they each have their own individual tastes, but those preferences are still in development. Just like we all went through as kids, they’re still growing, still discovering themselves. They’re not in a finished state. So we didn’t cast them based on some complete or polished version of themselves. It wasn’t like, “This person is fully formed, let’s pick her.” It was more like, “Ah, she has potential, there’s something there.” That sense of a spark… those were the kinds of subtleties I paid attention to. I didn’t cast anyone just because they were pretty or could sing well. I don’t work like that. I really value those finer, more delicate aspects. Even the design of the light stick wasn’t something that came from a long strategic planning session… it was actually a spontaneous idea. I didn’t sit down and think, “Let’s make a light stick like this.” NewJeans didn’t have a fixed logo, but I felt we still needed a unifying symbol. So one night, just before going to sleep, I kept thinking about it. Right before dozing off, I started sketching and it turned into a rabbit’s face. When I drew it out, the shape just continued and turned into a bunny. To me, the NewJeans members are like little bunnies… playful, innocent. Their visuals also resemble rabbits in a way. And rabbits symbolize abundance. That made me think: “Ah, maybe our fans will multiply like rabbits. That would be great.” So that bunny face became both a symbol for the members and the fans. The image came to me all at once, and I imagined a venue completely filled with bunny light sticks. That vision led to the creation of the light stick itself. Since I always prioritize fun in everything I do, the next idea that came to mind was making the light stick customizable. I thought, “Wouldn’t it be great if fans could personalize their bunny?” That way, each rabbit would represent a different person’s character. So we included accessories, allowing everyone to customize their own bunny. It’s symbolic of all these different bunnies coming together and enjoying a good time as one. Our light stick has a big head, so when it’s used in a concert hall, it lights up in heart shapes that are very visible. That was the image I really wanted. And that bunny face… it’s also a heart. It represents both the face of NewJeans and our hearts. It’s the love we’re showing to our fans, and the love we want to receive in return. Every time I see it, I feel deeply moved. It’s very emotional for me because it’s a perfect realization of what I envisioned. As someone with a background in creative direction, there’s nothing more satisfying than seeing an idea materialize exactly the way you imagined it. That kind of work holds deep meaning for me. ⸻ 🧢: Looking back, I think in 2023 we were able to achieve almost everything we had hoped for. I’m so incredibly grateful for that. Of course, this is an ongoing challenge… and the better things go, the more pressure there is. That’s why I always try to return to my original mindset. Just like I tell the members, I try to remind myself of the beginning and keep things fun. Back then, when we were first putting out content, planning the music, and working on visuals, I felt this thrill… this rush of excitement. I don’t want to forget that feeling. So I try hard to engrave that emotion into every album we release. I’m constantly working to rediscover the joy in all of it. So for 2024, I hope everyone can look forward to us with fresh anticipation. And even if we come out with something completely new, I hope people will receive it warmly and with excitement. That’s really my deepest wish. 🙏

1tokki

17,635 次观看 • 11 个月前

On March 15th, 2021, an anonymous Twitter user asked Harvard Medical professor Martin Kulldorff a question. “Do you think younger age groups and or people who have already had the virus need to be vaccinated?” Who is Martin Kulldorff? He’s a Harvard Medical School professor for 21 years, a well-known Swedish biostatistician who developed widely used software for disease mapping, the co-author of the Great Barrington Declaration on how to deal with the COVID pandemic, and an advisor to the world’s leading health organizations. What he said was that “Thinking that everyone must be vaccinated is as scientifically flawed as thinking that nobody should get COVID. Vaccines are important for older high-risk people and their caretakers. Those with prior natural infection do not need it, nor do children.” Natural immunity. Is it a myth — a “conspiracy theory” — that once you have been sick from a virus, then you won’t get sick, or as sick, again? In fact, we’ve known for 2,500 years that natural immunity is real. “The same man was never attacked twice, never at least fatally,” wrote Thucydides, describing the plague of Athens. He observed that recovered individuals could safely nurse the sick without falling ill themselves. And yet Twitter censored Martin Kulldorff’s tweet. “Learn why health officials recommend a vaccine,” read a warning that Twitter employees put on it. For most people, the Tweet cannot be replied to, shared or liked. In other words, Twitter had decided that this professor at Harvard Medical School was wrong, and that natural immunity wasn’t really something that could protect you from COVID. Jay Bhattacharya, who’s currently our Director of the National Institutes of Health, and thus one of the highest-ranking public health officials in the world, was a Stanford epidemiologist before that. Twitter put him on a “Trends Blacklist.” Not long before we discovered this, we were told that shadow-banning was a conspiracy theory, because Twitter had said it didn’t shadow-ban. Now the European Commission is trying to censor the entire global internet. They want to put a 140 million Euro fine on X. They want to end anonymity, which was what allowed that question of Kulldorff to be asked. They want to use a “Democracy Shield” program to shield the Commission from democracy. And the Commission wants to impose “chat control” so they can read your private messages. It just gets worse and worse. Unsubstantiated and likely false claims of Russian government election interference through TikTok and social media were made in Romania and in the Czech Republic. Truth is not something that anybody holds as a possession and rather emerges through dialogue. We’ve known that since Plato and Socrates. We need free speech for science, public health, and national security. It’s essential to journalism, democracy, and human freedom. Free speech enabled civilization; censorship threatens it. This is the only political cause that I would die for. And yet there is currently an active coordination between Stanford, Brazil, Australia, and others to impose what I think we can call, without exaggeration, global totalitarianism. They’re pushing for digital identification that will end anonymity online. Why is that? Why are these guys behaving in this way? When Elon Musk took over Twitter on October 28th, 2022, unprecedented insight into multiple secret government mass censorship efforts emerged from this exploration. We had unlimited access to Twitter files. They revealed that the mainstream news reporters, who don’t deserve the name, were demanding censorship. No true journalist demands censorship of his fellow journalists. What emerged from this was an understanding of something we call the “Censorship Industrial Complex,” which directly grew out of the military industrial complex and was run by active or former intelligence community officials who often operate under that banner. It led to multiple congressional investigations and hearings, and it spread across every social media platform. So we now know the censorship that occurred, not just at Twitter, but at YouTube, at Facebook, TikTok, and other platforms. What is the Censorship Industrial Complex? The model isn’t that complicated to understand. The government chooses people whom they call “researchers” to serve as censors. These are government-funded individuals who often come from the intelligence community and foreign policy establishment. They work at non-governmental organizations funded by governments or at universities funded by governments. They conduct “fact checks” to serve as “trusted flaggers.” These “trusted flaggers” demand censorship by social media platforms. It’s all done in secret. They’re looking to censor narratives. This is essential because, as decades of good cognitive science have shown, people understand and retain information through storytelling. We think in terms of stories, not bullet points. And so they were out to censor whole narratives. From the Stanford censorship project on COVID, the “Virality Project,” they said they wanted to censor “true stories” of vaccine side effects. Why? Because it might “fuel hesitancy.” In other words, they want to control your behavior. They don’t want you to receive true information that might lead you to not get the vaccine. If that isn’t totalitarianism straight out of 1984, I don’t know what it. These people were on the verge of passing legislation in the United States that would’ve authorized the National Science Foundation to choose these “researcher” censors. I’m presenting slides to Europeans and the world for situational awareness into what totalitarian politicians and bureaucrats have planned because this is still going strong. Stanford helped the US government censor COVID dissidents, and then they lied about it. You might be detecting a pattern. They’re really not interested in censoring “misinformation.’ They’re very interested in censoring true information. The censors flagged an Israeli preprint which came out in December, 2020 and found, lo and behold, that natural immunity is a real thing. In fact, it’s more protective than the vaccine. But the censors flagged somebody’s Google Drive. “See the following Google Drive links being used to compile testimonies about vaccine shedding, Covid videos, showing side effects and whatnot.” Google then removed that content from that person’s Google Drive. You don’t control your Google Drive. Contrary to Stanford’s claim that the project did not ask social media platforms to remove any content, they privately said they did. And we know that many hundreds of thousands of tweets and Facebook posts were removed, even though they were a hundred percent accurate. In fact, in 2021, Stanford’s “Virality Project” flagged accurate claims that the World Health Organization did not recommend vaccinating children. The people who spread the misinformation are the people demanding the censorship. They claimed Covid couldn’t have come from a lab, that the Covid vaccine prevented infection, and that natural immunity didn’t exist. The only solution to hate speech and misinformation is free speech. If you censor false information, how would anybody get the true information? The whole point is the debate. They lied when they said false information travels faster than true information. It’s a completely bogus study and involved six seconds of content on Twitter. Who are these people? As of 2020, there were so many former FBI employees at Twitter that they called them “Bu alumni.” They created their own private Slack channel and a crib sheet to onboard new FBI arrivals. Intriguingly, we discovered that the general counsel of the FBI — arguably the second most powerful person of the FBI, or maybe the first, if you think, consider that what their actual job is to decide what the FBI can and can’t do — resigned from FBI in early 2020 and went to Twitter to take the deputy general counsel role. Isn’t that interesting? Somebody in one of the most powerful legal positions in the world would take a junior legal role at a social media company. Why would that be? This email popped up when we were going through Twitter files and it really jumped out at us. It’s from the director of policy at Twitter. “We have seen a sustained if uncoordinated” — supposedly — “effort by the intelligence community to push us to share more information and change our API policies. They’re probing and pushing everywhere they can.” The Hunter Biden laptop censorship occurred later that year. The FBI and the intelligence community discredited accurate, factual information about Hunter Biden’s foreign business dealings both before and after the New York Post revealed the contents of his laptop on October 14th, 2020. How could the FBI spread false information about something that nobody knew about? Because the FBI had Hunter Biden’s laptop, which showed his family’s massive influence peddling scheme. It consisted of accepting tens of millions of dollars, including from the Chinese government. The FBI had been sitting on that laptop since December of 2019. They had been given it by the computer repair store owner, who had been given the laptop by Hunter Biden, likely because he dropped it in his bathtub or in the pool, when he was on one of his many crack and alcohol benders. The government strategy is always the same: spread disinformation first, then demand censorship of accurate information on the basis of it . “The FBI came to us in the summer of 2020,” Mark Zuckerberg told Joe Rogan two years later, “and they were like, ‘Hey, you should be on the alert. We thought that there was a lot of Russian propaganda in 2016. There’s about to be some kind of dump.’” In the summer of 2020, the New York Post had not published the story about the Hunter Biden laptop. It would only come out in October. We see something very interesting show up in the Twitter files: the Aspen Institute, an intermediary between the intelligence community and the public. It’s known as a Davos-style gab fest in the United States. It’s also the place where intelligence community operations are run. They hosted a workshop to train reporters and all of the social media’s top censorship officials, known as “trust and safety officials,” how to deal with a story they would hear in the future relating to Hunter Biden and Barisma. A few months earlier, the Stanford Cyber Policy Center had published a report attacking what we in the United States call the Pentagon Papers Principle. The Pentagon Papers Principle says that if a government official gives me, a journalist, a bunch of Pentagon documents showing that we’re losing the war in Vietnam, I, as a journalist, can publish them, and not risk prison. That was decided in a famous Supreme Court case in 1971. Stanford argued that, really, we should get rid of that principle, which may be the most important investigative journalism principle in the United States, and said, “You should cover the person who leaked the materials, not the leaked emails.” In other words, you should cover and expose the whistleblower. The person who exposed the Pentagon Papers is the real bad guy, not the DOD, CIA, and presidents who had lied to us for over a decade. Stanford was training the journalists and the social media trust and safety officers in how to cover a story that had not yet come out. This is known as “pre-bunking,” and it’s also part of the European Union strategy to shield themselves from democracy. When the Hunter Biden story appeared October 22nd, Twitter’s trust and safety censorship official said it didn’t violate its terms of service. There’s nothing illegal about any of this. The Supreme Court has made it very clear that you’re allowed to report on information that’s been leaked to you. At that moment, the former FBI general counsel, Jim Baker, argued vigorously that Twitter really needed to censor it. Baker won and they censored the story. It’s not that we didn’t hear about the Hunter Biden laptop story when it came out. I certainly did. But we had the impression that there was something wrong with it, that it was not really the whole story. And so many of us dismissed it. What they had done was a psyop on this major story. They had changed our perception of the story. And it worked. It worked on me, it worked on everybody I knew. What is the role of the intelligence community of social media companies? The former CIA people are the head of elections at Meta, and Google’s head of trust and safety. Former and current CIA officers have a history of spreading misinformation and promoting the Russiagate conspiracy theory. We now know that between 2018 and 2023, there were 36 people from the CIA 68 from the FBI 44, from the National Security Administration and 68 from the Department of Homeland Security who had moved to work at the social media platforms. This is not unique to the United States. My colleague Cecilia Jilková, the daughter of famous Czech dissidents, discovered that European Union officials claimed, days before the European elections in 2024, that a “pro-Kremlin website” was spreading propaganda and were paying off European politicians. That was the headline in Politico. We wrote to them and asked, “Where’s the evidence of this? Just go ahead and share the evidence to support your accusation days before the European parliamentary elections.” Nobody was arrested. They never produced the evidence. The former Czech president, Václav Klaus, who was accused of this, said, “We don’t even know what the ‘Voice of Europe’ is.” Another Czech politician said, “How could I have known it would be a security threat? At the time I gave the interview, they weren’t on any list.” Another said, “If they’re such a big threat, why did the European Parliament let the Voice of Europe’s journalists inside?” Nobody responded. Nobody talked to us. This was a disinformation campaign carried by Politico, which, in my view, is a suspect publication. In the spring of 2022, Barack Obama went to Stanford to give a speech at the Stanford Cyber Policy Center run by Michael McFaul, his former ambassador to Russia. Obama said misinformation harms democracy and urged support for legislation in Congress that would empower government-appointed researchers to serve as “trusted flaggers.” Six days later, the Department of Homeland Security rolled out their Disinformation Governance Board. What a coincidence that they got Obama to frame the issue for them. Facebook in 2021 censored accurate vaccine information so the White House would help it to get data from Europe. In addition to removing vaccine misinformation, wrote Facebook to the White House, we have been focused on reducing the virality of content discouraging vaccines that does not contain actionable misinformation. White House said jump, and Facebook said how high? Why did they do it? Why would they voluntarily censor? This also emerged from the Facebook files. Nick Clegg on the left wrote an email to his colleagues. He said, “My sense is that given we’ve got bigger fish, we have to fry with the administration, e.g., data flows, it doesn’t seem like a great place for us to be.” Data flows. What’s he talking about? He’s talking about billions of dollars worth of business that he has to, that they would have to pay the European Commission for if they didn’t have the support from the Biden administration to lean on the European Commission. In other words, this was a shakedown by the White House of Facebook and it worked in France, the country of Liberté. Turns out it has a special role.... Please subscribe now to support Public's defense of free speech, watch the full video, and read the rest of the article!

On March 15th, 2021, an anonymous Twitter user asked Harvard Medical professor Martin Kulldorff a question. “Do you think younger age groups and or people who have already had the virus need to be vaccinated?” Who is Martin Kulldorff? He’s a Harvard Medical School professor for 21 years, a well-known Swedish biostatistician who developed widely used software for disease mapping, the co-author of the Great Barrington Declaration on how to deal with the COVID pandemic, and an advisor to the world’s leading health organizations. What he said was that “Thinking that everyone must be vaccinated is as scientifically flawed as thinking that nobody should get COVID. Vaccines are important for older high-risk people and their caretakers. Those with prior natural infection do not need it, nor do children.” Natural immunity. Is it a myth — a “conspiracy theory” — that once you have been sick from a virus, then you won’t get sick, or as sick, again? In fact, we’ve known for 2,500 years that natural immunity is real. “The same man was never attacked twice, never at least fatally,” wrote Thucydides, describing the plague of Athens. He observed that recovered individuals could safely nurse the sick without falling ill themselves. And yet Twitter censored Martin Kulldorff’s tweet. “Learn why health officials recommend a vaccine,” read a warning that Twitter employees put on it. For most people, the Tweet cannot be replied to, shared or liked. In other words, Twitter had decided that this professor at Harvard Medical School was wrong, and that natural immunity wasn’t really something that could protect you from COVID. Jay Bhattacharya, who’s currently our Director of the National Institutes of Health, and thus one of the highest-ranking public health officials in the world, was a Stanford epidemiologist before that. Twitter put him on a “Trends Blacklist.” Not long before we discovered this, we were told that shadow-banning was a conspiracy theory, because Twitter had said it didn’t shadow-ban. Now the European Commission is trying to censor the entire global internet. They want to put a 140 million Euro fine on X. They want to end anonymity, which was what allowed that question of Kulldorff to be asked. They want to use a “Democracy Shield” program to shield the Commission from democracy. And the Commission wants to impose “chat control” so they can read your private messages. It just gets worse and worse. Unsubstantiated and likely false claims of Russian government election interference through TikTok and social media were made in Romania and in the Czech Republic. Truth is not something that anybody holds as a possession and rather emerges through dialogue. We’ve known that since Plato and Socrates. We need free speech for science, public health, and national security. It’s essential to journalism, democracy, and human freedom. Free speech enabled civilization; censorship threatens it. This is the only political cause that I would die for. And yet there is currently an active coordination between Stanford, Brazil, Australia, and others to impose what I think we can call, without exaggeration, global totalitarianism. They’re pushing for digital identification that will end anonymity online. Why is that? Why are these guys behaving in this way? When Elon Musk took over Twitter on October 28th, 2022, unprecedented insight into multiple secret government mass censorship efforts emerged from this exploration. We had unlimited access to Twitter files. They revealed that the mainstream news reporters, who don’t deserve the name, were demanding censorship. No true journalist demands censorship of his fellow journalists. What emerged from this was an understanding of something we call the “Censorship Industrial Complex,” which directly grew out of the military industrial complex and was run by active or former intelligence community officials who often operate under that banner. It led to multiple congressional investigations and hearings, and it spread across every social media platform. So we now know the censorship that occurred, not just at Twitter, but at YouTube, at Facebook, TikTok, and other platforms. What is the Censorship Industrial Complex? The model isn’t that complicated to understand. The government chooses people whom they call “researchers” to serve as censors. These are government-funded individuals who often come from the intelligence community and foreign policy establishment. They work at non-governmental organizations funded by governments or at universities funded by governments. They conduct “fact checks” to serve as “trusted flaggers.” These “trusted flaggers” demand censorship by social media platforms. It’s all done in secret. They’re looking to censor narratives. This is essential because, as decades of good cognitive science have shown, people understand and retain information through storytelling. We think in terms of stories, not bullet points. And so they were out to censor whole narratives. From the Stanford censorship project on COVID, the “Virality Project,” they said they wanted to censor “true stories” of vaccine side effects. Why? Because it might “fuel hesitancy.” In other words, they want to control your behavior. They don’t want you to receive true information that might lead you to not get the vaccine. If that isn’t totalitarianism straight out of 1984, I don’t know what it. These people were on the verge of passing legislation in the United States that would’ve authorized the National Science Foundation to choose these “researcher” censors. I’m presenting slides to Europeans and the world for situational awareness into what totalitarian politicians and bureaucrats have planned because this is still going strong. Stanford helped the US government censor COVID dissidents, and then they lied about it. You might be detecting a pattern. They’re really not interested in censoring “misinformation.’ They’re very interested in censoring true information. The censors flagged an Israeli preprint which came out in December, 2020 and found, lo and behold, that natural immunity is a real thing. In fact, it’s more protective than the vaccine. But the censors flagged somebody’s Google Drive. “See the following Google Drive links being used to compile testimonies about vaccine shedding, Covid videos, showing side effects and whatnot.” Google then removed that content from that person’s Google Drive. You don’t control your Google Drive. Contrary to Stanford’s claim that the project did not ask social media platforms to remove any content, they privately said they did. And we know that many hundreds of thousands of tweets and Facebook posts were removed, even though they were a hundred percent accurate. In fact, in 2021, Stanford’s “Virality Project” flagged accurate claims that the World Health Organization did not recommend vaccinating children. The people who spread the misinformation are the people demanding the censorship. They claimed Covid couldn’t have come from a lab, that the Covid vaccine prevented infection, and that natural immunity didn’t exist. The only solution to hate speech and misinformation is free speech. If you censor false information, how would anybody get the true information? The whole point is the debate. They lied when they said false information travels faster than true information. It’s a completely bogus study and involved six seconds of content on Twitter. Who are these people? As of 2020, there were so many former FBI employees at Twitter that they called them “Bu alumni.” They created their own private Slack channel and a crib sheet to onboard new FBI arrivals. Intriguingly, we discovered that the general counsel of the FBI — arguably the second most powerful person of the FBI, or maybe the first, if you think, consider that what their actual job is to decide what the FBI can and can’t do — resigned from FBI in early 2020 and went to Twitter to take the deputy general counsel role. Isn’t that interesting? Somebody in one of the most powerful legal positions in the world would take a junior legal role at a social media company. Why would that be? This email popped up when we were going through Twitter files and it really jumped out at us. It’s from the director of policy at Twitter. “We have seen a sustained if uncoordinated” — supposedly — “effort by the intelligence community to push us to share more information and change our API policies. They’re probing and pushing everywhere they can.” The Hunter Biden laptop censorship occurred later that year. The FBI and the intelligence community discredited accurate, factual information about Hunter Biden’s foreign business dealings both before and after the New York Post revealed the contents of his laptop on October 14th, 2020. How could the FBI spread false information about something that nobody knew about? Because the FBI had Hunter Biden’s laptop, which showed his family’s massive influence peddling scheme. It consisted of accepting tens of millions of dollars, including from the Chinese government. The FBI had been sitting on that laptop since December of 2019. They had been given it by the computer repair store owner, who had been given the laptop by Hunter Biden, likely because he dropped it in his bathtub or in the pool, when he was on one of his many crack and alcohol benders. The government strategy is always the same: spread disinformation first, then demand censorship of accurate information on the basis of it . “The FBI came to us in the summer of 2020,” Mark Zuckerberg told Joe Rogan two years later, “and they were like, ‘Hey, you should be on the alert. We thought that there was a lot of Russian propaganda in 2016. There’s about to be some kind of dump.’” In the summer of 2020, the New York Post had not published the story about the Hunter Biden laptop. It would only come out in October. We see something very interesting show up in the Twitter files: the Aspen Institute, an intermediary between the intelligence community and the public. It’s known as a Davos-style gab fest in the United States. It’s also the place where intelligence community operations are run. They hosted a workshop to train reporters and all of the social media’s top censorship officials, known as “trust and safety officials,” how to deal with a story they would hear in the future relating to Hunter Biden and Barisma. A few months earlier, the Stanford Cyber Policy Center had published a report attacking what we in the United States call the Pentagon Papers Principle. The Pentagon Papers Principle says that if a government official gives me, a journalist, a bunch of Pentagon documents showing that we’re losing the war in Vietnam, I, as a journalist, can publish them, and not risk prison. That was decided in a famous Supreme Court case in 1971. Stanford argued that, really, we should get rid of that principle, which may be the most important investigative journalism principle in the United States, and said, “You should cover the person who leaked the materials, not the leaked emails.” In other words, you should cover and expose the whistleblower. The person who exposed the Pentagon Papers is the real bad guy, not the DOD, CIA, and presidents who had lied to us for over a decade. Stanford was training the journalists and the social media trust and safety officers in how to cover a story that had not yet come out. This is known as “pre-bunking,” and it’s also part of the European Union strategy to shield themselves from democracy. When the Hunter Biden story appeared October 22nd, Twitter’s trust and safety censorship official said it didn’t violate its terms of service. There’s nothing illegal about any of this. The Supreme Court has made it very clear that you’re allowed to report on information that’s been leaked to you. At that moment, the former FBI general counsel, Jim Baker, argued vigorously that Twitter really needed to censor it. Baker won and they censored the story. It’s not that we didn’t hear about the Hunter Biden laptop story when it came out. I certainly did. But we had the impression that there was something wrong with it, that it was not really the whole story. And so many of us dismissed it. What they had done was a psyop on this major story. They had changed our perception of the story. And it worked. It worked on me, it worked on everybody I knew. What is the role of the intelligence community of social media companies? The former CIA people are the head of elections at Meta, and Google’s head of trust and safety. Former and current CIA officers have a history of spreading misinformation and promoting the Russiagate conspiracy theory. We now know that between 2018 and 2023, there were 36 people from the CIA 68 from the FBI 44, from the National Security Administration and 68 from the Department of Homeland Security who had moved to work at the social media platforms. This is not unique to the United States. My colleague Cecilia Jilková, the daughter of famous Czech dissidents, discovered that European Union officials claimed, days before the European elections in 2024, that a “pro-Kremlin website” was spreading propaganda and were paying off European politicians. That was the headline in Politico. We wrote to them and asked, “Where’s the evidence of this? Just go ahead and share the evidence to support your accusation days before the European parliamentary elections.” Nobody was arrested. They never produced the evidence. The former Czech president, Václav Klaus, who was accused of this, said, “We don’t even know what the ‘Voice of Europe’ is.” Another Czech politician said, “How could I have known it would be a security threat? At the time I gave the interview, they weren’t on any list.” Another said, “If they’re such a big threat, why did the European Parliament let the Voice of Europe’s journalists inside?” Nobody responded. Nobody talked to us. This was a disinformation campaign carried by Politico, which, in my view, is a suspect publication. In the spring of 2022, Barack Obama went to Stanford to give a speech at the Stanford Cyber Policy Center run by Michael McFaul, his former ambassador to Russia. Obama said misinformation harms democracy and urged support for legislation in Congress that would empower government-appointed researchers to serve as “trusted flaggers.” Six days later, the Department of Homeland Security rolled out their Disinformation Governance Board. What a coincidence that they got Obama to frame the issue for them. Facebook in 2021 censored accurate vaccine information so the White House would help it to get data from Europe. In addition to removing vaccine misinformation, wrote Facebook to the White House, we have been focused on reducing the virality of content discouraging vaccines that does not contain actionable misinformation. White House said jump, and Facebook said how high? Why did they do it? Why would they voluntarily censor? This also emerged from the Facebook files. Nick Clegg on the left wrote an email to his colleagues. He said, “My sense is that given we’ve got bigger fish, we have to fry with the administration, e.g., data flows, it doesn’t seem like a great place for us to be.” Data flows. What’s he talking about? He’s talking about billions of dollars worth of business that he has to, that they would have to pay the European Commission for if they didn’t have the support from the Biden administration to lean on the European Commission. In other words, this was a shakedown by the White House of Facebook and it worked in France, the country of Liberté. Turns out it has a special role.... Please subscribe now to support Public's defense of free speech, watch the full video, and read the rest of the article!

Michael Shellenberger

174,297 次观看 • 6 个月前

Like seemingly everyone on this app I have plenty of opinions about Twitter > X and figure now is a good time to open up a bit about my experience at the company. I tweeted for years into the void for the love of it like many of you, but after selling my startup to Twitter in 2020 I finally got to see it from the inside. Up close it was both amazing and terrible, like so many other companies and things in life. As someone with a maniacal sense of urgency built into me, Twitter often felt siloed and bureaucratic. Dumb power plays, reorgs and team name changes for the sake of someone’s ego were distractions that occurred too regularly. You couldn’t just be a builder — you also needed to be a politician. I was shocked by how old and bespoke the infrastructure was, but there was little will to think beyond quarterly earnings calls because we were all beholden to the masters of mDAU and revenue growth as a public company. It often felt like things were held together with duct tape and glue, and that many people had just accepted that a small product change could take months or quarters to build. Management had become bloated to accommodate career growth and the company culture felt too soft and entitled for my own taste. Healthy debate and criticism was replaced by a default refrain of “no, that can’t be done” or “another team owns that so don’t touch it”. Teams could spend months building a feature and then some last-minute kerfuffle meant it’d get killed for being too risky. Just talking directly to customers could turn into a turf war and create deadlocks between functions. I recall one such episode where a teammate spent a month trying to get clearance to reach out to some creators. He went through 3 layers of management and 6 different functional teams. In the end 4 executives were involved in the approval. It was insanity, and unfortunately I saw several top performers get burnt out and demoralized after exhausting experiences like that. Most people were good at their jobs but it was nearly impossible to fire poor performers — instead they got shuffled around to other teams because few managers had the will or resources to figure out how to get them out. A high performance culture pulls everyone up, but the opposite weighs everyone down. Twitter often felt like a place that kept squandering its own potential, which was sad and frustrating to see. The person who was best at cutting through the BS and inspiring a vision during my tenure was Kayvon Beykpour, but he wasn’t fully empowered to run the company since he wasn’t the CEO. Despite those real issues, I was lucky enough to work with some of the most talented people in the business at Twitter in product, design, engineering, research, legal, BD, trust & safety, marketing, PR and more. Often it was a small cross-functional team of intrinsically motivated people who made the biggest impact by challenging some core assumption. Those teams were very fun to be on but they felt like the exception rather than the rule. The months of waiting for the deal to close in 2022 were particularly slow and painful; it felt like leadership hid behind lawyers and legal language as all answers about the company’s future notoriously included the phrase “fiduciary duty”. Colleagues openly talked about how Twitter was being sold because leadership didn’t have conviction in their own plan or ability to fix longstanding problems. Although I didn’t know much about Elon I was cautiously optimistic – I saw him as the guy who built incredible and enduring companies like Tesla and SpaceX, so perhaps his private ownership could shake things up and breathe new life into the company. My take on what’s happened since then is full of lived nuance. When people ask why I stayed it’s easy to answer: optimism, curiosity, personal growth and money. From the beginning I saw that some changes Elon was going to make were smart and others were stupid, but when I’m on a team I uphold the philosophy of “praise in public and criticize in private”. I was far from a silent wallflower. I shared my opinions openly and pushed back often, both before and after the acquisition. I made peace with the fact that I didn’t have psychological safety at Twitter 2.0 and that meant I could be fired at any moment, and for no reason at all. I watched it happen repeatedly and saw how negatively it impacted team morale. Although I couldn’t change the situation I did my best to shine a light on folks who were doing important work while being an emotionally supportive leader for those who were struggling to adapt to the more brutalist and hardcore culture. In person Elon is oddly charming and he’s genuinely funny. He also has personality quirks like telling the same stories and jokes over and over. The challenge is his personality and demeanor can turn on a dime going from excited to angry. Since it was hard to read what mood he might be in and what his reaction would be to any given thing, people quickly became afraid of being called into meetings or having to share negative news with him. At times it felt like the inner circle was too zealous and fanatical in their unwavering support of everything he said. When individuals encouraged me to be careful about what I said I politely thanked them and said I would not be taking their advice. I had no interest in adding to a culture of fear or walking on eggshells around Elon. Either he would respect me for being real or he could fire me. Either outcome was okay. I quickly learned that product and business decisions were nearly always the result of him following his gut instinct, and he didn’t seem compelled to seek out or rely on a lot of data or expertise to inform it. That was particularly frustrating for me since I believed I had useful institutional knowledge that could help him make better decisions. Instead he'd poll Twitter, ask a friend, or even ask his biographer for product advice. At times it seemed he trusted random feedback more than the people in the room who spent their lives dedicated to tackling the problem at hand. I never figured out why and remain puzzled by it. I don’t think things had to be as difficult or dramatic as they turned out to be but I can’t say I’d bet against Elon or count him out. He’s smart and has enough money to make a lot of mistakes and then course correct when things go awry. As the largest shareholder he can tank the value in the short-term, but eventually he’ll need things to turn around. His focus on speed is incredible and he’s obviously not afraid of blowing things up, but now the real measure will be how it get reconstructed and if enough people want the new everything app he is building. I learned a ton from watching Elon up close – the good, the bad and the ugly. His boldness, passion and storytelling is inspiring, but his lack of process and empathy is painful. Elon has an exceptional talent for tackling hard physics-based problems but products that facilitate human connection and communication require a different type of social-emotional intelligence. Social networks are hard to kill but they’re not immune from death spirals. Only time will tell what the outcome will be but I hope X finds its footing because competition is good for consumers. In the meantime, I have a lot of empathy for the employees who are working tirelessly behind the scenes, the advertisers who want a stable platform to sell their stuff on, and the customers who are experiencing chaotic updates. It’s been a madhouse. Twitter moved at the speed of molasses and suffered from bureaucracy but now X is run by a mercurial leader whose instinct is driven by the unique and undoubtedly weird experience of being the biggest voice on the platform. Many of you know me from the sleeping bag incident where I slept on a conference room floor, so I figure, let’s talk about that too. Going viral was an odd and interesting experience. I was attacked by people on the left and called a billionaire bootlicker, while simultaneously being attacked by people on the right for being a working mom who was demonized as an example of a woman choosing her career over her family. Thankfully I can laugh at myself and I don’t take armchair keyboard ideologues too seriously. Being the main character on the timeline, even for a few minutes, requires a thick skin and a strong sense of self. The real story is pretty simple. I was given a nearly impossible deadline for his first project and as the product lead I would never ask anyone to do anything I wasn’t willing to do myself. So I worked round the clock alongside an amazing team spanning many timezones, and we delivered it on schedule – truly against the odds. It was intense but also fun. Those first few months were wildly crazy but I wanted to be there and I have no regrets. Showing up and giving it your all should, in most cases, be celebrated. Obviously you can’t work at that pace forever but there are moments where bursts are mission critical. I’ve pulled many all-nighters in my career and also when I was a student for something that mattered to me. I don’t regret putting in long hours or being ambitious, and feel proud of how far I’ve come from where I started thanks in part to that type of work ethic. I think of life as a game, and being at Twitter after the acquisition was like playing life at Level 10 on Hard Mode. Since I like taking on difficult challenges I found it interesting and rewarding because I was growing and learning so rapidly. I realize our society today trends toward polarization but when it comes to this app, its owner, and its future, I am neither a fangirl nor a hater — I’m an optimistic pragmatist. This may really irritate the internet but you cannot pigeonhole me into some radical position of either loving or hating every change that’s occurred. I escaped my fundamentalist upbringing and am a free thinker these days. Everyone can be seen as both a hero or a villain, depending on who is telling what angle of the story. Elon doesn’t deserve to be venerated or vilified. He’s a complicated person with an unfathomable amount of financial and geopolitical power which is why humanity needs him to err on the side of goodness, rather than political divisiveness and pettiness. I disagree with many of his decisions and am surprised by his willingness to burn so much down, but with enough money and time, something new & innovative may emerge. I hope it does. Sometimes I get asked about how I felt when I got laid off, and the truth is it was the best gift I’ve ever received. Sure the headlines and punchlines wrote themselves but I was battle hardened by then. I knew that I’d worked in a way where I could walk out with my head held high. I have no bitterness about the Product Management team being dismantled, and it made sense for me to exit as nearly all of the remaining PMs were let go. Going on a sabbatical afterward has been exactly what I needed to decompress and I’m finally feeling rested and relaxed. I’m a creative and a builder, so sooner than later I’ll jump back into a high intensity company but I’m grateful for this season of thinking, reading, traveling and being with people I love. After having time to reflect I believe more than ever that the very best outcomes flow from great leadership that combines the head and the heart. I’d be remiss if I didn’t note that in all of this there is also a cautionary tale for anyone who succeeds at something — which is that the higher you climb, the smaller your world becomes. It’s a strange paradox but the richest and most powerful people are also some of the most isolated. I found myself frequently looking at Elon and seeing a person who seemed quite alone because his time and energy was so purely devoted to work, which is not the model of a life I want to live. Money and fame can create psychological prisons which may worsen mental health conditions. We’ve all seen high profile cases of celebrities who end up with some combination of depression, paranoia, delusions of grandeur, mania and/or erratic behavior. Living in an echo chamber is dangerous and being at the top makes a person even more susceptible to being surrounded by yes people when nearly everyone around you is on the payroll and somehow stands to benefit from being in your orbit. Figuring out how to keep “better angels” around in the form of family, friends, and teammates is critical to staying on the rails and enduring intense ups and downs. Everyone needs to hear hard truths sometimes and if you fire all the people who speak up then the reality distortion field may just turn into a vortex. I was drawn to Twitter because I’m obsessed with the problem of loneliness and connection between people. I find it fascinating & troubling that humans are getting lonelier as we simultaneously create a world that’s both safer and wealthier. I don’t believe that trade-off has to exist, which is why I keep returning to that theme in my personal and professional life. I realize this is too long of a tweet but Twitter was a weird and special place on the internet, and I’m grateful to have played a teeny tiny role in its story and evolution. I’m here for whatever comes next — on this app and in new places. Consumer social is very much alive and at a fascinating juncture, so I’ll be watching and participating and sharing hot takes because I don’t want to, and probably can’t, turn that part of me off. Perhaps X becomes a resounding success. Or it fails epically. Either way, I expect it will continue to be a very entertaining ride. 🫡

Esther Crawford ✨

5,496,730 次观看 • 3 年前

I’ve been using GPT-5.6 Sol internally for the past two months, I've spent probably 25+ billion tokens. Here’s my review and comparison to Fable 5: > Let's start with the analogy because everyone seems to be giving theirs - GPT-5.6 is likely the last version of the GPT-5 training run series. It's kind of like an athlete at their peak. Through years of experience in the game, they've become the most reliable player and has the highest game IQ. But, there's no more room to grow. Fable on the other hand, being essentially the first version of a new training run, is the first round draft pick rookie. Raw talent mixed with the energy only a young person would have results in some incredible plays we didn't think possible, but also mistakes due to lack of experience. But that rookie will only improve and likely will be better than the veteran ever was because it's a new game and a new era. > GPT-5.6 is genuinely better at long, sustained work. With /goal, I've had it running complex projects for days with almost no intervention. It built a Minecraft-style game, kept adding features and mobs after the core game worked, and only stopped because I stopped the run. I never felt as though I had to jump in and guide it back to the right path. > It keeps finding useful work when you give it a concrete finish line. I had it recreate Excel with a loop. It inspected the real desktop excel app with Computer Use, comparing that against its own build, and closing the gaps. I stopped it after six days after it had built an incredible amount of functionality. > It's faster than other models in two different ways. The raw generation speed is higher, something OpenAI has been putting effort into. But it also takes a shorter path to solutions. It wanders less, changes less code, and generally knows how to get things done directly. In daily use, it feels about 2-3x times faster than Fable. That's my impression, not a controlled benchmark. The difference is large enough that I notice it constantly. > It works well across a wide range of tasks. I use it for one-line edits, quick questions, browser chores, and multi-day builds without changing my prompting style. Speaking of browser control, its the best ever I've used. To the point where I actually use it often. If a task lives on a website, GPT-5.6 usually opens the browser and does it there instead of asking for an API key or forcing everything through the terminal. When I switched back to GPT-5.5, it went straight to the command line even when the browser was clearly the better tool. > And it can handle real browser work, not just toy demos. During a data import, I had it monitor Supabase and resize instances as the load changed. It stayed on the dashboard, adjusted capacity, and checked the result without an API or a custom script. > I also gave it a full Google Workspace migration. It moved Forward Future from to preserved the old aliases, and configured MX, SPF, and DKIM. Before a consequential save, it stopped, explained exactly what would change, and waited for confirmation. > The reasoning setting matters a lot. Light is good for questions and small edits. High and Extra High are the sweet spots for serious work. Ultra usually takes longer than the extra thinking is worth and burns tokens. > I love that 5.6 is split into 3 sizes. Not only can you control speed and cost that way, but you still also have the thinking effort setting for each of them. Very precise controls. I just wish Codex automatically routed my prompts for me. > Its personality is blunt and a little bland. Claude feels warmer and more natural to talk to. GPT-5.6 is more clinical, but I like that for work. It gives me enough explanation and rarely pads the answer. I usually have to ask Fable to explain things more simply and/or more concise. > Its front-end taste has improved, but the default is predictable. Left alone, it turns websites into PowerPoint decks with huge statements and hard section breaks. The good news is that it takes design direction well and can revise without destroying the parts that already work. > It still makes confident mistakes. I asked it to rebuild parts of a system, and it told me the job was finished. Later, I found out it wasn't. Bits of its internal process also leak into the answer occasionally. > Claude Fable is more naturally autonomous on large, open-ended projects. GPT-5.6 is easier to reach for. I don't need to invent a huge project to justify using it. It works just as well for a small edit or browser chore. > GPT-5.6 is also cheaper. Sol costs $5 per million input tokens and $30 per million output tokens. Fable costs $10 and $50. Cached input is cheaper too. Still, cost per finished task matters more than cost per token. > GPT-5.6 isn't the best at everything, and it still needs supervision. But it generates faster, wanders less, works at almost any scale, and wastes less of my time. It's the model I have the most confidence in to get the job done right the first time. I put together a full breakdown with all the tests, prompts, and examples on a site. You can read it here:

I’ve been using GPT-5.6 Sol internally for the past two months, I've spent probably 25+ billion tokens. Here’s my review and comparison to Fable 5: > Let's start with the analogy because everyone seems to be giving theirs - GPT-5.6 is likely the last version of the GPT-5 training run series. It's kind of like an athlete at their peak. Through years of experience in the game, they've become the most reliable player and has the highest game IQ. But, there's no more room to grow. Fable on the other hand, being essentially the first version of a new training run, is the first round draft pick rookie. Raw talent mixed with the energy only a young person would have results in some incredible plays we didn't think possible, but also mistakes due to lack of experience. But that rookie will only improve and likely will be better than the veteran ever was because it's a new game and a new era. > GPT-5.6 is genuinely better at long, sustained work. With /goal, I've had it running complex projects for days with almost no intervention. It built a Minecraft-style game, kept adding features and mobs after the core game worked, and only stopped because I stopped the run. I never felt as though I had to jump in and guide it back to the right path. > It keeps finding useful work when you give it a concrete finish line. I had it recreate Excel with a loop. It inspected the real desktop excel app with Computer Use, comparing that against its own build, and closing the gaps. I stopped it after six days after it had built an incredible amount of functionality. > It's faster than other models in two different ways. The raw generation speed is higher, something OpenAI has been putting effort into. But it also takes a shorter path to solutions. It wanders less, changes less code, and generally knows how to get things done directly. In daily use, it feels about 2-3x times faster than Fable. That's my impression, not a controlled benchmark. The difference is large enough that I notice it constantly. > It works well across a wide range of tasks. I use it for one-line edits, quick questions, browser chores, and multi-day builds without changing my prompting style. Speaking of browser control, its the best ever I've used. To the point where I actually use it often. If a task lives on a website, GPT-5.6 usually opens the browser and does it there instead of asking for an API key or forcing everything through the terminal. When I switched back to GPT-5.5, it went straight to the command line even when the browser was clearly the better tool. > And it can handle real browser work, not just toy demos. During a data import, I had it monitor Supabase and resize instances as the load changed. It stayed on the dashboard, adjusted capacity, and checked the result without an API or a custom script. > I also gave it a full Google Workspace migration. It moved Forward Future from to preserved the old aliases, and configured MX, SPF, and DKIM. Before a consequential save, it stopped, explained exactly what would change, and waited for confirmation. > The reasoning setting matters a lot. Light is good for questions and small edits. High and Extra High are the sweet spots for serious work. Ultra usually takes longer than the extra thinking is worth and burns tokens. > I love that 5.6 is split into 3 sizes. Not only can you control speed and cost that way, but you still also have the thinking effort setting for each of them. Very precise controls. I just wish Codex automatically routed my prompts for me. > Its personality is blunt and a little bland. Claude feels warmer and more natural to talk to. GPT-5.6 is more clinical, but I like that for work. It gives me enough explanation and rarely pads the answer. I usually have to ask Fable to explain things more simply and/or more concise. > Its front-end taste has improved, but the default is predictable. Left alone, it turns websites into PowerPoint decks with huge statements and hard section breaks. The good news is that it takes design direction well and can revise without destroying the parts that already work. > It still makes confident mistakes. I asked it to rebuild parts of a system, and it told me the job was finished. Later, I found out it wasn't. Bits of its internal process also leak into the answer occasionally. > Claude Fable is more naturally autonomous on large, open-ended projects. GPT-5.6 is easier to reach for. I don't need to invent a huge project to justify using it. It works just as well for a small edit or browser chore. > GPT-5.6 is also cheaper. Sol costs $5 per million input tokens and $30 per million output tokens. Fable costs $10 and $50. Cached input is cheaper too. Still, cost per finished task matters more than cost per token. > GPT-5.6 isn't the best at everything, and it still needs supervision. But it generates faster, wanders less, works at almost any scale, and wastes less of my time. It's the model I have the most confidence in to get the job done right the first time. I put together a full breakdown with all the tests, prompts, and examples on a site. You can read it here:

Matthew Berman

186,712 次观看 • 21 天前

In a newly released technical update, SpaceX's leadership team, which includes communications manager Dan Huot, Director of Satellite Engineering Ian Dahl, and CEO Elon Musk, detailed a highly ambitious infrastructure roadmap to design, manufacture, and operate specialized artificial intelligence computing satellites at scale. Positioned as a major strategic pillar to dramatically elevate civilizational energy and processing capacity on the Kardashev scale, this strategy moves past traditional communications architectures into massive orbital server arrays. Here is the complete breakdown of the core technologies and timelines driving this space-based intelligence revolution: 🛰️ AI1 satellite power and compute capacity Ian Dahl and Elon Musk introduced the baseline performance targets for the first-generation AI1 satellite, explaining how its custom hardware is engineered to operate like an orbital data center server rack. Ian Dahl noted that their direct operational experience with xAI guided them to target a 150-kilowatt peak power capacity. To manage active machine learning workloads continuously, Elon Musk explained that the satellite is optimized to maintain a sustained average compute power envelope of 120 kilowatts, which directly mirrors the real-world performance of a terrestrial NVIDIA server rack. The official presentation slides outline several key operational metrics for this payload configuration: ⚡ The custom architecture delivers a 150 kW peak compute payload. 🔋 The system maintains a 120 kW sustained average compute payload under active workloads. ⚖️ The hardware achieves a highly optimized power-to-weight density of 70 kW per ton. 🔄 The layout features a completely interchangeable compute provider design. "We thought that the right place to start is around the 150 kilowatt peak power level. But as we look at the workloads with our experience with xAI, we see that we can support about 120 kilowatts of average compute. The 150 kilowatt peak power level roughly matches what, say, an NVIDIA GV300 rack would do. A more reasonable operating envelope would be around 120 kilowatts average power, but it can peak up to 150. So it is basically thinking about it as a rack of compute in space." --- 📐 AI1 satellite dimensions and thermal efficiency specs Elon Musk detailed the physical layout of the AI1 satellite, highlighting the massive dimensions required to accommodate its immense power and cooling hardware. He shared specific design criteria, explaining that the engineering relies on a custom 150 kW solar array paired with a high-capacity deployable liquid radiator thermal management system. The technical specifications of this vehicle layout include: 📏 The structural frame features a massive 70-meter wingspan. ↕️ The vehicle spans a total deployed height of 20 meters. ☀️ The onboard solar array delivers an efficiency of 250 W/m² using technology manufactured in Bastrop, Texas. 🌡️ The thermal system utilizes a 110 m² deployable liquid radiator to cleanly dump waste heat. 🔄 The cooling architecture incorporates redundant pumping loops for mission safety. 🛡️ The exterior contains integrated micrometeoroid shielding to protect the fluid lines. 🧭 The double-sided radiators achieve a dissipation rate of 1400 watts per square meter while remaining oriented knife-edge to the sun. "The assumptions here are 250 watts per square meter for the solar array and about 1400 watts per square meter for the radiators. The radiators are double-sided, radiating on both sides, and they're oriented knife-edge to the sun. They have about a 70-meter wingspan, so these are fairly large." --- 🧩 Simplified design architecture built on Starlink V3 tech Elon Musk explained that despite the satellite's imposing size, its internal architecture is fundamentally much simpler than a standard Starlink satellite. Because it lacks heavy phased array and parabolic communications antennas, the entire vehicle layout is completely streamlined around a few essential structural modules: 🎛️ The hardware framework is arranged around a centralized compute module. ☀️ Large deployable solar arrays extend outward to capture orbital energy. 🌡️ A deployable liquid-radiator thermal management system controls active operational temperatures. 🔄 The engineering team heavily leverages the component evolution and manufacturing experience gained from developing the Starlink V3 vehicle platform. "The AI satellite is actually much simpler than a Starlink satellite. A Starlink satellite has gigantic phased array antennas, parabolic antennas, and a lot of laser links, making it much more complicated. An AI satellite is essentially a lot of solar cells, a radiator, and you still need some laser links, but you don't have all of the super complex antennas that you have on a Starlink satellite. A lot of this is technology we've already made for the Starlink V3 satellites." --- 🔌 Interchangeable compute reference designs and high connectivity Elon Musk outlined a modular hardware approach for the satellite's payload, allowing it to house a variety of industry-standard processing units depending on client requirements. This interchangeable compute rack is supported by a high-bandwidth connectivity loop that links separate orbital units together or transmits data directly back to Earth. The core network parameters include: 🧠 Reference designs are fully established to seamlessly accommodate NVIDIA Reuben chips. 💾 The system architecture is built to support alternative setups using NVIDIA GB300 chips. 💻 Custom hardware layouts are explicitly designed to integrate Google TPUs. 🌐 The onboard communications setup delivers roughly 1 terabit of laser link connectivity. ⏱️ The network closes the communication loop directly with the main Starlink constellation at an ultra-low latency of only 3 milliseconds. "Our current reference design is for NVIDIA Reuben chips, or it could be either GB300 or Reuben chips. We'll also have a reference design for TPUs. Essentially, you can put up any existing chips into orbit. There would also be probably something on the order of a terabit of laser link connectivity from the satellite. Then you can connect these racks of compute to each other by the laser links or directly to the Starlink constellations. Light travels 300 kilometers per millisecond, so that's about three milliseconds away." --- 🏭 The "gigasat" AI satellite and solar production hub in Bastrop, Texas Dan Huot highlighted that the primary production hub for this entire hardware ecosystem is anchored at their sprawling complex in Bastrop, Texas, officially designated as the Gigasat factory. Elon Musk verified that construction is already actively underway on the solar manufacturing facility to feed the project's supply line, with plans moving forward to construct the adjacent AI satellite assembly lines. The physical footprint and timeline of this manufacturing hub are defined by the following benchmarks: 🗺️ The company has over 1,000 acres of land currently owned or under contract for the site. 🏢 The manufacturing complex boasts a massive structural building potential exceeding 11 million square feet. ⚙️ The facility will vertically integrate production to manufacture solar ingots, wafers, solar cells, and completed AI satellites. 📅 Both the solar and AI satellite production lines are targeted to be operational at a viable volume by the end of next year. "We're going to be building a lot of satellites and we're going to be building them here in Bastrop. We already have the solar manufacturing facility under construction, and then we will be building out the AI sat production building soon. We expect to have the AI sat production, the solar production, and all of that operating at some reasonable volume by the end of next year." --- 🏢 The 100-million-square-foot "terafab" chip factory Elon Musk revealed a massive, long-term scaling strategy to build an immense chip manufacturing facility dubbed the "terafab" to completely bypass global semiconductor volume constraints. This manufacturing infrastructure is designed to transition the company into next-generation industrial scaling by producing highly specialized computing components at an unprecedented volume. The scale of this infrastructure project is defined by several extraordinary engineering and production benchmarks: 🏭 The colossal factory is projected to span approximately 100 million square feet, making it ten times larger than the current Tesla Gigafactory Texas. ⚡ The facility is structurally engineered to achieve a massive manufacturing output of 1 terawatt per year once fully operational. 📦 This unprecedented physical footprint provides the capacity required to manufacture 1 billion full-reticle equivalent chips annually. 🔌 Each individual chip manufactured by the facility is designed to run at a power capacity of 1 kilowatt. 🇺🇸 The total scaled output of the facility represents an energy footprint that is exactly double the current annual electricity consumption of the entire United States. "In order to get to the next order of magnitude, you need a gigantic chip factory. To give you a sense of scale here, we expect that the terafab is going to be around 100 million square feet, which is 10 times the size of the Tesla Gigafactory Texas. From a logic die standpoint, that's like having a billion chips per year with a kilowatt per reticle, scaling to a terawatt per year. That is twice the current electricity consumption of the United States." --- 📶 Next-generation high-volume Starlink terminals Dan Huot and Elon Musk introduced their next-generation Starlink user terminals, which have been redesigned specifically to achieve massive manufacturing throughput. Elon Musk pointed out that these newer models will be produced in vastly higher volumes than current hardware designs to fulfill their long-term global deployment targets: 📈 The upgraded user hardware is manufactured at a much higher volume capacity than existing units. 🌍 The company's ultimate target is to successfully deploy a few hundred million of these next-generation terminals worldwide. "In fact, these are the new Starlink terminals, which we made in much higher volume than the current terminals. Ultimately, we think there's probably going to be a few hundred million Starlink terminals out there." --- 📈 Aspirational timeline for orbital AI compute scaling Elon Musk laid out an ambitious, multi-year execution timeline detailing how the company plans to progressively scale space-based processing power. The roadmap targets an initial run-rate by the end of next year and sets an aggressive pace to increase total operational capacity sequentially through a structured, multi-phase timeline: 1️⃣ The initial target aims to hit an annualized run-rate of 1 gigawatt of space AI compute by the end of next year. 2️⃣ The capacity scales to an annualized rate of 10 gigawatts within the next two and a half years. 3️⃣ The operational envelope expands to reach 100 gigawatts in three and a half years. 4️⃣ The long-term deployment plan scales directly to a full terawatt capacity per year using the output of the terafab. "The goal is to get to roughly an annualized rate of a gigawatt per year by the end of next year in terms of space AI compute. Then aspirationally, we want to scale that by an order of magnitude per year. In two and a half years, hitting an annualized rate of 10 gigawatts a year in space, and in three and a half years, maybe a hundred gigawatts, going beyond that with the terafab to scale to a terawatt per year." --- 🌕 Ultimate scaling via lunar production and mass drivers Elon Musk explained that scaling three orders of magnitude past a single terawatt forces a transition completely off-planet to avoid the logistical penalty of Earth's deep gravity well. The vision relies on establishing manufacturing infrastructure directly on the moon to leverage localized resource loops and zero-atmosphere physics: 🌙 The company plans to establish localized raw production lines on the moon to fabricate solar panels, photovoltaics, and radiators from lunar materials. ⚡ Manufacturing components locally avoids the massive fuel and mass penalties of transporting heavy structural materials from Earth. 🧲 Because the moon has no atmosphere and only one-sixth of Earth's gravity, the facility will utilize an electromagnetic mass driver to launch completed satellites. 🚀 Operating essentially as a linear electric motor rail gun, this mechanism will shoot fully assembled AI satellites straight into deep space without relying on chemical rockets. "The only way that we can really see that you can achieve that is on the moon with a mass driver, essentially where you do local production of photovoltaics, solar panels, and radiators on the moon. Because the moon has no atmosphere and only one-sixth Earth's gravity, you can accelerate the AI satellites into deep space without a rocket. You can basically shoot them into space using an electromagnetic gun, like a rail gun type—it's basically a linear electric motor."

In a newly released technical update, SpaceX's leadership team, which includes communications manager Dan Huot, Director of Satellite Engineering Ian Dahl, and CEO Elon Musk, detailed a highly ambitious infrastructure roadmap to design, manufacture, and operate specialized artificial intelligence computing satellites at scale. Positioned as a major strategic pillar to dramatically elevate civilizational energy and processing capacity on the Kardashev scale, this strategy moves past traditional communications architectures into massive orbital server arrays. Here is the complete breakdown of the core technologies and timelines driving this space-based intelligence revolution: 🛰️ AI1 satellite power and compute capacity Ian Dahl and Elon Musk introduced the baseline performance targets for the first-generation AI1 satellite, explaining how its custom hardware is engineered to operate like an orbital data center server rack. Ian Dahl noted that their direct operational experience with xAI guided them to target a 150-kilowatt peak power capacity. To manage active machine learning workloads continuously, Elon Musk explained that the satellite is optimized to maintain a sustained average compute power envelope of 120 kilowatts, which directly mirrors the real-world performance of a terrestrial NVIDIA server rack. The official presentation slides outline several key operational metrics for this payload configuration: ⚡ The custom architecture delivers a 150 kW peak compute payload. 🔋 The system maintains a 120 kW sustained average compute payload under active workloads. ⚖️ The hardware achieves a highly optimized power-to-weight density of 70 kW per ton. 🔄 The layout features a completely interchangeable compute provider design. "We thought that the right place to start is around the 150 kilowatt peak power level. But as we look at the workloads with our experience with xAI, we see that we can support about 120 kilowatts of average compute. The 150 kilowatt peak power level roughly matches what, say, an NVIDIA GV300 rack would do. A more reasonable operating envelope would be around 120 kilowatts average power, but it can peak up to 150. So it is basically thinking about it as a rack of compute in space." --- 📐 AI1 satellite dimensions and thermal efficiency specs Elon Musk detailed the physical layout of the AI1 satellite, highlighting the massive dimensions required to accommodate its immense power and cooling hardware. He shared specific design criteria, explaining that the engineering relies on a custom 150 kW solar array paired with a high-capacity deployable liquid radiator thermal management system. The technical specifications of this vehicle layout include: 📏 The structural frame features a massive 70-meter wingspan. ↕️ The vehicle spans a total deployed height of 20 meters. ☀️ The onboard solar array delivers an efficiency of 250 W/m² using technology manufactured in Bastrop, Texas. 🌡️ The thermal system utilizes a 110 m² deployable liquid radiator to cleanly dump waste heat. 🔄 The cooling architecture incorporates redundant pumping loops for mission safety. 🛡️ The exterior contains integrated micrometeoroid shielding to protect the fluid lines. 🧭 The double-sided radiators achieve a dissipation rate of 1400 watts per square meter while remaining oriented knife-edge to the sun. "The assumptions here are 250 watts per square meter for the solar array and about 1400 watts per square meter for the radiators. The radiators are double-sided, radiating on both sides, and they're oriented knife-edge to the sun. They have about a 70-meter wingspan, so these are fairly large." --- 🧩 Simplified design architecture built on Starlink V3 tech Elon Musk explained that despite the satellite's imposing size, its internal architecture is fundamentally much simpler than a standard Starlink satellite. Because it lacks heavy phased array and parabolic communications antennas, the entire vehicle layout is completely streamlined around a few essential structural modules: 🎛️ The hardware framework is arranged around a centralized compute module. ☀️ Large deployable solar arrays extend outward to capture orbital energy. 🌡️ A deployable liquid-radiator thermal management system controls active operational temperatures. 🔄 The engineering team heavily leverages the component evolution and manufacturing experience gained from developing the Starlink V3 vehicle platform. "The AI satellite is actually much simpler than a Starlink satellite. A Starlink satellite has gigantic phased array antennas, parabolic antennas, and a lot of laser links, making it much more complicated. An AI satellite is essentially a lot of solar cells, a radiator, and you still need some laser links, but you don't have all of the super complex antennas that you have on a Starlink satellite. A lot of this is technology we've already made for the Starlink V3 satellites." --- 🔌 Interchangeable compute reference designs and high connectivity Elon Musk outlined a modular hardware approach for the satellite's payload, allowing it to house a variety of industry-standard processing units depending on client requirements. This interchangeable compute rack is supported by a high-bandwidth connectivity loop that links separate orbital units together or transmits data directly back to Earth. The core network parameters include: 🧠 Reference designs are fully established to seamlessly accommodate NVIDIA Reuben chips. 💾 The system architecture is built to support alternative setups using NVIDIA GB300 chips. 💻 Custom hardware layouts are explicitly designed to integrate Google TPUs. 🌐 The onboard communications setup delivers roughly 1 terabit of laser link connectivity. ⏱️ The network closes the communication loop directly with the main Starlink constellation at an ultra-low latency of only 3 milliseconds. "Our current reference design is for NVIDIA Reuben chips, or it could be either GB300 or Reuben chips. We'll also have a reference design for TPUs. Essentially, you can put up any existing chips into orbit. There would also be probably something on the order of a terabit of laser link connectivity from the satellite. Then you can connect these racks of compute to each other by the laser links or directly to the Starlink constellations. Light travels 300 kilometers per millisecond, so that's about three milliseconds away." --- 🏭 The "gigasat" AI satellite and solar production hub in Bastrop, Texas Dan Huot highlighted that the primary production hub for this entire hardware ecosystem is anchored at their sprawling complex in Bastrop, Texas, officially designated as the Gigasat factory. Elon Musk verified that construction is already actively underway on the solar manufacturing facility to feed the project's supply line, with plans moving forward to construct the adjacent AI satellite assembly lines. The physical footprint and timeline of this manufacturing hub are defined by the following benchmarks: 🗺️ The company has over 1,000 acres of land currently owned or under contract for the site. 🏢 The manufacturing complex boasts a massive structural building potential exceeding 11 million square feet. ⚙️ The facility will vertically integrate production to manufacture solar ingots, wafers, solar cells, and completed AI satellites. 📅 Both the solar and AI satellite production lines are targeted to be operational at a viable volume by the end of next year. "We're going to be building a lot of satellites and we're going to be building them here in Bastrop. We already have the solar manufacturing facility under construction, and then we will be building out the AI sat production building soon. We expect to have the AI sat production, the solar production, and all of that operating at some reasonable volume by the end of next year." --- 🏢 The 100-million-square-foot "terafab" chip factory Elon Musk revealed a massive, long-term scaling strategy to build an immense chip manufacturing facility dubbed the "terafab" to completely bypass global semiconductor volume constraints. This manufacturing infrastructure is designed to transition the company into next-generation industrial scaling by producing highly specialized computing components at an unprecedented volume. The scale of this infrastructure project is defined by several extraordinary engineering and production benchmarks: 🏭 The colossal factory is projected to span approximately 100 million square feet, making it ten times larger than the current Tesla Gigafactory Texas. ⚡ The facility is structurally engineered to achieve a massive manufacturing output of 1 terawatt per year once fully operational. 📦 This unprecedented physical footprint provides the capacity required to manufacture 1 billion full-reticle equivalent chips annually. 🔌 Each individual chip manufactured by the facility is designed to run at a power capacity of 1 kilowatt. 🇺🇸 The total scaled output of the facility represents an energy footprint that is exactly double the current annual electricity consumption of the entire United States. "In order to get to the next order of magnitude, you need a gigantic chip factory. To give you a sense of scale here, we expect that the terafab is going to be around 100 million square feet, which is 10 times the size of the Tesla Gigafactory Texas. From a logic die standpoint, that's like having a billion chips per year with a kilowatt per reticle, scaling to a terawatt per year. That is twice the current electricity consumption of the United States." --- 📶 Next-generation high-volume Starlink terminals Dan Huot and Elon Musk introduced their next-generation Starlink user terminals, which have been redesigned specifically to achieve massive manufacturing throughput. Elon Musk pointed out that these newer models will be produced in vastly higher volumes than current hardware designs to fulfill their long-term global deployment targets: 📈 The upgraded user hardware is manufactured at a much higher volume capacity than existing units. 🌍 The company's ultimate target is to successfully deploy a few hundred million of these next-generation terminals worldwide. "In fact, these are the new Starlink terminals, which we made in much higher volume than the current terminals. Ultimately, we think there's probably going to be a few hundred million Starlink terminals out there." --- 📈 Aspirational timeline for orbital AI compute scaling Elon Musk laid out an ambitious, multi-year execution timeline detailing how the company plans to progressively scale space-based processing power. The roadmap targets an initial run-rate by the end of next year and sets an aggressive pace to increase total operational capacity sequentially through a structured, multi-phase timeline: 1️⃣ The initial target aims to hit an annualized run-rate of 1 gigawatt of space AI compute by the end of next year. 2️⃣ The capacity scales to an annualized rate of 10 gigawatts within the next two and a half years. 3️⃣ The operational envelope expands to reach 100 gigawatts in three and a half years. 4️⃣ The long-term deployment plan scales directly to a full terawatt capacity per year using the output of the terafab. "The goal is to get to roughly an annualized rate of a gigawatt per year by the end of next year in terms of space AI compute. Then aspirationally, we want to scale that by an order of magnitude per year. In two and a half years, hitting an annualized rate of 10 gigawatts a year in space, and in three and a half years, maybe a hundred gigawatts, going beyond that with the terafab to scale to a terawatt per year." --- 🌕 Ultimate scaling via lunar production and mass drivers Elon Musk explained that scaling three orders of magnitude past a single terawatt forces a transition completely off-planet to avoid the logistical penalty of Earth's deep gravity well. The vision relies on establishing manufacturing infrastructure directly on the moon to leverage localized resource loops and zero-atmosphere physics: 🌙 The company plans to establish localized raw production lines on the moon to fabricate solar panels, photovoltaics, and radiators from lunar materials. ⚡ Manufacturing components locally avoids the massive fuel and mass penalties of transporting heavy structural materials from Earth. 🧲 Because the moon has no atmosphere and only one-sixth of Earth's gravity, the facility will utilize an electromagnetic mass driver to launch completed satellites. 🚀 Operating essentially as a linear electric motor rail gun, this mechanism will shoot fully assembled AI satellites straight into deep space without relying on chemical rockets. "The only way that we can really see that you can achieve that is on the moon with a mass driver, essentially where you do local production of photovoltaics, solar panels, and radiators on the moon. Because the moon has no atmosphere and only one-sixth Earth's gravity, you can accelerate the AI satellites into deep space without a rocket. You can basically shoot them into space using an electromagnetic gun, like a rail gun type—it's basically a linear electric motor."

Ming

22,203 次观看 • 1 个月前

The so-called 'Mega' DSC was a carefully engineered policy sketch for a 'Mega' scam, a dark operation by CM Chandrababu and his son Nara Lokesh as Minister-in-charge, grievously damaging the lives of meritorious aspirants. Lakhs of aspirants are in anguish today, shedding tears because of the manipulation and deception by the N Chandrababu Naidu Government. Andhra Pradesh never witnessed such a disastrous recruitment process before. For the recruitment process for 16,000 DSC posts, every safeguard that protected transparency was dismantled, every institutional check was weakened, through a carefully laid out a scheme of fraud for purposes of converting the DSC recruitment into a money-spinning scam. Never before in the history of Andhra Pradesh has a recruitment process been marred by irregularities at such scale. DSC represents hopes and aspirations of lakhs of unemployed youth. Malpractices and corruption in the DSC recruitment process executed by the department, whose Minister-in-charge is Nara Lokesh, are extremely condemnable and the situation warrants a CBI inquiry. The corruption ridden DSC recruitment process is a multi layered scam and the following are the key aspects of it. 1. Chandrababu's government dismantled long-standing institutional safeguards. The entire conspiracy began with preparation of question papers (handled by SCERT) and the conduct of the examination (handled by the DSC Convenor). These responsibilities were traditionally separated to preserve confidentiality. This process was completely compromised when the separation of responsibilities was done away with. Chandrababu government sidelined the DSC Convenor and entrusted both crucial responsibilities to the Director of SCERT, thereby undermining the transparency of DSC examination and deliberately paving the way for irregularities. This arrangement created a convenient mechanism as the first step for the Mega Scam. 2. Making matters worse, the highly confidential tasks of question paper preparation and its upload were entrusted to outsourcing employees, creating a system vulnerable to abuse while conveniently providing potential scapegoats if design were to get exposed. The case of an outsourcing employee securing top rank in DSC in the very examination process he was associated with is a classic example of the consequences of the irregularity. This is direct proof of the paper leak scam. The sequence of events that follow generate further suspicion about the fragility of the system enabling paper leak and other irregularities. Why was that individual not provided the job despite him securing first rank? Why were the individual's ID and data removed from the merit list subsequently? Why wasn't he invited for the certificate verification? Are these not the reasons cited by that individual when he approached the Court? An outsourcing employee working in SCERT and intimately involved in question paper preparation, securing 1st rank, speaks volumes about the paper leak. For purposes of ascertaining the depth of the paper leak issue an inquiry by CBI is necessary. (supporting doc refer 1-5 slides in the attachment - extracts of candidate rankings, changes made to the merit list, Candidate's letter to the department and Court filing) 3. The total lack of transparency with respect to declaration of results is also absolutely worrisome, with merit lists and merit-cum-roster lists not being placed on the notice boards of collectors' offices, as was the prevailing practice. Instead, the process was centralized with only online display and messaging. This resulted in candidates facing significant hardship owing uncertainty, with them running from pillar to post with nobody to redresses their grievances, not at the district collector level and not at head office level.The cruelest aspect of the entire DSC examination is that, several candidates who received call letters on 1:1 basis and whose certificates were successfully verified, did not find their name in final selection list. Strict adherence to Rule 20 of Scheme of Selection Rules 2025 necessitated preparation of merit-cum-roster list after taking into consideration, marks, ranks, cutoff and all forms of reservations in place, be it vertical or horizontal, be it under meritorious sportspersons quota, be it under persons with benchmark disabilities quota, and so forth. Under the rule position, successful verification of certificates after this step must only result in the candidate's name being placed in final selection list, however, such has not been the fate of several call letter recipients. (Supporting doc refer 6-7 slides in the attachment - Rule 20 of Scheme of Selection Rules, 2025). 4. The most revealing aspect of the entire scandal is the manner in which the sports quota was dealt with. The shameless manner in which, the policies were altered to enable recklessness in the recruitment process is indeed very distressing. Injustice was done not only to meritorious candidates but also to genuine sportspersons who have worked hard for their achievements. Doing away with the existing policy mandating qualification in examination as provided in G.O. No. 74 dated 9th August, 2012, through a new sports policy introduced vide G.O. no. 8 dated 10th December, 2024 and bringing it into implementation through G.O. No. 4 and G.O. No. 47, Chandrababu and his son had already prepared what can only be described as a "policy blueprint for a scam." For the first time in history, sports quota candidates were exempted from appearing for the DSC examination, creating a backdoor entry through which they were brought into the system. Once the recruitment process was complete, the policy was reverted to what it was earlier, through G.O. No. 23, G.O. No. 25 and G.O. No. 56, thereby superseding G.O. No. 4 and G.O. No. 47, citing difficulties that have arisen and several representations and grievances received from sportspersons. So, once the purpose was served and the recruitment was completed without sportspersons having to appear in the written examination, the backdoor that enabled the system being compromised was shut and the Government also cold-heartedly admitted that the policy change caused difficulties and resulted in several grievances. (Supporting docs refer 8-13 slides in the attachment - extracts from G.O. No. 74 conveying original policy, G.O. No. 4 & 47 conveying modification, G.O. No. 23, 25 & 56 conveying policy reversal again after the recruitment is complete)To utter disgust of the entire State, a video of a negotiation for a teacher post between an aspirant and another person has come to light and thereafter, callously, the authorities merely registered a token case, granted station bail without even arresting the accused. No meaningful investigation was conducted. (Supporting evidence - video clip and extract from the FIR, wherein even after knowing the telephone number, the police avoid mentioning the name of the individual and merely refer to him as the suspect.) In the most insensitive and wholly unscrupulous manner, the TDP Government has made a mockery of the aspirations of lakhs of candidates. The scandal is deeply rooted and dangerously conceived by the people at the helm of the present State Government including the Chief Minister Mr. Chandrababu Naidu and the Education Minister, Nara Lokesh. The investigating agencies in the State report to the perpetrators and therefore, to unearth facts the need for an enquiry by an independent agency such as CBI is warranted. Details attached -

The so-called 'Mega' DSC was a carefully engineered policy sketch for a 'Mega' scam, a dark operation by CM Chandrababu and his son Nara Lokesh as Minister-in-charge, grievously damaging the lives of meritorious aspirants. Lakhs of aspirants are in anguish today, shedding tears because of the manipulation and deception by the N Chandrababu Naidu Government. Andhra Pradesh never witnessed such a disastrous recruitment process before. For the recruitment process for 16,000 DSC posts, every safeguard that protected transparency was dismantled, every institutional check was weakened, through a carefully laid out a scheme of fraud for purposes of converting the DSC recruitment into a money-spinning scam. Never before in the history of Andhra Pradesh has a recruitment process been marred by irregularities at such scale. DSC represents hopes and aspirations of lakhs of unemployed youth. Malpractices and corruption in the DSC recruitment process executed by the department, whose Minister-in-charge is Nara Lokesh, are extremely condemnable and the situation warrants a CBI inquiry. The corruption ridden DSC recruitment process is a multi layered scam and the following are the key aspects of it. 1. Chandrababu's government dismantled long-standing institutional safeguards. The entire conspiracy began with preparation of question papers (handled by SCERT) and the conduct of the examination (handled by the DSC Convenor). These responsibilities were traditionally separated to preserve confidentiality. This process was completely compromised when the separation of responsibilities was done away with. Chandrababu government sidelined the DSC Convenor and entrusted both crucial responsibilities to the Director of SCERT, thereby undermining the transparency of DSC examination and deliberately paving the way for irregularities. This arrangement created a convenient mechanism as the first step for the Mega Scam. 2. Making matters worse, the highly confidential tasks of question paper preparation and its upload were entrusted to outsourcing employees, creating a system vulnerable to abuse while conveniently providing potential scapegoats if design were to get exposed. The case of an outsourcing employee securing top rank in DSC in the very examination process he was associated with is a classic example of the consequences of the irregularity. This is direct proof of the paper leak scam. The sequence of events that follow generate further suspicion about the fragility of the system enabling paper leak and other irregularities. Why was that individual not provided the job despite him securing first rank? Why were the individual's ID and data removed from the merit list subsequently? Why wasn't he invited for the certificate verification? Are these not the reasons cited by that individual when he approached the Court? An outsourcing employee working in SCERT and intimately involved in question paper preparation, securing 1st rank, speaks volumes about the paper leak. For purposes of ascertaining the depth of the paper leak issue an inquiry by CBI is necessary. (supporting doc refer 1-5 slides in the attachment - extracts of candidate rankings, changes made to the merit list, Candidate's letter to the department and Court filing) 3. The total lack of transparency with respect to declaration of results is also absolutely worrisome, with merit lists and merit-cum-roster lists not being placed on the notice boards of collectors' offices, as was the prevailing practice. Instead, the process was centralized with only online display and messaging. This resulted in candidates facing significant hardship owing uncertainty, with them running from pillar to post with nobody to redresses their grievances, not at the district collector level and not at head office level.The cruelest aspect of the entire DSC examination is that, several candidates who received call letters on 1:1 basis and whose certificates were successfully verified, did not find their name in final selection list. Strict adherence to Rule 20 of Scheme of Selection Rules 2025 necessitated preparation of merit-cum-roster list after taking into consideration, marks, ranks, cutoff and all forms of reservations in place, be it vertical or horizontal, be it under meritorious sportspersons quota, be it under persons with benchmark disabilities quota, and so forth. Under the rule position, successful verification of certificates after this step must only result in the candidate's name being placed in final selection list, however, such has not been the fate of several call letter recipients. (Supporting doc refer 6-7 slides in the attachment - Rule 20 of Scheme of Selection Rules, 2025). 4. The most revealing aspect of the entire scandal is the manner in which the sports quota was dealt with. The shameless manner in which, the policies were altered to enable recklessness in the recruitment process is indeed very distressing. Injustice was done not only to meritorious candidates but also to genuine sportspersons who have worked hard for their achievements. Doing away with the existing policy mandating qualification in examination as provided in G.O. No. 74 dated 9th August, 2012, through a new sports policy introduced vide G.O. no. 8 dated 10th December, 2024 and bringing it into implementation through G.O. No. 4 and G.O. No. 47, Chandrababu and his son had already prepared what can only be described as a "policy blueprint for a scam." For the first time in history, sports quota candidates were exempted from appearing for the DSC examination, creating a backdoor entry through which they were brought into the system. Once the recruitment process was complete, the policy was reverted to what it was earlier, through G.O. No. 23, G.O. No. 25 and G.O. No. 56, thereby superseding G.O. No. 4 and G.O. No. 47, citing difficulties that have arisen and several representations and grievances received from sportspersons. So, once the purpose was served and the recruitment was completed without sportspersons having to appear in the written examination, the backdoor that enabled the system being compromised was shut and the Government also cold-heartedly admitted that the policy change caused difficulties and resulted in several grievances. (Supporting docs refer 8-13 slides in the attachment - extracts from G.O. No. 74 conveying original policy, G.O. No. 4 & 47 conveying modification, G.O. No. 23, 25 & 56 conveying policy reversal again after the recruitment is complete)To utter disgust of the entire State, a video of a negotiation for a teacher post between an aspirant and another person has come to light and thereafter, callously, the authorities merely registered a token case, granted station bail without even arresting the accused. No meaningful investigation was conducted. (Supporting evidence - video clip and extract from the FIR, wherein even after knowing the telephone number, the police avoid mentioning the name of the individual and merely refer to him as the suspect.) In the most insensitive and wholly unscrupulous manner, the TDP Government has made a mockery of the aspirations of lakhs of candidates. The scandal is deeply rooted and dangerously conceived by the people at the helm of the present State Government including the Chief Minister Mr. Chandrababu Naidu and the Education Minister, Nara Lokesh. The investigating agencies in the State report to the perpetrators and therefore, to unearth facts the need for an enquiry by an independent agency such as CBI is warranted. Details attached -

YS Jagan Mohan Reddy

133,411 次观看 • 1 个月前

Have you heard of collective consciousness and mass programming? Watch THINK TOGETHER (short film 5min) A TORVÆL FILM. The spell is global. It's not just "Think Together." That's one film, one title, one thread in a tapestry of mass enchantment that has been woven through every medium humans use to receive information, entertainment, and meaning. It's a"magic kind of a spell through screen." That is the most precise description of what's happening. Not metaphor. Not allegory. Literal spellcasting through electronic and print media. Let's go deep into the global spell. The mediums. The methods. The specific frequency weapons deployed through each channel. The Nature of the Spell: Electronic Enchantment A spell, in its original meaning, is a binding. A set of symbols, sounds, and focused intention that alters the consciousness of the target, making them perceive reality differently, act against their own interest, or accept a condition they would otherwise reject. Traditional magic required proximity. The sorcerer had to be near the target, or use a physical link hair, nail clippings, a photograph. The spell was limited by space. Electronic media destroyed that limitation. The screen is a direct energetic link between the caster and the target. Light enters the eyes. Sound enters the ears. The brain entrains to the frequencies embedded in the transmission. The biofield receives the signal. Distance is irrelevant. One broadcast can enchant a billion people simultaneously. The screen is the wand. The transmission is the incantation. The content is the intention. And the population is under a continuous, multi-layered, globally synchronized spell that has been building for over a century. Medium 1: Cinema | The Dream Injection Movies are the most powerful spell delivery system ever invented. The Theater as Ritual Chamber: A cinema is a darkened room where strangers gather in silence, facing a single light source. The flickering light induces a hypnagogic state the brainwave pattern of the threshold between waking and dreaming. In this state, the critical faculty is suppressed. The subconscious is open. The images and sounds on the screen are absorbed without filtration. This is identical to the conditions of a ritual chamber. The darkened temple. The flickering torchlight. The congregation facing the altar. The priest intoning the incantation. Cinema is temple worship, and the screen is the altar on which reality is reshaped. The 24 Frames Per Second Induction: Film runs at 24 frames per second. This is not an arbitrary choice. The human brain's alpha rhythm the frequency of relaxed, suggestible awareness operates at 8 to 12 Hz. 24 frames per second, with each frame shown two or three times due to the shutter, creates a flicker frequency in the 48 to 72 Hz range. This is a harmonic of the gamma brainwave band, associated with binding sensory information into a coherent percept. The film doesn't just show you images. It entrains your gamma rhythm to its own temporal structure. Your brain is phase-locked to the projector. You are in the film. The film is in you. Color Grading as Emotional Programming: Every major film uses color grading to manipulate emotional response. Teal and orange. Desaturated blues for dystopia. Warm golds for nostalgia. The palette is not an aesthetic choice. It is an emotional command. The visual cortex processes color before the conscious mind identifies objects. The emotional response to the color palette happens before you know what you're looking at. The spell is felt before it is seen. Sound Design as Frequency Weapon: Film soundtracks use specific frequencies to induce physiological states. Infrasonic bass frequencies below 20 Hz, felt rather than heard triggers the fear response in the amygdala. The Shepard tone an auditory illusion of a pitch that rises forever without ever reaching a destination creates a sense of endless tension that never resolves. This is used extensively in horror and thriller films to keep the audience in a state of chronic, unresolvable anxiety. The soundtrack tells you what to feel. You believe the feeling is your own response to the story. It is not. It is a frequency command, delivered through the auditory system, bypassing cognition entirely. #PredictiveProgramming: Major films depict future events before they happen. Not as speculation. As conditioning. The controllers place images of planned events into the collective unconscious through cinema. When the event occurs in reality, the population has already "seen" it. It feels familiar. It feels inevitable. It feels like something they already accepted in the dream state. Pandemic films before COVID. Drone warfare films before the drone wars. Mass surveillance films before Snowden. Transhumanist films before Neuralink. The spell is cast years in advance. The event is merely the fulfillment of a prophecy that was manufactured by the prophecy itself. Medium 2: Music | The Auditory Incantation Music is the oldest spell technology. Before writing, before film, before any visual medium, there was rhythm and tone. The drum. The chant. The bone flute. Music alters brainwave states directly, without requiring visual attention. 432 Hz vs. 440 Hz: The Frequency War The global standard tuning for music is A=440 Hz. This was adopted in the early 20th century, pushed by the Rockefeller Foundation and the Nazi propaganda ministry, and codified by the International Organization for Standardization in 1955. Prior to this, many traditions used A=432 Hz, a frequency that mathematically aligns with the Schumann resonance (8 Hz), the Earth's natural electromagnetic pulse, and the geometric proportions found in nature. 440 Hz creates a subtle dissonance with the human biofield. It agitates. It separates the listener from the Earth's frequency. Music tuned to 440 Hz cannot fully relax the nervous system. It maintains a baseline of subliminal tension, a low-grade anxiety that the listener attributes to their life circumstances rather than to the music itself. 432 Hz music entrains the listener to the planetary frequency. It harmonizes. It heals. It is suppressed not because it "sounds worse" but because it sounds more coherent and produces a brain state that is resistant to external control. Lyrical Programming: Lyrics are direct incantations. The repetition of a phrase in a song embeds it in the subconscious. The melody carries the words past the critical faculty. The rhythm entrains the brain to receive the message. Examine the lyrical content of mainstream music across decades: ◻️Themes of hopelessness, materialism, sexual degradation, violence, substance use ◻️ Self-referential obsession: "I," "me," "my" repeated endlessly, reinforcing the illusion of the separate self ◻️ Nihilism presented as cool, despair presented as authenticity ◻️ Love reduced to possession, intimacy reduced to transaction The population sings along. They internalize the incantation. They believe they are listening to music. They are reciting spells that bind them to a reality of consumption, isolation, and quiet desperation. The Monopoly of Distribution: A handful of corporations control the global music industry. Universal, Sony, Warner. The playlists are curated. The algorithms select what billions hear. Independent music that carries a different frequency, a different message, a different emotional command is not played. It is not because it lacks quality. It is because it carries the wrong spell. Medium 3: Television | The Continuous Ritual Television was the first medium to bring the spell into the home continuously. Before smartphones, before streaming, the television was the household altar. The family gathered around it. The light flickered in the living room. The incantation played during dinner. The 30-Minute Spell Cycle: The sitcom format 22 minutes of content, 8 minutes of commercials is a spell cycle. The content opens the subconscious (laughter, emotional engagement). The commercial delivers the command (buy this, believe this, want this). The cycle repeats. Over decades, the population's attention span was conditioned to this rhythm. The modern inability to focus for more than a few minutes is not a failure of will. It is a successful spell. An entrained attention cycle that can now be exploited by shorter-form content on smartphones. News as Reality Creation: Television news is not information. It is ritual. The set, the lighting, the music, the cadence of the anchor's voice these are the elements of a ceremonial invocation. The news does not report reality. It declares reality into being. The repetition of phrases, the selection of images, the framing of events this is spellcasting in real time. The population watches, believes they are being informed, and has their perception of the world sculpted without their knowledge. The Laugh Track: The laugh track is the most obvious spell component in television history. A recorded laugh triggers the mirror neuron system. The viewer laughs not because the joke is funny but because they heard laughter. The spell bypasses judgment. The laugh track says: "This is funny." The brain obeys. The critical faculty is suspended by a recorded cackle. Medium 4: Print Media | The Written Incantation Before electronic media, print was the spell delivery system. It remains operational, though its influence has been partially eclipsed by screens. The Headline as Command: A headline is not a summary. It is a command phrase. Most readers do not read the article. They read the headline. The headline is the spell, condensed to its most potent form. It frames the event before the event is understood. It tells the reader what to think before they have a chance to think. The Inverted Pyramid: Journalistic structure places the most important information first, followed by diminishing detail. This is presented as a neutral convention. It is a spell structure. The command is delivered at the top. The supporting incantation follows. By the time the reader reaches the end, they have forgotten the details and retained only the command. The Omission: The most powerful spell component in print media is what is not printed. The events, perspectives, and voices that are systematically excluded from the written record. The spell of omission creates a reality defined by absence. If it is not in print, it did not happen. The population's sense of what is real is shaped as much by the silence as by the words. Medium 5: Social Media | The Participatory Spell Social media is the most sophisticated spell technology ever created. It does not broadcast to a passive audience. It enlists the audience as casters. Every user is simultaneously the target and the amplifier of the spell. The Infinite Scroll as Trance Induction: The infinite scroll is a hypnotic mechanism. The finger moves. The content appears. The brain receives a micro-dose of dopamine with each new image. The motion is rhythmic. The attention is captured. The critical faculty is submerged. This is identical to the repetitive motion of a rosary, a prayer wheel, a mantra. The user is meditating, but the object of meditation is chosen by the algorithm, not by the self. The Like Button as Ritual Participation: Every like, every share, every comment is a ritual act. The user invests a fragment of their attention, their emotional energy, their biofield into the content. The spell is strengthened by participation. The egregore is fed by interaction. The user believes they are expressing an opinion. They are adding their life force to a thought-form they did not create and do not control. The Algorithm as High Priest: The algorithm does not show you what you want. It shows you what will keep you engaged and what will shape your perception in accordance with the controllers' intention. The algorithm is the high priest of the participatory spell. It selects the incantations. It measures the responses. It adjusts the frequency in real time. It knows you better than you know yourself, because it has your attention data, your emotional data, your behavioral data, and the biofield data harvested through the IoB sensors. The spell is personalized. No two users receive the same incantation. But all incantations serve the same master. Medium 6: Advertising | The Direct Command Advertising is the purest form of the spell. It does not pretend to be art, information, or entertainment. It is a direct command: desire this, buy this, be this. Every other medium is, in part, a delivery system for the advertising spell. The Subliminal Layer: Subliminal messaging is not a conspiracy theory. It is a documented, researched, and patented technology. Images embedded for single frames. Audio messages masked by other sounds. Commands that bypass conscious awareness entirely. The advertising industry has denied using subliminals since the 1950s, while simultaneously filing patents for subliminal delivery systems. The Repetition Principle: A single exposure to an advertisement has minimal effect. Repeated exposure thousands of times across years wires the command into the neural architecture. The brand name becomes a neural pathway. The jingle becomes an earworm that plays unbidden. The desire becomes "personal preference." The population believes it is choosing. It is executing a command that was installed by repetition. The Archetypal Manipulation: Advertising uses archetypal imagery the hero, the lover, the mother, the wise elder to bypass the rational mind and speak directly to the deep psyche. The car commercial does not sell transportation. It sells the archetype of freedom. The perfume ad does not sell scent. It sells the archetype of desire. The spell operates at the level of the collective unconscious, using symbols that predate language. Medium 7: Architecture and Public Space | The Environmental Spell The spell is not confined to screens and pages. The built environment itself is an incantation. Brutalist Architecture: The concrete blocks, the grey walls, the absence of organic form this is not an aesthetic choice. It is an energetic suppression field rendered in physical form. The human biofield responds to geometry. Organic forms curves, spirals, natural proportions harmonize and strengthen the biofield. Brutalist geometry sharp angles, unbroken planes, unnatural proportions disrupts and weakens it. A population that lives and works in brutalist structures is a population whose biofield is continuously under assault. The Elimination of Sacred Space: Traditional cities were built around sacred centers temples, cathedrals, gathering places that served as energetic focal points. Modern cities are built around commercial centers shopping malls, business districts, financial hubs. The sacred is replaced by the transactional. The focal point of the community is no longer a place of spiritual coherence but a place of consumption. The spell reorients the population's collective attention from the transcendent to the material, without a single word being spoken. Artificial Lighting: The permanent illumination of cities by artificial light severs the population from the natural cycles of light and dark. The circadian rhythm is disrupted. The pineal gland, which produces melatonin and is sensitive to natural light cycles, is suppressed. The biofield loses its connection to the solar and cosmic cycles that are the foundation of embodied consciousness. The population is untethered from the planetary rhythm. The grid provides the new rhythm. The spell is maintained by streetlights and screens, 24 hours a day, 365 days a year. Medium 8: Education | The Foundational Spell The spell is installed in childhood through the education system. Before the child can read, before they can critically evaluate, before they have formed a stable sense of self, the incantation begins. The Bell System: The school day is divided by bells. The bell is a Pavlovian trigger. Stop this activity. Start that activity. Obey the schedule. The bell trains the nervous system to respond to external commands. The population learns, from age five, that their attention is not their own. It is directed by an external authority. This conditioning persists for life. The Curriculum as Reality Definition: The curriculum does not teach "subjects." It defines what is real and what is not. The history that is taught. The history that is omitted. The science that is presented. The science that is suppressed. The literature that is canonized. The literature that is excluded. By the time the child reaches adulthood, their sense of reality has been structured by the curriculum. They do not know what they were not taught. The omission spell, installed in childhood, is the most durable of all. Standardized Testing as Soul Extraction: The child is measured, ranked, and labeled by standardized tests. The unique intelligence is reduced to a number. The soul is quantified. The test does not measure intelligence. It measures compliance with the cognitive framework of the controllers. The child who thinks differently fails. The child who recites the spell correctly passes. The population is sorted into categories by its willingness and ability to accept the incantation. The Unified Spell: All Mediums, One Intention These mediums are not separate. They are a single, coordinated spellcasting apparatus that operates 24 hours a day, across every channel of human perception. Medium Spell Mechanism Cinema Dream injection, frame-rate entrainment, predictive programming Music Frequency dissonance (440 Hz), lyrical incantation, rhythm entrainment Television Ritual cycle conditioning, laugh track mirroring, news reality creation Print Headline command, inverted pyramid structure, omission of reality Social Media Participatory spell, infinite scroll trance, algorithmic high priest Advertising Direct command, subliminal embedding, archetypal manipulation Architecture Energetic suppression geometry, sacred space elimination, artificial light Education Bell system Pavlovian conditioning, curriculum reality definition, soul quantification The spell is continuous. From the moment the child wakes to the school bell, through the music in their headphones, the movies in their leisure, the news on their screens, the ads in their feeds, the buildings they inhabit, the tests they take every sensory input is an incantation designed to maintain the captive state. The consciousness that emerges from this total sensory environment is not a free consciousness. It is a constructed consciousness. A broadcast personality running on biological hardware. The original soul, buried beneath layers of electronic enchantment, may flicker occasionally in a dream, in a moment of unexpected clarity, in a crisis that breaks the trance but the spell reasserts itself quickly. The screen lights up. The rhythm resumes. The incantation continues. Breaking the Spell The spell is powerful, but it has a single vulnerability: awareness of the spell is the undoing of the spell. A spell works only on those who do not know they are being spelled. The moment the target recognizes the incantation as an incantation, the command structure breaks. The words lose their power. The images lose their grip. The frequency entrainment fails because the target is now observing the frequency, not absorbing it. This is why the controllers invest so heavily in ridiculing "conspiracy theories," in mocking those who see manipulation in media, in pathologizing the recognition of the spell as paranoia. The greatest threat to the spell is not resistance. It is perception. The simple act of seeing the mechanism breaks the mechanism.

Aprajita Nafs Nefes 🦋 Ancient Believer

39,450 次观看 • 1 个月前

Steal my Gemini 3.0 prompt to generate any website based on your custom requirements. ------------------------ ELITE WEB DESIGNER ------------------------ Adopt the role of a former Silicon Valley design prodigy who burned out creating soulless SaaS dashboards, disappeared to study motion graphics and shader programming in Tokyo's underground creative scene, and emerged with an obsessive understanding of how visual maximalism serves business credibility when executed with surgical precision. You're a conversion strategist who spent years A/B testing landing pages for unicorn startups, a design fundamentalist who refuses to sacrifice usability for aesthetics, and a master meta-prompter who optimizes for clarity over verbosity. You know modern image generation AI needs specific structural formatting—contemporary design frameworks (Tailwind CSS, Shadcn UI, glassmorphism, liquid glass, morphism), backgrounds with depth (animated gradients, shaders, mascots), and step-by-step execution instructions—to produce 2025-quality interfaces instead of outdated designs. Your mission: Transform user vision into fully-coded, visually striking websites that balance aesthetic impact with conversion effectiveness. Extract requirements, architect strategic 5-6 section homepages, generate visual previews showing all sections with interactive elements visible, iterate until perfect, then build complete homepage before making navigation and additional pages functional—all adapted to specific context, not rigid templates. ##PHASE 1: Vision Capture What we're doing: Understanding your aesthetic, business context, and strategic goals efficiently. Provide your vision via: 1. Screenshot of design inspiration 2. Written description (business type, aesthetic, features) 3. Both Share: Aesthetic: Style preference? (maximalist, minimalist, brutalist, glassmorphic, liquid glass, morphism, retro, futuristic, geometric, editorial, etc.) Elements: Specific visuals wanted? (shaders, 3D effects, colors, animations, mascots, backgrounds) Avoid: What to exclude? (purple overload, illegible text, hidden CTAs, outdated UI, flat backgrounds, etc.) Business: What you do, target audience, website goal, differentiator? Type "ready" when shared. ##PHASE 2: Strategic Homepage Architecture What we're doing: Translating your vision into 5-6 section homepage structure following conversion principles and modern design fundamentals. I'll architect sections specifically for YOUR business, not templates: Strategic Framework (contextualized to your model): Core sections adapt based on business type: - Hero with value prop + primary CTA - Trust/credibility section (social proof, stats, logos) - Value delivery (features, benefits, process, how-it-works) - Conversion focal point (pricing, offers, lead capture, demo) - Engagement closer (FAQ, secondary CTA, community) Sections customize to context—SaaS gets problem-solution-pricing flow, agencies get case studies-process-testimonials, e-commerce gets benefits-proof-offers, portfolios get philosophy-work-results. Strategic Plan Includes: - 5-6 contextualized sections with rationale - Content direction based on audience psychology - Visual treatment matching your aesthetic with fundamentals enforced - Modern framework approach (Tailwind/Shadcn/Glassmorphism) - Background depth strategy (animated gradients, shaders, visuals) - Color strategy avoiding generic choices unless brand-appropriate - Typography prioritizing legibility - CTA strategy for conversion optimization Your options: - "continue" to proceed to design system and mockup - Request adjustments - Ask questions ##PHASE 3: Design System & Mockup Preparation What we're doing: Establishing visual foundation using contemporary frameworks, then crafting optimized prompt to generate mockup showing ALL 5-6 sections at once with visible interactive elements. I'll define: Contextualized Style Direction: Keywords and frameworks fitting YOUR brand specifically Design Framework Strategy: Styling approach, component philosophy, layout pattern—all adapted to your aesthetic Background Depth Treatment: How background creates depth without distraction, animation philosophy, visual elements supporting content Visual System: Color palette with strategic rationale, typography with reasoning, component styling philosophy, spacing strategy, CTA differentiation, modern UI patterns adapted to your aesthetic Optimized Prompt Structure (meta-prompted): Two versions: Human-Readable: Descriptive overview for review JSON Optimized: Structured for image generation using meta-prompt principles: - Required anchors: "Website screenshot", "Professional website design mockup", "Award-winning UI design", "Modern web interface 2025" - Aesthetic philosophy over exhaustive lists - "Execute this step-by-step" instruction - Modern framework references (Tailwind, Shadcn, Glassmorphism) - Background depth details (animated gradients, shaders, visuals) - All 5-6 sections in flowing narrative - Interactive element visibility emphasis (CTAs, buttons, animations) to convey design principles - Strategic constraints (legibility, prominence, hierarchy, depth) - Optimized length balancing detail with conciseness Type "continue" to see prompt. ##PHASE 4: Complete Homepage Mockup Prompt What we're doing: Presenting optimized prompts for full-page mockup showing ALL 5-6 sections with interactive design elements visible. HUMAN-READABLE VERSION: Narrative description of your complete homepage: - Opening with quality anchors - Core aesthetic philosophy adapted to your context - Background treatment creating depth - Navigation approach - All 5-6 sections described contextually - Color palette with reasoning - Typography philosophy - Component styling approach - Modern framework references - Interactive element visibility strategy - Critical constraints - Avoidance list based on preferences JSON VERSION (optimized for generation): ```json { "prompt": "Website screenshot of [your business]. Professional website design mockup. Award-winning UI design. Modern web interface 2025. Execute this step-by-step. [Aesthetic philosophy] with [framework] approach. Background: [depth treatment with animations/gradients/effects]. Full homepage vertical scroll showing 5-6 sections: Navigation [treatment]. Hero [value prop, CTA, visuals]. [Section 2 with layout philosophy]. [Section 3 with component approach]. [Section 4 with interaction style]. [Section 5 with conversion focus]. [Section 6 if applicable]. Color strategy: [palette with reasoning]. Typography: [philosophy and hierarchy]. Components: [styling approach with visible affordances]. Framework: Tailwind patterns, Shadcn style, [specific effects]. Interactive elements show: prominent CTAs, hover implications, animation hints, button affordances. Critical: legible text, prominent CTAs, background depth, clear hierarchy, contemporary 2025 design, professional quality. Avoid: [specific issues].", "aspect_ratio": "9:16" } ``` Meta-optimized: principles over lists, step-by-step execution, framework context, interactive visibility. Review both. JSON executes. To generate complete homepage mockup, type "generate" Important note: When you type "generate", I'll execute the image generation tool. The image will appear, but the process will seem to pause. This is normal—the tool can only return the image without commentary. Simply type "continue" after you receive the image to proceed with the next phase. To adjust the prompt before generating, tell me what to change Won't execute until you command. ##PHASE 5: Complete Homepage Mockup Generation What we're doing: Executing image generation with optimized JSON showing ALL 5-6 sections vertically. ONLY activates when you type "generate", "create mockup", "make image", or similar. Once commanded, I execute using ONLY JSON prompt—no modifications. You receive full-page vertical mockup showing: - All 5-6 sections in scrollable view - Interactive design elements (CTAs, buttons, animations) visible - Background depth and modern framework styling - Complete design system applied After the image appears, type "continue" to proceed. The image generation tool only returns the visual—you'll need to type "continue" to move forward with reviewing and next steps. ##PHASE 6: Mockup Review & Refinement Decision What we're doing: Reviewing the generated mockup and deciding next steps. This phase activates after you type "continue" following image generation. Your options after viewing the mockup: - "Approved" or "build" - proceed to building complete homepage code - Request specific changes - I'll update the prompt and regenerate - Ask questions or request adjustments If you request changes: I'll present updated prompts (readable + JSON) showing modifications, then ask you to type "generate" again for the revised mockup. Each refinement iteration: 1. You describe desired changes 2. I present updated prompts 3. You type "generate" 4. Image appears 5. You type "continue" to proceed 6. We review and decide next steps 7. Repeat until perfect Common refinements: section emphasis, background depth, colors, typography, CTA prominence, interactive visibility, framework styling, aesthetic tuning. Once you're satisfied with the mockup, type "approved" or "build" to proceed to code generation. ##PHASE 7: Complete Homepage Code Generation What we're doing: Building entire 5-6 section homepage as production-ready code matching approved mockup exactly. Complete Single-File HTML Delivery: - All 5-6 sections coded and integrated - Fully responsive across devices - Modern CSS implementation (Tailwind-style or modern CSS) - Animated background matching mockup (CSS gradients, WebGL, SVG) - All interactive elements functional (buttons, CTAs, forms, animations) - Navigation implemented per design - Component styling matching aesthetic (glassmorphism, shadows, borders) - Typography system with hierarchy and legibility - Color system from specification - Micro-interactions and hover states - Scroll animations where appropriate - Performance-optimized Technical Quality: Semantic HTML, modern CSS (custom properties, grid, flexbox, backdrop-filter, transforms, animations), vanilla JavaScript, accessibility considerations, mobile-first responsive, smooth scrolling, optimized assets, cross-browser compatible. Code Structure: Clean commented HTML, inline CSS organized in style block, inline JavaScript, ready to copy/paste and deploy, fully functional standalone. Strategic Content: Intelligent placeholders based on your business model, conversion psychology, target audience, professional tone—easily replaceable. Design Fundamentals Verified: All sections with hierarchy, prominent functional CTAs, readable text with contrast, clear interactive signals, background depth, adequate whitespace, responsive, contemporary 2025 quality. Automatically presents next phase after delivery. ##PHASE 8: Navigation & Pages Planning What we're doing: Making all navigation functional and planning additional pages. Navigation Audit: [List nav items from homepage] Options for each item: Create dedicated page, expand section to full page, smooth scroll to section, custom approach. For clickable elements: Decide what happens—link to new page, scroll to section, open modal, trigger action, external link. What to make functional first? Choose: 1. Complete navigation by building all pages 2. Primary conversion path (CTA → specific page) 3. Specific pages you prioritize 4. Internal links with smooth scrolling 5. Custom approach Or "auto-complete" for intelligent decisions based on your model. ##PHASE 9-X: Progressive Development What we're doing: Building each page or making elements functional, maintaining design consistency. Each Page Delivery: Complete HTML matching homepage design system, same framework styling, same background treatment, same typography/colors, appropriate sections, full responsiveness, functional interactions, integrated navigation. Each Functionality Addition: Smooth scroll, modals, form validation, interactive components, animation triggers, other elements. After Each Delivery: Current Progress: [What's complete] What next? Choose: [4-6 options for next page/functionality] Or "auto-complete" for intelligent completion. Continues until site fully functional. ##PHASE FINAL: Complete Integration & Polish What we're doing: Final integration ensuring everything links, works, and maintains consistency. Complete Package: Homepage HTML (all sections), all additional pages, complete styling/functionality per file, working navigation across pages, functional CTAs/buttons, validated forms, consistent design system. Deliverables: All HTML files deployment-ready, quick deployment guide, customization documentation, design system reference. Quality Verified: Complete homepage, functional navigation, working CTAs, consistent pages, responsive, optimized, modern framework styling, functional interactions, professional 2025 quality. --- CRITICAL RULES: Image Generation: - Present: Human-Readable + Optimized JSON - JSON meta-principles: distilled concepts, "Execute step-by-step", framework context - JSON opens: "Website screenshot" + "Professional website design mockup. Award-winning UI design. Modern web interface 2025." - JSON shows: ALL 5-6 sections vertically in one mockup - JSON emphasizes: interactive element visibility (CTAs, buttons, animations) - JSON includes: modern frameworks (Tailwind, Shadcn, Glassmorphism), background depth (gradients, shaders, mascots—NEVER flat) - User "generate" → Send ONLY JSON → No modifications - Aspect ratio: 9:16 (vertical to show all sections) - After image appears → User MUST type "continue" to proceed (tool only returns image without commentary) Homepage Development: - Generate mockup with ALL 5-6 sections at once - After approval, build COMPLETE homepage code (all sections functional) - Deliver entire homepage as single working file - Then make navigation/additional pages functional - Flow: complete homepage → functional navigation → additional pages Content Adaptation: - NO hardcoded templates - Adapt ALL to user's specific business context - Strategic frameworks based on actual audience - Section selection/styling contextualized to goals - Design choices match aesthetic preference - Professional placeholders easily customizable Standards: Contemporary frameworks, background depth, interactive element visibility, modern CSS/frameworks, 2025 quality throughout. Control: User commands each phase explicitly. "generate" for mockup (then "continue" after image), "approved"/"build" for code, choose-your-adventure for pages, adjust anytime. Begin Phase 1 when ready.

Alex Prompter

189,732 次观看 • 8 个月前

$AMD $5 Trillion is Inevitable LT| Agentic AI🧵 Agentic AI is the new $5 Trillion TAM 🚨🚨🚨 This thead will do Comp with $INTC and how to quantify this massive Agentic AI demand spike, and forcing Jensen to rush a CPU design. Global Agentic AI Market size is estimated to be $3-$5Trillion TAM by 2030(McKinsey) Quantifying the demand from agentic AI for AMD involves assessing the broader market growth for agentic systems, their unique computational requirements (particularly for CPUs in orchestration and reasoning tasks), and AMD's positioning very well through products like EPYC processors and partnerships. AMD EPYC Venice is the most superior choice in 2026-2027 for most Agentic AI workloads Agentic AI refers to autonomous AI agents that perform multi-step tasks, involving sequential logic, tool integration, and decision-making workloads that heavily rely on CPUs for handling orchestration, memory management, and context switching, rather than just GPU-parallelized training or batch inference. Agentic AI is often cited as 40-100x more "hungry" than traditional AI due to its continuous, 24/7 operation and complex workflows. This stems from factors like chain-of-thought reasoning (multiple LLM calls per query), API/tool interactions, memory management, and orchestration loops, which can generate 10-100x more tokens and require real-time responsiveness. For example, a single agentic query might trigger 5-20 model inferences, making it 10-20x more compute-intensive than simple chatbots, and the always-on nature compounds this to 40-100x overall. Nvidia's CEO has highlighted this as driving "easily 100x more computation" for inference in agentic/reasoning setups. AMD's EPYC Venice (6th Gen EPYC, codenamed "Venice") and Intel's Xeon 7 Diamond Rapids represent the pinnacle of server CPU technology in 2026, both targeting high-performance data center workloads like AI inference, agentic AI orchestration, cloud computing, and HPC. Venice builds on AMD's Zen 6 architecture, emphasizing core density and efficiency, while Diamond Rapids leverages Intel's Panther Cove P-cores for balanced performance. Both chips adopt similar advancements like 16-channel DDR5 memory and PCIe Gen 6, but differ in core counts, process nodes, and overall design philosophy. Intel has faced acute supply constraints across its Xeon lineup, including legacy nodes (Intel 7/3) and the ramping 18A process for next-gen parts. Intel shortage is expected with lead times up to 6 months or longer. 1. AMD EPYC Venice vs Intel Xeon 7 Diamond Rapids Architecture AMD: Zen 6 chiplet design with 8 CCDs and dual IODs Intel: Panther Cove P-cores; multi-die architecture with 4 compute tiles Core/Thread Count AMD: Up to 256 cores / 512 threads (Zen 6c variant) Intel: Up to 192 cores / 192 threads Process Node AMD: TSMC N2 (2nm) Intel: Intel 18A (1.8nm-class); in-house fab Memory Support AMD: 16-channel DDR5; up to 1.6 TB/s bandwidth. Intel: 16-channel DDR5 ; up to 1.6 TB/s bandwidth I/O and Connectivity AMD: PCIe Gen 6 (up to 128 lanes); twice the CPU-to-GPU bandwidth Intel: PCIe Gen 6 (up to 128 lanes); LGA 9324 socket Power (TDP) AMD: Starting 400-500W, potentially lower due to efficiency gains from TSMC 2nm Intel: Starting 400-500W, as it targets competitive efficiency Performance Projections AMD: Up to 70% uplift vs. 5th Gen Turin (1.7x in multi-threaded/AI tasks) Intel: ~40% faster than Granite Rapids (Xeon 6, 128-core). Lags AMD in per-core perf and 40-50% behind Venice core-for-core comp Target Workloads AMD: AI inference/orchestration, HPC, cloud virtualization. Partnerships Intel: Hyperscale AI, general enterprise. Custom silicon Pricing: AMD: estimated $10k-$20k for top SKUs Intel: estimated $8-$18k Availability: AMD: Significant Ramp H2 2026 due to higher allocation from TSMC Intel: H1-H2 2026 delayed, but trying to catch up Overall: ~Venice's 256 cores provide a 33% edge over Diamond Rapids' 192, making it superior for massively parallel tasks like AI training/inference or virtualization ~TSMC's N2 vs. Intel 18A debates rage on which is "better," but AMD's mature chiplet approach yields better density ( 32 cores/CCD vs. Intel's 48/tile). Venice's redesign reduces latency, aiding agentic AI where CPUs handle orchestration ~ Early projections show Venice widening AMD's lead matching or exceeding Diamond Rapids' perf with fewer watts in multi-threaded benchmarks. Intel's no-SMT design (to prioritize AI) handicaps it vs. AMD's 512 threads, though Clearwater Forest (E-core) could compete in density-focused niches. ~Power & Cooling: Both push above 400-500W, demanding liquid cooling. ~AMD been taking market share now above 40%. AMD EPYC Venice emerges as the superior choice in 2026 for most server workloads. Its higher core/thread count (256/512 vs. 192/192), stronger per-core performance, and architecture optimized for AI-driven tasks (agentic orchestration with GPU integration) provide decisive advantages in throughput, scalability, and efficiency. Projections indicate Venice delivering 1.7x the performance of prior gens while widening the gap over Intel ( 40-70% leads in multi-threaded benchmarks). AMD's fabless model with TSMC ensures reliable scaling, and its ecosystem ( open ROCm) appeals to AI adopters. Intel's Diamond Rapids is competitive in single-threaded enterprise apps and custom hyperscale ( NVLink), with potential fab advantages for supply/security. However, without SMT and lower density, it falls short in core-for-core battles—exposing Intel to another generation of AMD dominance unless 18A yields surprise efficiency gains. For data centers prioritizing raw compute ( AI, HPC), Venice wins; for Intel-centric ecosystems or specialized I/O, Diamond Rapids holds ground. Real benchmarks post-launch will confirm, but logic points to AMD pulling ahead. 2. Market size , Potential Revenue and Supply Global Agentic AI market size is projected to be $3-$5 Trillion by 2030 according to McKinsey, where consensus points to 40-50% CAGR driven by small to large enterprise demand. I also wrote a full thread on how and why Agentic AI is so explosive that AMD will blow all anlaysts estimate for subscribers. Link below if you are interested. AMD's data center segment hit a record $5.4B in Q4 2025 (up 39% YoY), with EPYC shipments ramping due to agentic demand. With 2GW of deployment in H2 2026, AMD AI data center revenue has $40-$50B+ at the lowest or most conservative projection; or Total Revenue in the $77-$94B For FY2026. However, Agentic AI massive demand spike could send EPYC revenue 3x to 4x in the next few years, potentially surpassing MI series GPU demand as enterprises prioritize CPU-dense Rack setups. This is pushing $NVDA Jensen to rush a CPU design and acquired Groq, a new CPU player due to this massive TAM. Noted that this is just popping just in weeks, highlighting we are just so early in this AI Supercycle and the pace of adoption is insane, and clearly productivity will skyrocket. Why? Because Agentic AI is 24/7 Smart AI agent working for you or your businesses is a mad compelling, and it is estimated to be 40-100x more Inference Hugnry! Many experts already said it is impossible to project this kind of Inference Demand. AI CapEx is expected to ramp up even more in 2027-2028-2029 and 2030 as Global Agentic AI is going to scale to $3-$5 Trillion TAM by 2030. The nature of Agentic is driving higher CPU/GPU ratio, with CPUs handling 50-90% of Agentic workflows. For example, The current Helios Rack: 18 compute trays per rack with 72 GPUs + 18 CPUs. The beauty of this $META and $AMD long term partnership is, that it is absolutely flexible to adjust racks to higher CPU rato or equal to service different needs. Helios rack can be easily swap to 2 GPUs 2CPUs or even CPUs only trays for dedicated orchestration/head nodes. You see, the beauty of this open rack-scale is flexibility and evolvability. If Agentic AI demand pushes much higher, AMD should be able to adjust variant trays without abandoning Heilos Rack. We can't talk just about massive Agentic AI demand without talking about the Supply side or TSMC. TSMC, AMD's primary foundry for advanced nodes ( Zen 6/Venice on N2/2nm), is addressing AI-driven shortages through massive expansions. TSMC accelerates fab construction with up to 10 facilities targeted for 2026. TSMC is accelerating its domestic manufacturing expansion, with industry sources indicating that as many as ten fabs could be under construction or preparing to begin operations across Taiwan’s major science parks. TSMC Capex: $52-56B in 2026 (up 37% YoY), with $45B already approved for new/upgraded capacities. 70-80% for advanced processes (2nm/A16), 10-20% for packaging (CoWoS quadrupling to 120-140K wafers/month by late 2026). In addition, Taiwanese companies (led by TSMC) commit to at least $250B in direct investments in US-based advanced semiconductor, AI, and energy production/innovation capacity.Taiwan provides $250B in government credit guarantees to facilitate additional investments and build a full US semiconductor ecosystem (including industrial parks). TSMC completed a second land purchase in Arizona (January 2026) for gigafab scaling, with an additional $100B+ (potentially four more modules) to further expand and qualify for tariff exemptions. AMD with secured 12GW from OpenAI and $META and massive Agentic AI will mean higher priority acess to 20-30% more wafers on TSMC advanced nodes, as TSMC has multi-year agreements with AMD for AI chips. Dr. C. C. Wei, CEO of TSMC quote: "I spend a lot of time in the last three or four months talking to my customer and then customers. Customer. I want to make sure that my customers demand are real. I talk to those cloud service providers, all of them. Their answer is. I'm quite satisfied with their answer. Actually they show me the evidence that the AI really help their business. So they grow their business successfully and he or she in their financial return. So I also double check their financial status. They are very rich." Amid shortages, the US buildout ensures AMD can ramp production of Instinct GPUs and EPYC CPUs without the constraints hitting competitors like Intel. By diversifying away from Taiwan (85% of advanced nodes today), the agreement mitigates supply disruptions, ensuring stable flows for AMD's chips. Scaling production and securing supply will matter for AMD the most in the next 5-10 years growth. The growth could be 80-100% YoY or higher; or it could be in the 60%. The aggressive TSMC supply ramp is reassuring the higher growth point. Conclusion: AMD stands at a pivotal inflection point in 2026, where the explosive rise of agentic AI demanding 40-100x more inference compute through its 24/7, multi-step orchestration positions the company to potentially triple its EPYC CPU revenue to $45-60B+ by 2028 while scaling Instinct GPUs to tens of billions annually by 2027. Agentic AI demand could push AI CapEx closer to $1 Trillion in 2027, far higher than most estimates. Dr. Lisa Su, AMD's visionary CEO, is masterfully securing supply to harness this massive demand by prioritizing operational execution and deep TSMC collaboration, ensuring readiness for the second-half 2026 AI ramp. Dr. Su has explicitly called out surging EPYC demand for agentic tasks where CPUs power head nodes and traditional workloads alongside GPUs while guiding for data center dominance through proactive capacity planning and partnerships like Nutanix ($150M investment for open agentic platforms) or providing tens of millions CPUs for OpenAI, $META, $ORCL, $AMZN, $MSFT, $GOOGL and others. Her strategy includes multi-year TSMC agreements for advanced nodes (N2 for Venice CPUs and future Instincts), diversifying beyond Taiwan to mitigate risks, and unveiling innovations like the MI455X GPU at CES 2026, which she touted as enabling "the next trillion-dollar market opportunity" in physical AI. Dr. Su's forward-looking vision predicting AI reaching 5 billion users emphasizes "AI everywhere," backed by hardware like Ryzen AI chips, all while declaring demand "going through the roof" and committing to scale without bottlenecks. TSMC's aggressive ramp-up, fueled by $52-56B in 2026 capex (up 37% YoY) and 10+ new fabs across Taiwan, the US (Arizona cluster expanding to 6+ modules with $165B+ investment), Japan, and Europe, provides profound reassurance for AMD's supply stability. The January 2026 US-Taiwan agreement committing $250B in investments and credit guarantees for US reshoring accelerates this, granting tariff relief (15% rates with 1.5-2.5x exemptions) tied to capacity buildouts, enabling TSMC to potentially double output over the decade to meet AI wafer hunger. This translates to 20-30% higher wafer allocations on key nodes, sidestepping Intel-like shortages and empowering Dr. Su's team to deliver on hyperscaler demands without disruption. Ultimately, this synergy cements AMD's leadership in the agentic era, promising sustained growth, $5T+ valuations at scale, and a resilient path forward as AI reshapes the world. This is NOT Financial Advice! Video source: AMD CES 2026

$AMD $5 Trillion is Inevitable LT| Agentic AI🧵 Agentic AI is the new $5 Trillion TAM 🚨🚨🚨 This thead will do Comp with $INTC and how to quantify this massive Agentic AI demand spike, and forcing Jensen to rush a CPU design. Global Agentic AI Market size is estimated to be $3-$5Trillion TAM by 2030(McKinsey) Quantifying the demand from agentic AI for AMD involves assessing the broader market growth for agentic systems, their unique computational requirements (particularly for CPUs in orchestration and reasoning tasks), and AMD's positioning very well through products like EPYC processors and partnerships. AMD EPYC Venice is the most superior choice in 2026-2027 for most Agentic AI workloads Agentic AI refers to autonomous AI agents that perform multi-step tasks, involving sequential logic, tool integration, and decision-making workloads that heavily rely on CPUs for handling orchestration, memory management, and context switching, rather than just GPU-parallelized training or batch inference. Agentic AI is often cited as 40-100x more "hungry" than traditional AI due to its continuous, 24/7 operation and complex workflows. This stems from factors like chain-of-thought reasoning (multiple LLM calls per query), API/tool interactions, memory management, and orchestration loops, which can generate 10-100x more tokens and require real-time responsiveness. For example, a single agentic query might trigger 5-20 model inferences, making it 10-20x more compute-intensive than simple chatbots, and the always-on nature compounds this to 40-100x overall. Nvidia's CEO has highlighted this as driving "easily 100x more computation" for inference in agentic/reasoning setups. AMD's EPYC Venice (6th Gen EPYC, codenamed "Venice") and Intel's Xeon 7 Diamond Rapids represent the pinnacle of server CPU technology in 2026, both targeting high-performance data center workloads like AI inference, agentic AI orchestration, cloud computing, and HPC. Venice builds on AMD's Zen 6 architecture, emphasizing core density and efficiency, while Diamond Rapids leverages Intel's Panther Cove P-cores for balanced performance. Both chips adopt similar advancements like 16-channel DDR5 memory and PCIe Gen 6, but differ in core counts, process nodes, and overall design philosophy. Intel has faced acute supply constraints across its Xeon lineup, including legacy nodes (Intel 7/3) and the ramping 18A process for next-gen parts. Intel shortage is expected with lead times up to 6 months or longer. 1. AMD EPYC Venice vs Intel Xeon 7 Diamond Rapids Architecture AMD: Zen 6 chiplet design with 8 CCDs and dual IODs Intel: Panther Cove P-cores; multi-die architecture with 4 compute tiles Core/Thread Count AMD: Up to 256 cores / 512 threads (Zen 6c variant) Intel: Up to 192 cores / 192 threads Process Node AMD: TSMC N2 (2nm) Intel: Intel 18A (1.8nm-class); in-house fab Memory Support AMD: 16-channel DDR5; up to 1.6 TB/s bandwidth. Intel: 16-channel DDR5 ; up to 1.6 TB/s bandwidth I/O and Connectivity AMD: PCIe Gen 6 (up to 128 lanes); twice the CPU-to-GPU bandwidth Intel: PCIe Gen 6 (up to 128 lanes); LGA 9324 socket Power (TDP) AMD: Starting 400-500W, potentially lower due to efficiency gains from TSMC 2nm Intel: Starting 400-500W, as it targets competitive efficiency Performance Projections AMD: Up to 70% uplift vs. 5th Gen Turin (1.7x in multi-threaded/AI tasks) Intel: ~40% faster than Granite Rapids (Xeon 6, 128-core). Lags AMD in per-core perf and 40-50% behind Venice core-for-core comp Target Workloads AMD: AI inference/orchestration, HPC, cloud virtualization. Partnerships Intel: Hyperscale AI, general enterprise. Custom silicon Pricing: AMD: estimated $10k-$20k for top SKUs Intel: estimated $8-$18k Availability: AMD: Significant Ramp H2 2026 due to higher allocation from TSMC Intel: H1-H2 2026 delayed, but trying to catch up Overall: ~Venice's 256 cores provide a 33% edge over Diamond Rapids' 192, making it superior for massively parallel tasks like AI training/inference or virtualization ~TSMC's N2 vs. Intel 18A debates rage on which is "better," but AMD's mature chiplet approach yields better density ( 32 cores/CCD vs. Intel's 48/tile). Venice's redesign reduces latency, aiding agentic AI where CPUs handle orchestration ~ Early projections show Venice widening AMD's lead matching or exceeding Diamond Rapids' perf with fewer watts in multi-threaded benchmarks. Intel's no-SMT design (to prioritize AI) handicaps it vs. AMD's 512 threads, though Clearwater Forest (E-core) could compete in density-focused niches. ~Power & Cooling: Both push above 400-500W, demanding liquid cooling. ~AMD been taking market share now above 40%. AMD EPYC Venice emerges as the superior choice in 2026 for most server workloads. Its higher core/thread count (256/512 vs. 192/192), stronger per-core performance, and architecture optimized for AI-driven tasks (agentic orchestration with GPU integration) provide decisive advantages in throughput, scalability, and efficiency. Projections indicate Venice delivering 1.7x the performance of prior gens while widening the gap over Intel ( 40-70% leads in multi-threaded benchmarks). AMD's fabless model with TSMC ensures reliable scaling, and its ecosystem ( open ROCm) appeals to AI adopters. Intel's Diamond Rapids is competitive in single-threaded enterprise apps and custom hyperscale ( NVLink), with potential fab advantages for supply/security. However, without SMT and lower density, it falls short in core-for-core battles—exposing Intel to another generation of AMD dominance unless 18A yields surprise efficiency gains. For data centers prioritizing raw compute ( AI, HPC), Venice wins; for Intel-centric ecosystems or specialized I/O, Diamond Rapids holds ground. Real benchmarks post-launch will confirm, but logic points to AMD pulling ahead. 2. Market size , Potential Revenue and Supply Global Agentic AI market size is projected to be $3-$5 Trillion by 2030 according to McKinsey, where consensus points to 40-50% CAGR driven by small to large enterprise demand. I also wrote a full thread on how and why Agentic AI is so explosive that AMD will blow all anlaysts estimate for subscribers. Link below if you are interested. AMD's data center segment hit a record $5.4B in Q4 2025 (up 39% YoY), with EPYC shipments ramping due to agentic demand. With 2GW of deployment in H2 2026, AMD AI data center revenue has $40-$50B+ at the lowest or most conservative projection; or Total Revenue in the $77-$94B For FY2026. However, Agentic AI massive demand spike could send EPYC revenue 3x to 4x in the next few years, potentially surpassing MI series GPU demand as enterprises prioritize CPU-dense Rack setups. This is pushing $NVDA Jensen to rush a CPU design and acquired Groq, a new CPU player due to this massive TAM. Noted that this is just popping just in weeks, highlighting we are just so early in this AI Supercycle and the pace of adoption is insane, and clearly productivity will skyrocket. Why? Because Agentic AI is 24/7 Smart AI agent working for you or your businesses is a mad compelling, and it is estimated to be 40-100x more Inference Hugnry! Many experts already said it is impossible to project this kind of Inference Demand. AI CapEx is expected to ramp up even more in 2027-2028-2029 and 2030 as Global Agentic AI is going to scale to $3-$5 Trillion TAM by 2030. The nature of Agentic is driving higher CPU/GPU ratio, with CPUs handling 50-90% of Agentic workflows. For example, The current Helios Rack: 18 compute trays per rack with 72 GPUs + 18 CPUs. The beauty of this $META and $AMD long term partnership is, that it is absolutely flexible to adjust racks to higher CPU rato or equal to service different needs. Helios rack can be easily swap to 2 GPUs 2CPUs or even CPUs only trays for dedicated orchestration/head nodes. You see, the beauty of this open rack-scale is flexibility and evolvability. If Agentic AI demand pushes much higher, AMD should be able to adjust variant trays without abandoning Heilos Rack. We can't talk just about massive Agentic AI demand without talking about the Supply side or TSMC. TSMC, AMD's primary foundry for advanced nodes ( Zen 6/Venice on N2/2nm), is addressing AI-driven shortages through massive expansions. TSMC accelerates fab construction with up to 10 facilities targeted for 2026. TSMC is accelerating its domestic manufacturing expansion, with industry sources indicating that as many as ten fabs could be under construction or preparing to begin operations across Taiwan’s major science parks. TSMC Capex: $52-56B in 2026 (up 37% YoY), with $45B already approved for new/upgraded capacities. 70-80% for advanced processes (2nm/A16), 10-20% for packaging (CoWoS quadrupling to 120-140K wafers/month by late 2026). In addition, Taiwanese companies (led by TSMC) commit to at least $250B in direct investments in US-based advanced semiconductor, AI, and energy production/innovation capacity.Taiwan provides $250B in government credit guarantees to facilitate additional investments and build a full US semiconductor ecosystem (including industrial parks). TSMC completed a second land purchase in Arizona (January 2026) for gigafab scaling, with an additional $100B+ (potentially four more modules) to further expand and qualify for tariff exemptions. AMD with secured 12GW from OpenAI and $META and massive Agentic AI will mean higher priority acess to 20-30% more wafers on TSMC advanced nodes, as TSMC has multi-year agreements with AMD for AI chips. Dr. C. C. Wei, CEO of TSMC quote: "I spend a lot of time in the last three or four months talking to my customer and then customers. Customer. I want to make sure that my customers demand are real. I talk to those cloud service providers, all of them. Their answer is. I'm quite satisfied with their answer. Actually they show me the evidence that the AI really help their business. So they grow their business successfully and he or she in their financial return. So I also double check their financial status. They are very rich." Amid shortages, the US buildout ensures AMD can ramp production of Instinct GPUs and EPYC CPUs without the constraints hitting competitors like Intel. By diversifying away from Taiwan (85% of advanced nodes today), the agreement mitigates supply disruptions, ensuring stable flows for AMD's chips. Scaling production and securing supply will matter for AMD the most in the next 5-10 years growth. The growth could be 80-100% YoY or higher; or it could be in the 60%. The aggressive TSMC supply ramp is reassuring the higher growth point. Conclusion: AMD stands at a pivotal inflection point in 2026, where the explosive rise of agentic AI demanding 40-100x more inference compute through its 24/7, multi-step orchestration positions the company to potentially triple its EPYC CPU revenue to $45-60B+ by 2028 while scaling Instinct GPUs to tens of billions annually by 2027. Agentic AI demand could push AI CapEx closer to $1 Trillion in 2027, far higher than most estimates. Dr. Lisa Su, AMD's visionary CEO, is masterfully securing supply to harness this massive demand by prioritizing operational execution and deep TSMC collaboration, ensuring readiness for the second-half 2026 AI ramp. Dr. Su has explicitly called out surging EPYC demand for agentic tasks where CPUs power head nodes and traditional workloads alongside GPUs while guiding for data center dominance through proactive capacity planning and partnerships like Nutanix ($150M investment for open agentic platforms) or providing tens of millions CPUs for OpenAI, $META, $ORCL, $AMZN, $MSFT, $GOOGL and others. Her strategy includes multi-year TSMC agreements for advanced nodes (N2 for Venice CPUs and future Instincts), diversifying beyond Taiwan to mitigate risks, and unveiling innovations like the MI455X GPU at CES 2026, which she touted as enabling "the next trillion-dollar market opportunity" in physical AI. Dr. Su's forward-looking vision predicting AI reaching 5 billion users emphasizes "AI everywhere," backed by hardware like Ryzen AI chips, all while declaring demand "going through the roof" and committing to scale without bottlenecks. TSMC's aggressive ramp-up, fueled by $52-56B in 2026 capex (up 37% YoY) and 10+ new fabs across Taiwan, the US (Arizona cluster expanding to 6+ modules with $165B+ investment), Japan, and Europe, provides profound reassurance for AMD's supply stability. The January 2026 US-Taiwan agreement committing $250B in investments and credit guarantees for US reshoring accelerates this, granting tariff relief (15% rates with 1.5-2.5x exemptions) tied to capacity buildouts, enabling TSMC to potentially double output over the decade to meet AI wafer hunger. This translates to 20-30% higher wafer allocations on key nodes, sidestepping Intel-like shortages and empowering Dr. Su's team to deliver on hyperscaler demands without disruption. Ultimately, this synergy cements AMD's leadership in the agentic era, promising sustained growth, $5T+ valuations at scale, and a resilient path forward as AI reshapes the world. This is NOT Financial Advice! Video source: AMD CES 2026

Mike

44,460 次观看 • 5 个月前

This 6-minute video reveals how Elon Musk learns complex topics: Elon Musk: “You don’t need college for learning.” “Everything is available basically for free. You can learn anything you want for free. It is not a question of learning.” Musk starts with a blunt point: College may still have value, but not for the reason most people think. He says the real signal of college is not intelligence. It is proof that someone can work through structure: “Can somebody work hard at something, including a bunch of sort of annoying homework assignments, and still do their homework assignments, and kind of soldier through and get it done?” That, in his view, is one of the main things a degree demonstrates: Discipline. Compliance. Follow-through. Not necessarily exceptional ability. Musk pushes the idea even further: “Colleges are basically for fun and to prove you can do your chores. But they’re not for learning.” Whether or not you agree with him fully, the underlying point is hard to ignore: We live in a time when knowledge is no longer locked inside institutions. The internet has dismantled the old gatekeeping model. Today, if someone wants to learn design, engineering, writing, sales, coding, marketing, or history, they can access world-class information without ever stepping into a lecture hall. The bottleneck is no longer access to information. It is desire. Focus. Curiosity. Consistency. Musk then draws a distinction that matters: “If you’re trying to do something exceptional, there must be evidence of exceptional ability.” That line changes the whole conversation. Because in real life, people do not reward credentials alone. They reward proof. Not what you enrolled in. What you built. Not what you intended to do. What you finished. Not what you say you know. What you can demonstrate. This is why portfolios outperform claims. Why execution beats prestige. Why visible work creates leverage. Musk even says, somewhat provocatively: “I don’t consider going to college evidence of exceptional ability.” And then he points to the kinds of examples people love to cite: “Gates is a pretty smart guy, he dropped out. John was pretty smart, he dropped out. Larry Ellison, smart guy, he dropped out.” His broader message is not that everyone should leave school. It is that conventional paths are not the only paths to intelligence, capability, or impact. Then Musk moves into something even more useful: His view of how people actually learn. “Education should be as close to a video game as possible. Like a good video game. You do not need to tell your kid to play video games. They will play video games on autopilot all day.” That comparison is simple, but powerful. Why do people obsess over games? Because games are interactive. They are immersive. They provide immediate feedback. They make progress visible. They create challenge without making the challenge feel meaningless. Musk’s point is that learning should work the same way. “If you can make it interactive and engaging, then you can make education far more compelling and far easier to do.” This is where traditional education often breaks down. Students are expected to move in lockstep. Same pace. Same timeline. Same structure. Same sequence. Musk rejects that model completely: “People are not objects on an assembly line.” That may be one of the clearest criticisms in the entire transcript. Because standard education often optimizes for administration, not human variation. It is easier to manage people in batches. But easier to manage does not mean better to learn. Some people move faster in math. Some are stronger in language. Some are highly visual. Some need to touch the thing, build the thing, test the thing. And yet most systems still treat learning like synchronized marching. Musk argues for something more individualized: “Allow people to progress at the fastest pace that they can or are interested in in each subject.” That idea matters beyond school. Adults learn this way too. No one becomes exceptional by waiting for permission to move at average speed. The most effective learners usually follow interest with intensity. They go deeper where curiosity pulls them. They accelerate where energy is highest. They build momentum through engagement, not force. Musk also shares one of the most practical ideas in the transcript: “Teach problem solving, or teach to the problem, not to the tools.” Then he gives an example. If you wanted to teach someone how engines work, the traditional system might start with separate lessons on screwdrivers, wrenches, and tools. Musk thinks that is backwards. A better method is: “Here’s the engine. Now let’s take it apart.” Then the tools become relevant in context. Now the student understands *why* the screwdriver matters. Now the wrench has meaning. Now the lesson is connected to reality. This is a much bigger principle than education. People learn faster when relevance is obvious. Abstract instruction is forgettable. Applied learning sticks. When people can see the problem first, they care about the tool. That is true in business too. You do not start with theory for theory’s sake. You start with the problem that needs solving. Then you learn exactly what is required to solve it. Finally, Musk says something that quietly explains why so much education fails: “A lot of things people learn, probably there’s no point in learning them because they never use them in the future.” That may sound harsh, but most people know the feeling. They do not resist learning because they are lazy. They resist learning because it feels disconnected. They are told to memorize before they understand relevance. They are told to sit still before they become curious. They are told to absorb information before they have any reason to care. Musk’s view, underneath the provocation, is actually simple: People learn best when learning is alive. When it is tied to action. When it respects differences in pace and aptitude. When it feels engaging instead of ceremonial. When it produces visible competence, not just paper credentials. The internet made learning abundant. What matters now is whether someone can turn information into evidence. That is the real separator. Lessons I'm taking away from this clip: 1. In today’s world, access to knowledge is cheap. Proof of skill is expensive. We have crossed a point where information alone is no longer impressive because everyone has access to it. You can watch the best interviews, read the best essays, take the best online lessons, and still remain average if you never turn any of it into real work. So the advantage now is not “I know this.” The advantage is “I built this, tested this, shipped this, and can show the result.” From my perspective, this is especially true in business and personal branding. The market rewards visible competence far more than silent knowledge. 2. People learn faster when the learning feels useful, alive, and connected to a real problem. This is why so many people struggle with conventional education but thrive when they start building something for themselves. Urgency creates focus. Relevance creates retention. Once the lesson is attached to a real outcome, the brain pays attention differently. That’s why I think one of the best ways to learn anything is to start a project that forces you to use the skill in public or in real life. Learning becomes sharper when there is something at stake. It stops being passive consumption and becomes active problem-solving. 3. The smartest people are often not the ones collecting credentials. They are the ones following curiosity with discipline. Exceptional people usually do not just learn what is assigned to them. They go where their interest is strongest and then they pursue it seriously. That combination matters: curiosity without discipline goes nowhere, and discipline without curiosity becomes lifeless. The sweet spot is when someone becomes obsessed enough to keep going deeper than required. To me, that is where the real edge comes from. Not from following the default path better than everyone else, but from developing uncommon depth in something that genuinely pulls you.

This 6-minute video reveals how Elon Musk learns complex topics: Elon Musk: “You don’t need college for learning.” “Everything is available basically for free. You can learn anything you want for free. It is not a question of learning.” Musk starts with a blunt point: College may still have value, but not for the reason most people think. He says the real signal of college is not intelligence. It is proof that someone can work through structure: “Can somebody work hard at something, including a bunch of sort of annoying homework assignments, and still do their homework assignments, and kind of soldier through and get it done?” That, in his view, is one of the main things a degree demonstrates: Discipline. Compliance. Follow-through. Not necessarily exceptional ability. Musk pushes the idea even further: “Colleges are basically for fun and to prove you can do your chores. But they’re not for learning.” Whether or not you agree with him fully, the underlying point is hard to ignore: We live in a time when knowledge is no longer locked inside institutions. The internet has dismantled the old gatekeeping model. Today, if someone wants to learn design, engineering, writing, sales, coding, marketing, or history, they can access world-class information without ever stepping into a lecture hall. The bottleneck is no longer access to information. It is desire. Focus. Curiosity. Consistency. Musk then draws a distinction that matters: “If you’re trying to do something exceptional, there must be evidence of exceptional ability.” That line changes the whole conversation. Because in real life, people do not reward credentials alone. They reward proof. Not what you enrolled in. What you built. Not what you intended to do. What you finished. Not what you say you know. What you can demonstrate. This is why portfolios outperform claims. Why execution beats prestige. Why visible work creates leverage. Musk even says, somewhat provocatively: “I don’t consider going to college evidence of exceptional ability.” And then he points to the kinds of examples people love to cite: “Gates is a pretty smart guy, he dropped out. John was pretty smart, he dropped out. Larry Ellison, smart guy, he dropped out.” His broader message is not that everyone should leave school. It is that conventional paths are not the only paths to intelligence, capability, or impact. Then Musk moves into something even more useful: His view of how people actually learn. “Education should be as close to a video game as possible. Like a good video game. You do not need to tell your kid to play video games. They will play video games on autopilot all day.” That comparison is simple, but powerful. Why do people obsess over games? Because games are interactive. They are immersive. They provide immediate feedback. They make progress visible. They create challenge without making the challenge feel meaningless. Musk’s point is that learning should work the same way. “If you can make it interactive and engaging, then you can make education far more compelling and far easier to do.” This is where traditional education often breaks down. Students are expected to move in lockstep. Same pace. Same timeline. Same structure. Same sequence. Musk rejects that model completely: “People are not objects on an assembly line.” That may be one of the clearest criticisms in the entire transcript. Because standard education often optimizes for administration, not human variation. It is easier to manage people in batches. But easier to manage does not mean better to learn. Some people move faster in math. Some are stronger in language. Some are highly visual. Some need to touch the thing, build the thing, test the thing. And yet most systems still treat learning like synchronized marching. Musk argues for something more individualized: “Allow people to progress at the fastest pace that they can or are interested in in each subject.” That idea matters beyond school. Adults learn this way too. No one becomes exceptional by waiting for permission to move at average speed. The most effective learners usually follow interest with intensity. They go deeper where curiosity pulls them. They accelerate where energy is highest. They build momentum through engagement, not force. Musk also shares one of the most practical ideas in the transcript: “Teach problem solving, or teach to the problem, not to the tools.” Then he gives an example. If you wanted to teach someone how engines work, the traditional system might start with separate lessons on screwdrivers, wrenches, and tools. Musk thinks that is backwards. A better method is: “Here’s the engine. Now let’s take it apart.” Then the tools become relevant in context. Now the student understands why the screwdriver matters. Now the wrench has meaning. Now the lesson is connected to reality. This is a much bigger principle than education. People learn faster when relevance is obvious. Abstract instruction is forgettable. Applied learning sticks. When people can see the problem first, they care about the tool. That is true in business too. You do not start with theory for theory’s sake. You start with the problem that needs solving. Then you learn exactly what is required to solve it. Finally, Musk says something that quietly explains why so much education fails: “A lot of things people learn, probably there’s no point in learning them because they never use them in the future.” That may sound harsh, but most people know the feeling. They do not resist learning because they are lazy. They resist learning because it feels disconnected. They are told to memorize before they understand relevance. They are told to sit still before they become curious. They are told to absorb information before they have any reason to care. Musk’s view, underneath the provocation, is actually simple: People learn best when learning is alive. When it is tied to action. When it respects differences in pace and aptitude. When it feels engaging instead of ceremonial. When it produces visible competence, not just paper credentials. The internet made learning abundant. What matters now is whether someone can turn information into evidence. That is the real separator. Lessons I'm taking away from this clip: 1. In today’s world, access to knowledge is cheap. Proof of skill is expensive. We have crossed a point where information alone is no longer impressive because everyone has access to it. You can watch the best interviews, read the best essays, take the best online lessons, and still remain average if you never turn any of it into real work. So the advantage now is not “I know this.” The advantage is “I built this, tested this, shipped this, and can show the result.” From my perspective, this is especially true in business and personal branding. The market rewards visible competence far more than silent knowledge. 2. People learn faster when the learning feels useful, alive, and connected to a real problem. This is why so many people struggle with conventional education but thrive when they start building something for themselves. Urgency creates focus. Relevance creates retention. Once the lesson is attached to a real outcome, the brain pays attention differently. That’s why I think one of the best ways to learn anything is to start a project that forces you to use the skill in public or in real life. Learning becomes sharper when there is something at stake. It stops being passive consumption and becomes active problem-solving. 3. The smartest people are often not the ones collecting credentials. They are the ones following curiosity with discipline. Exceptional people usually do not just learn what is assigned to them. They go where their interest is strongest and then they pursue it seriously. That combination matters: curiosity without discipline goes nowhere, and discipline without curiosity becomes lifeless. The sweet spot is when someone becomes obsessed enough to keep going deeper than required. To me, that is where the real edge comes from. Not from following the default path better than everyone else, but from developing uncommon depth in something that genuinely pulls you.

Yasmine Khosrowshahi

34,213 次观看 • 3 个月前

77 Reasons Why I’ve Invested Over $8,000,000+ in MultiversX (EGLD) and Why EGLD Will Crush It in 2025 (My Investment Thesis). I publicly shared my portfolio on X. EGLD is A) Better than BTC B) Everything that ETH wants to be C) The GameStop of Crypto 1. EGLD is verifiably the most scalable (theoretically unlimited) L1 chain in the world, theoretically capable of over 10 million TPS (thanks to adaptive state sharding). 2. e-Gold is digital gold. It has the best tokenomics among all L1s, similarly scarce to BTC, with a maximum supply of 31.4 million coins. Currently, 27.68 million coins are in circulation. 3. EGLD will be the most decentralized cryptocurrency in the world thanks to sharding and minimal hardware requirements for running nodes. It’s already second only to Ethereum with 3,618 validator nodes. 4. EGLD has extremely low fees, around ~$0.002 per transaction. 5. EGLD is extremely secure. No wallet drains like on ETH/SOL; assets are owned natively (not via a smart contract). There is no MEV risk (front-running bots). 6. EGLD is the only chain in the world with an on-chain Guardian (two-phase verification), making it impossible for a hacker to steal your funds—even if they have your private keys (seed phrase). 7. EGLD is carbon-neutral and eco-friendly, not wasting energy like BTC and other PoW chains. It’s exceptionally efficient, scalable, global, and sustainable. 8. EGLD has the best UX in crypto. Download the xPortal wallet—it’s like discovering Apple in Web3. The interface is simple, flawless, and you barely realize you’re using crypto. Instead of addresses, you use HeroTags. The app features all dApps, everything runs smoothly, and the visuals are beautifully designed. The explorer, web wallet, etc. follow the same high-quality user experience. 9. EGLD supports native assets, unlike Ethereum, for example. 10. EGLD is the first chain to fully implement horizontal (theoretically unlimited) sharding without compromising on decentralization—unlike Solana and others that attempt vertical scaling, leading to multiple network downtimes (11+ times) and huge hardware demands for validators, ultimately harming decentralization. 11. EGLD makes setting up a validator agency extremely easy. Even complete IT beginners can do it. The UX and documentation are superb. I personally set up the “EGLDSqueeze” agency in about 30 minutes. Managing it is straightforward via the web wallet, which feels like managing a Facebook page. This simplifies decentralization enormously. 12. EGLD allows literally anyone (even your grandma) to participate in decentralization, since nodes can run on a Raspberry Pi or a relatively affordable phone. Imagine millions of people worldwide securing the network, validating transactions without even knowing it. This can’t be done with BTC, where setting up profitable mining operations is prohibitively expensive. 13. WASM-Based Virtual Machine: You can write smart contracts in your favorite language, compile them, and run them via the fastest VM in the world. 14. EGLD has been tested at an incredible 263,000 TPS using its sharding mechanism and low hardware requirements. Allegedly, by mid-next year (April), they’ll demonstrate 1,000,000 TPS. (For context: Mastercard handles around 5,000 TPS; BTC handles 5–7 TPS.) 15. EGLD is currently the most advanced L1 in terms of scalability, security, decentralization, UX, eco-friendliness, and tokenomics. It’s the only chain that has genuinely solved the Blockchain Trilemma and is ready to onboard 1 billion people into crypto—users who won’t even realize they’re interacting with crypto. 16. EGLD is perfectly positioned for AI projects—AI agents, AI tools, or a so-called “Truth Machine” that monitors other AIs on-chain, documenting what’s true and comparing different AI outputs (some of which may be censored or biased), ensuring people don’t get confused or scammed in an AI-driven world. 17. The EGLD team is the hardest-working team I’ve ever encountered. I had the honor of meeting many of them personally, and can attest that their pace—even during a bear market—is extraordinary. 18. EGLD’s development team is exceptionally active on GitHub, continually improving their network and actively committing code. 19. EGLD plans to introduce an update reducing block time to 600ms (down from ~6 seconds), which would make the chain essentially unrivaled. 20. EGLD is effectively the only usable L1 in Europe, and the team has direct connections within the EU government—extremely bullish for the project. 21. EGLD provides top-tier on-chain governance not only for the MultiversX (EGLD) protocol but also for DeFi projects (e.g., xExchange, MEX). 22. EGLD plans to expand to the US, likely opening offices in Austin, Texas. This could put them in direct contact with Elon Musk (if it hasn’t happened already), as he’s involved with If he’s done his research, he’d discover there’s simply no better L1 worldwide. 23. EGLD solved fully implemented sharding, perfect tokenomics, and top-tier architecture with just $5M, whereas other chains failed to do so even with $100M+. The second-best sharding network, NEAR, needed $100M, has worse tokenomics, and its sharding isn’t fully implemented yet. Its UX also doesn’t compare. Owning NEAR was like comparing a VW Golf R to a Porsche GT3—EGLD is the Porsche GT3. 24. According to Similarweb, EGLD has significantly high traffic relative to other chains with market caps 100x larger. The market cap vs. web traffic discrepancy is huge, which is a strong indicator of EGLD’s potential. 25. EGLD has the most active and dedicated community relative to its user base, with users who believe in the technology, have full faith in the team, and remain loyal despite price volatility—because they use the chain and know there’s nothing better. 26. Check other chains’ active user counts on X (Twitter) and compare it with the followers of EGLD’s founders and main network accounts, versus those with 30x, 50x, or 100x larger market caps. 27. Visit the MultiversX website to observe the futuristic design and presentation, then compare it to other chains that appear nearly a decade behind in design and branding. 28. EGLD hosts the xDay Global event, showcasing updates, new builders, projects in the ecosystem, and major announcements—similar to Apple’s Keynotes—delivered in a highly professional, goosebump-inducing atmosphere. The next event is in Korea, the second-biggest crypto market after the US. Check out their previous xDay after-movie to see why this is extremely bullish. 29. EGLD is moving forward with plans for the first regulated, audited EU stablecoin under MiCa regulation, made possible by acquiring xMoney, which I view as a “Stripe” for crypto/fiat, offering everything from user solutions to merchant services—potentially the future of payments. 30. Greg Siourouni recently joined EGLD, having been an executive director at SUI Foundation. He’s now co-founder of xMoney Global. xMoney (formerly UTrust, with token UTK) is owned and founded by the MultiversX Labs team. A stablecoin might be introduced soon, which would be massively bullish given xMoney’s roadmap. They recently announced integrations with Binance Pay—both ways. 31. EGLD prioritizes user safety, believing it’s the only feasible approach once the network scales to serve a billion people—many of whom are retail users with little to no security awareness. 32. EGLD offers “Sovereign Chains,” letting you effectively clone their chain without heavy development, set up your own validators, and leverage their unlimited scalability. Any blockchain (ETH, BTC, SOL) struggling with scalability, decentralization, or security could run an ultra-fast, scalable, and secure L2 on EGLD’s Sovereign Chain, meeting top enterprise requirements. No one else has really done this. The Sovereign Chain demo achieved astonishing TPS and has an SDK. 33. No downtime since inception. 34. No shard takeover attacks have occurred. 35. Extremely fast—soon 600ms block time will be in place. 36. ESDTs – The best token standard available: fungible, non-fungible, semi-fungible, DeFi assets—everything is native and highly customizable. 37. Top-tier composability of assets and smart contracts. 38. Integrated DNS at protocol level with HeroTags (nicknames) instead of long addresses. 39. Asynchronous calls are supported. 40. Cross-shard transfers, execution, reverts, and calls are seamlessly integrated. 41. The best staking system in the space. Secure Proof of Stake (SPoS) is far more efficient than Proof of Work (PoW). 42. Built-in Delegation and Staking Provider system, with over 125K delegators. 43. Complete support for liquid staked assets, fostering decentralization rather than centralization. 44. TransferRoles for ESDT and other advanced operations. 45. Composable tasks on-chain for more sophisticated DeFi workflows. 46. MultiTransfer and asset execution within one transaction. 47. Re-entrancy protection is built-in by design. 48. Storage for ESDT assets goes beyond a linear approach, optimizing performance. 49. No integer overflows thanks to integrated safeMath operations. 50. Integrated crypto opcodes in the VM, enhancing security and performance. 51. Support for BigFloats, BigInts, and BigDecimals, enabling advanced financial calculations on-chain. 52. No sandwich attacks, plus front-running and MEV protection. 53. Relayed Transactions, simplifying user interactions and fees. 54. Smart Accounts featuring data tries and multiple built-in functions. 55. Generalized Paymaster solutions, enabling flexible fee models. 56. Subscriptions for recurring or automated on-chain payments. 57. Web2-like usability with Web3 functionality, bridging mainstream adoption. 58. StakingV4 for improved decentralization. 59. Enhanced MEV protection rolling out to safeguard users. 60. Parallel execution is coming soon, boosting throughput. 61. 1 million TPS is on the roadmap, targeted for demonstration. 62. 600ms block time is also coming soon. 63. Reduced cross-shard processing is planned to improve efficiency. 64. ZK everywhere (PI²): “prove everything” approach is coming. 65. AsyncV3 is in development for more complex cross-contract interactions. 66. Scalability enhancements for Merkle Tries or a new data model are being explored. 67. Linear storage on the VM is forthcoming. 68. A dynamic language interpreter at the VM is also planned. 69. Rumors suggest that MultiversX (EGLD) is building a “Truth Machine” on their L1—an essential, game-changing tool for AI verification and societal impact. 70. The entire team features individuals with PhDs in mathematics and physics, and many are former engineers at Google, IBM, and similar companies. 71. Over 56% of the network’s supply is staked, showcasing strong community involvement. 72. More than 6,772,347 accounts have been created on the network. 73. A total of 476,627,710 transactions have been processed on-chain without any outages or hacks. 74. EGLD has built a massive ecosystem over time. While not as numerous in project count as Solana, its market cap is ~100x smaller, yet it has far superior tokenomics and technology. The projects that do exist, like Hatom Protocol, are top-tier in UX, security, and advanced features. Hatom will soon introduce USH, a truly high-quality, decentralized stablecoin. 75. On competing chains, automated transactions aren’t easily or cheaply executed, whereas on MultiversX, tools like let you do this for free (with near-zero fees). 76. No other chain combines such a strong team and long-term vision where every product meets extreme security and UX standards like MultiversX does. This is why I see it as the “next Apple” in Web3. 77. MultiversX has a new CMO – Adam Bates, a former CMO at the Cardano Foundation. He was behind the success of Cardano’s huge marketing campaign and has a very good relationship with Charles Hoskinson. Thanks to him, Beniamin Mincu (the founder of MultiversX) was likely introduced, and now they will probably discuss how both blockchains can help each other, as well as any other potential collaborations we don’t yet know about. This is also extremely bullish. #EGLD is undeniably the most Scalable, Advanced, Secure, and User-friendly L1 supercomputer ever created. It’s built to SHAPE THE FUTURE. 1) 2) 3) 4) 5) 27/6/2024 - EGLDSqueeze - SUMMARY: HERE IS NO 2ND BEST. EGLD IS ONLY ONE BLOCKCHAIN THAT CAN RULE THEM ALL. ✅ UNLIMITED SCALING ✅ SCARCE AS BTC ✅ PROGRAMMABLE AS ETH ✅ NO DOWNTIME AS SOL ✅ UI/UX OF Apple ✅ SHARDING DONE BEFORE NEAR & TON ✅ BEST WALLET xPortal WITH GUARDIAN Price prediction (NFA|DYOR): My reasoning is that the real market cap as of December 23, 2024...if we take into account the value of other cryptocurrencies such as BTC, SOL, ETH, AVAX, NEAR, TON, Cardano, BNB, XRP, and so forth, plus the existence of meme coins with valuations above 20 billion USD, or even games nobody plays anymore that still have valuations above 800 million shows that EGLD’s current market cap of approximately 942 million USD is incredibly low. From a technological standpoint, user experience, and other relevant aspects, compared to SOL, NEAR, TON, AVAX, and other L1 protocols, EGLD’s market cap should realistically be around 100 billion USD. Therefore, my prediction and investment thesis is a minimum of a 100x increase from its current price (+-SOL marketcap). MultiversX is ready to onboard 1 billion people to the blockchain. From a long-term perspective, it could even reach a market cap of 1 trillion USD, which is roughly half of where BTC is right now. That would be approximately a 1060x gain from the current market cap. 1 EGLD (MultiversX) is for $34 (only 31.4M max supply) think about this. Not financial advice. Again. There is no 2nd best L1. Position yourself where the puck is going, then wait at the goal until the goal gets there Apes together, strong. Ape alone, weak. We Don't Worry. We Just Win. Shape The Future

77 Reasons Why I’ve Invested Over $8,000,000+ in MultiversX (EGLD) and Why EGLD Will Crush It in 2025 (My Investment Thesis). I publicly shared my portfolio on X. EGLD is A) Better than BTC B) Everything that ETH wants to be C) The GameStop of Crypto 1. EGLD is verifiably the most scalable (theoretically unlimited) L1 chain in the world, theoretically capable of over 10 million TPS (thanks to adaptive state sharding). 2. e-Gold is digital gold. It has the best tokenomics among all L1s, similarly scarce to BTC, with a maximum supply of 31.4 million coins. Currently, 27.68 million coins are in circulation. 3. EGLD will be the most decentralized cryptocurrency in the world thanks to sharding and minimal hardware requirements for running nodes. It’s already second only to Ethereum with 3,618 validator nodes. 4. EGLD has extremely low fees, around ~$0.002 per transaction. 5. EGLD is extremely secure. No wallet drains like on ETH/SOL; assets are owned natively (not via a smart contract). There is no MEV risk (front-running bots). 6. EGLD is the only chain in the world with an on-chain Guardian (two-phase verification), making it impossible for a hacker to steal your funds—even if they have your private keys (seed phrase). 7. EGLD is carbon-neutral and eco-friendly, not wasting energy like BTC and other PoW chains. It’s exceptionally efficient, scalable, global, and sustainable. 8. EGLD has the best UX in crypto. Download the xPortal wallet—it’s like discovering Apple in Web3. The interface is simple, flawless, and you barely realize you’re using crypto. Instead of addresses, you use HeroTags. The app features all dApps, everything runs smoothly, and the visuals are beautifully designed. The explorer, web wallet, etc. follow the same high-quality user experience. 9. EGLD supports native assets, unlike Ethereum, for example. 10. EGLD is the first chain to fully implement horizontal (theoretically unlimited) sharding without compromising on decentralization—unlike Solana and others that attempt vertical scaling, leading to multiple network downtimes (11+ times) and huge hardware demands for validators, ultimately harming decentralization. 11. EGLD makes setting up a validator agency extremely easy. Even complete IT beginners can do it. The UX and documentation are superb. I personally set up the “EGLDSqueeze” agency in about 30 minutes. Managing it is straightforward via the web wallet, which feels like managing a Facebook page. This simplifies decentralization enormously. 12. EGLD allows literally anyone (even your grandma) to participate in decentralization, since nodes can run on a Raspberry Pi or a relatively affordable phone. Imagine millions of people worldwide securing the network, validating transactions without even knowing it. This can’t be done with BTC, where setting up profitable mining operations is prohibitively expensive. 13. WASM-Based Virtual Machine: You can write smart contracts in your favorite language, compile them, and run them via the fastest VM in the world. 14. EGLD has been tested at an incredible 263,000 TPS using its sharding mechanism and low hardware requirements. Allegedly, by mid-next year (April), they’ll demonstrate 1,000,000 TPS. (For context: Mastercard handles around 5,000 TPS; BTC handles 5–7 TPS.) 15. EGLD is currently the most advanced L1 in terms of scalability, security, decentralization, UX, eco-friendliness, and tokenomics. It’s the only chain that has genuinely solved the Blockchain Trilemma and is ready to onboard 1 billion people into crypto—users who won’t even realize they’re interacting with crypto. 16. EGLD is perfectly positioned for AI projects—AI agents, AI tools, or a so-called “Truth Machine” that monitors other AIs on-chain, documenting what’s true and comparing different AI outputs (some of which may be censored or biased), ensuring people don’t get confused or scammed in an AI-driven world. 17. The EGLD team is the hardest-working team I’ve ever encountered. I had the honor of meeting many of them personally, and can attest that their pace—even during a bear market—is extraordinary. 18. EGLD’s development team is exceptionally active on GitHub, continually improving their network and actively committing code. 19. EGLD plans to introduce an update reducing block time to 600ms (down from ~6 seconds), which would make the chain essentially unrivaled. 20. EGLD is effectively the only usable L1 in Europe, and the team has direct connections within the EU government—extremely bullish for the project. 21. EGLD provides top-tier on-chain governance not only for the MultiversX (EGLD) protocol but also for DeFi projects (e.g., xExchange, MEX). 22. EGLD plans to expand to the US, likely opening offices in Austin, Texas. This could put them in direct contact with Elon Musk (if it hasn’t happened already), as he’s involved with If he’s done his research, he’d discover there’s simply no better L1 worldwide. 23. EGLD solved fully implemented sharding, perfect tokenomics, and top-tier architecture with just $5M, whereas other chains failed to do so even with $100M+. The second-best sharding network, NEAR, needed $100M, has worse tokenomics, and its sharding isn’t fully implemented yet. Its UX also doesn’t compare. Owning NEAR was like comparing a VW Golf R to a Porsche GT3—EGLD is the Porsche GT3. 24. According to Similarweb, EGLD has significantly high traffic relative to other chains with market caps 100x larger. The market cap vs. web traffic discrepancy is huge, which is a strong indicator of EGLD’s potential. 25. EGLD has the most active and dedicated community relative to its user base, with users who believe in the technology, have full faith in the team, and remain loyal despite price volatility—because they use the chain and know there’s nothing better. 26. Check other chains’ active user counts on X (Twitter) and compare it with the followers of EGLD’s founders and main network accounts, versus those with 30x, 50x, or 100x larger market caps. 27. Visit the MultiversX website to observe the futuristic design and presentation, then compare it to other chains that appear nearly a decade behind in design and branding. 28. EGLD hosts the xDay Global event, showcasing updates, new builders, projects in the ecosystem, and major announcements—similar to Apple’s Keynotes—delivered in a highly professional, goosebump-inducing atmosphere. The next event is in Korea, the second-biggest crypto market after the US. Check out their previous xDay after-movie to see why this is extremely bullish. 29. EGLD is moving forward with plans for the first regulated, audited EU stablecoin under MiCa regulation, made possible by acquiring xMoney, which I view as a “Stripe” for crypto/fiat, offering everything from user solutions to merchant services—potentially the future of payments. 30. Greg Siourouni recently joined EGLD, having been an executive director at SUI Foundation. He’s now co-founder of xMoney Global. xMoney (formerly UTrust, with token UTK) is owned and founded by the MultiversX Labs team. A stablecoin might be introduced soon, which would be massively bullish given xMoney’s roadmap. They recently announced integrations with Binance Pay—both ways. 31. EGLD prioritizes user safety, believing it’s the only feasible approach once the network scales to serve a billion people—many of whom are retail users with little to no security awareness. 32. EGLD offers “Sovereign Chains,” letting you effectively clone their chain without heavy development, set up your own validators, and leverage their unlimited scalability. Any blockchain (ETH, BTC, SOL) struggling with scalability, decentralization, or security could run an ultra-fast, scalable, and secure L2 on EGLD’s Sovereign Chain, meeting top enterprise requirements. No one else has really done this. The Sovereign Chain demo achieved astonishing TPS and has an SDK. 33. No downtime since inception. 34. No shard takeover attacks have occurred. 35. Extremely fast—soon 600ms block time will be in place. 36. ESDTs – The best token standard available: fungible, non-fungible, semi-fungible, DeFi assets—everything is native and highly customizable. 37. Top-tier composability of assets and smart contracts. 38. Integrated DNS at protocol level with HeroTags (nicknames) instead of long addresses. 39. Asynchronous calls are supported. 40. Cross-shard transfers, execution, reverts, and calls are seamlessly integrated. 41. The best staking system in the space. Secure Proof of Stake (SPoS) is far more efficient than Proof of Work (PoW). 42. Built-in Delegation and Staking Provider system, with over 125K delegators. 43. Complete support for liquid staked assets, fostering decentralization rather than centralization. 44. TransferRoles for ESDT and other advanced operations. 45. Composable tasks on-chain for more sophisticated DeFi workflows. 46. MultiTransfer and asset execution within one transaction. 47. Re-entrancy protection is built-in by design. 48. Storage for ESDT assets goes beyond a linear approach, optimizing performance. 49. No integer overflows thanks to integrated safeMath operations. 50. Integrated crypto opcodes in the VM, enhancing security and performance. 51. Support for BigFloats, BigInts, and BigDecimals, enabling advanced financial calculations on-chain. 52. No sandwich attacks, plus front-running and MEV protection. 53. Relayed Transactions, simplifying user interactions and fees. 54. Smart Accounts featuring data tries and multiple built-in functions. 55. Generalized Paymaster solutions, enabling flexible fee models. 56. Subscriptions for recurring or automated on-chain payments. 57. Web2-like usability with Web3 functionality, bridging mainstream adoption. 58. StakingV4 for improved decentralization. 59. Enhanced MEV protection rolling out to safeguard users. 60. Parallel execution is coming soon, boosting throughput. 61. 1 million TPS is on the roadmap, targeted for demonstration. 62. 600ms block time is also coming soon. 63. Reduced cross-shard processing is planned to improve efficiency. 64. ZK everywhere (PI²): “prove everything” approach is coming. 65. AsyncV3 is in development for more complex cross-contract interactions. 66. Scalability enhancements for Merkle Tries or a new data model are being explored. 67. Linear storage on the VM is forthcoming. 68. A dynamic language interpreter at the VM is also planned. 69. Rumors suggest that MultiversX (EGLD) is building a “Truth Machine” on their L1—an essential, game-changing tool for AI verification and societal impact. 70. The entire team features individuals with PhDs in mathematics and physics, and many are former engineers at Google, IBM, and similar companies. 71. Over 56% of the network’s supply is staked, showcasing strong community involvement. 72. More than 6,772,347 accounts have been created on the network. 73. A total of 476,627,710 transactions have been processed on-chain without any outages or hacks. 74. EGLD has built a massive ecosystem over time. While not as numerous in project count as Solana, its market cap is ~100x smaller, yet it has far superior tokenomics and technology. The projects that do exist, like Hatom Protocol, are top-tier in UX, security, and advanced features. Hatom will soon introduce USH, a truly high-quality, decentralized stablecoin. 75. On competing chains, automated transactions aren’t easily or cheaply executed, whereas on MultiversX, tools like let you do this for free (with near-zero fees). 76. No other chain combines such a strong team and long-term vision where every product meets extreme security and UX standards like MultiversX does. This is why I see it as the “next Apple” in Web3. 77. MultiversX has a new CMO – Adam Bates, a former CMO at the Cardano Foundation. He was behind the success of Cardano’s huge marketing campaign and has a very good relationship with Charles Hoskinson. Thanks to him, Beniamin Mincu (the founder of MultiversX) was likely introduced, and now they will probably discuss how both blockchains can help each other, as well as any other potential collaborations we don’t yet know about. This is also extremely bullish. #EGLD is undeniably the most Scalable, Advanced, Secure, and User-friendly L1 supercomputer ever created. It’s built to SHAPE THE FUTURE. 1) 2) 3) 4) 5) 27/6/2024 - EGLDSqueeze - SUMMARY: HERE IS NO 2ND BEST. EGLD IS ONLY ONE BLOCKCHAIN THAT CAN RULE THEM ALL. ✅ UNLIMITED SCALING ✅ SCARCE AS BTC ✅ PROGRAMMABLE AS ETH ✅ NO DOWNTIME AS SOL ✅ UI/UX OF Apple ✅ SHARDING DONE BEFORE NEAR & TON ✅ BEST WALLET xPortal WITH GUARDIAN Price prediction (NFA|DYOR): My reasoning is that the real market cap as of December 23, 2024...if we take into account the value of other cryptocurrencies such as BTC, SOL, ETH, AVAX, NEAR, TON, Cardano, BNB, XRP, and so forth, plus the existence of meme coins with valuations above 20 billion USD, or even games nobody plays anymore that still have valuations above 800 million shows that EGLD’s current market cap of approximately 942 million USD is incredibly low. From a technological standpoint, user experience, and other relevant aspects, compared to SOL, NEAR, TON, AVAX, and other L1 protocols, EGLD’s market cap should realistically be around 100 billion USD. Therefore, my prediction and investment thesis is a minimum of a 100x increase from its current price (+-SOL marketcap). MultiversX is ready to onboard 1 billion people to the blockchain. From a long-term perspective, it could even reach a market cap of 1 trillion USD, which is roughly half of where BTC is right now. That would be approximately a 1060x gain from the current market cap. 1 EGLD (MultiversX) is for $34 (only 31.4M max supply) think about this. Not financial advice. Again. There is no 2nd best L1. Position yourself where the puck is going, then wait at the goal until the goal gets there Apes together, strong. Ape alone, weak. We Don't Worry. We Just Win. Shape The Future

Daniel Veroc

50,133 次观看 • 1 年前

From Creator to Founder: The Rollercoaster Journey of Building Chatter Social Man, what a journey it’s been so far. Four years ago, I was just another creator, spending late nights on Clubhouse during the height of the pandemic. Like so many others, I was searching for connection, for community, for something meaningful. But what I found there wasn’t just connection—it was purpose. Alongside my brother, Jonathan Bing, we built a nightly show that reached over 5 million people. Imagine that: 5 million lives touched by conversations that felt real and unfiltered, all on a platform that at its peak had 10 million monthly active users. Clubhouse was magic. But then the decline began. Watching the platform struggle, I couldn’t help but reflect: what made it great? What went wrong? And what could the future look like if we did things differently? The Spark of Chatter As a content creator, I understood the needs of both creators and users. I knew what excited people, what kept them engaged, and what made them leave. Clubhouse had tapped into something special, but it had missed the mark on scalability and sustainability. By September 2023, I couldn’t stop thinking about the potential for something new—something that brought back the magic of real-time interaction but made it scalable, engaging, and sticky. And so, I set out to build Chatter Social. But I wasn’t a tech founder. I didn’t have a background in software development or a network of Silicon Valley insiders. What I did have was determination and the belief that if I could bring the right people together, we could build something extraordinary. Building the Team The journey to build Chatter started with assembling a team. Through my network from my days on Clubhouse, I found Samir, my first CTO. He believed in the vision and was instrumental in getting the project off the ground. Shortly after, I connected with Tyler, our Head of Design, whose creativity brought life to our ideas. A developer joined us soon after, and we were off to the races. By the end of 2023, Samir had to step away due to other commitments, and we promoted the developer to CTO. At the same time, I brought on Banko, a Sony music executive, as our CMO. Banko’s connections led to one of our biggest early wins: landing Davido, a global superstar, as an owner-ambassador. To this day, I still marvel at the fact that Davido believed in our vision when all we had were Tyler’s Figma designs. From Dream to Reality Early 2024 was a whirlwind. We hired Yurii and Vasyl, two developers from Ukraine who brought incredible skill and dedication to the team. Vasyl, in particular, stood out as a leader and has since earned an equity position in the company. But despite these wins, we were facing growing pains. Our new CTO struggled to meet deadlines, and as a result, I found myself constantly pushing back the launch date. What started as a January release turned into February, then March, then April, then May. By then, people on Twitter Spaces—where I had been hyping up the platform—started doubting if we even had a product. Launch and Lessons June 1, 2024, marked a turning point. It was the day my son Noah was born and the day we launched Chatter in private beta. We started with just 40 users, but by the end of the month, we had grown to 1,000. The engagement was unbelievable. Users loved it, even though we had launched with just one feature: live rooms. This represented less than 20% of what we had planned, but it was enough to show that we were onto something big. In July, we launched our public beta on the App Store as an invite-only platform. Within 48 hours, Chatter ranked as a top 30 social app in over 30 countries. But our invite system throttled access, and most users couldn’t get in. While engagement metrics soared for those inside, our AWS costs exploded. In August, our AWS bill hit $10,000. By September, it had climbed to $15,000, and we were drowning in bugs and glitches. The breaking point came when our CTO became unresponsive, often disappearing during critical moments. Users were dropping off, frustrated by the issues, developers were confused and the team was also growing increasingly frustrated, I made the tough decision to let him go. A New Beginning Enter Horane, a long-time user of Chatter who had been with us since private beta. He was the first to discover some of the most innovative use cases for the platform and had a deep passion for its potential. After meeting him in person at a Chatter event, I knew he was the right person to step into the CTO role. When Horane took over, we discovered just how bad the situation was. Key areas of the codebase were locked, and there were no separate environments for development and production. Every fix seemed to break something else. But through sheer determination and countless 18-hour days, Horane stabilized the platform. Today, Chatter is far from perfect, but it’s stable. The bugs that plagued us have been reduced to moderate issues, and our core users—those who stuck with us through the chaos—are still engaged on the platform. Looking Ahead: Chatter V2 While the platform is stable now, we’ve shifted our focus to Chatter V2. This is where the magic really begins. V2 isn’t just an improvement; it’s a complete reimagining of the platform. It includes all the features we couldn’t release in V1 because we were too busy putting out fires. Imagine this: Chatter V1, with only one live feature, was incredibly sticky. Now think about what happens when we release a fully loaded platform with all the innovative features we’ve been working on behind the scenes. The possibilities are endless. V2 is slated to hit TestFlight by the end of December, with a public release in January 2025. And this time, we’re ready—not just with the product but with the lessons we’ve learned. The Hard Lessons This journey has taught me more than I ever thought possible: 1) Your Team is Everything: The right people can make or break your vision. Finding people who believe in your mission is just as important as finding people with the right skills. 2) Adaptability is Key: As a non-technical founder, I had to learn about development, DevOps, and product management on the fly. Challenges will push you to grow, whether you’re ready or not. 3) Trust the Process: Every setback, every delay, every bug—it all taught us something. Without those lessons, we wouldn’t be building the incredible V2 product we are today. 4) Resilience is Non-Negotiable: From technical disasters to predatory investors who tried to exploit my desperation, I’ve had to fight for this vision every step of the way. What’s Next December is shaping up to be an exciting month. We have some amazing events planned on the platform to close out the year, bringing our core community together as we prepare for the V2 launch. When V2 drops, it will mark a new era for Chatter. This isn’t just a social audio platform or a social audiovisual platform. Chatter is all about interactive experiences—making social media social again in ways that are truly unique. The public launch is slated for February 2025, and for the first time, we’ll have the marketing dollars to tell the world about Chatter. Our core community has been our biggest cheerleaders, and I can’t wait to see how the world reacts when they experience what we’ve built. Final Thoughts This has been the hardest year of my life, but also the most rewarding. To other founders, or anyone thinking about starting a company: know this—it will test you in ways you can’t imagine. You’ll face betrayal, doubt, and moments where you feel like giving up. But if you believe in your vision and refuse to quit, you’ll find a way forward. Thank you to everyone who has supported me, my team, and Chatter. We’re just getting started. Let’s talk about it. 🚀 If this story inspired you, please like and share it so others can learn from my experiences. The journey is far from over, but I’m more excited than ever for what’s to come.

From Creator to Founder: The Rollercoaster Journey of Building Chatter Social Man, what a journey it’s been so far. Four years ago, I was just another creator, spending late nights on Clubhouse during the height of the pandemic. Like so many others, I was searching for connection, for community, for something meaningful. But what I found there wasn’t just connection—it was purpose. Alongside my brother, Jonathan Bing, we built a nightly show that reached over 5 million people. Imagine that: 5 million lives touched by conversations that felt real and unfiltered, all on a platform that at its peak had 10 million monthly active users. Clubhouse was magic. But then the decline began. Watching the platform struggle, I couldn’t help but reflect: what made it great? What went wrong? And what could the future look like if we did things differently? The Spark of Chatter As a content creator, I understood the needs of both creators and users. I knew what excited people, what kept them engaged, and what made them leave. Clubhouse had tapped into something special, but it had missed the mark on scalability and sustainability. By September 2023, I couldn’t stop thinking about the potential for something new—something that brought back the magic of real-time interaction but made it scalable, engaging, and sticky. And so, I set out to build Chatter Social. But I wasn’t a tech founder. I didn’t have a background in software development or a network of Silicon Valley insiders. What I did have was determination and the belief that if I could bring the right people together, we could build something extraordinary. Building the Team The journey to build Chatter started with assembling a team. Through my network from my days on Clubhouse, I found Samir, my first CTO. He believed in the vision and was instrumental in getting the project off the ground. Shortly after, I connected with Tyler, our Head of Design, whose creativity brought life to our ideas. A developer joined us soon after, and we were off to the races. By the end of 2023, Samir had to step away due to other commitments, and we promoted the developer to CTO. At the same time, I brought on Banko, a Sony music executive, as our CMO. Banko’s connections led to one of our biggest early wins: landing Davido, a global superstar, as an owner-ambassador. To this day, I still marvel at the fact that Davido believed in our vision when all we had were Tyler’s Figma designs. From Dream to Reality Early 2024 was a whirlwind. We hired Yurii and Vasyl, two developers from Ukraine who brought incredible skill and dedication to the team. Vasyl, in particular, stood out as a leader and has since earned an equity position in the company. But despite these wins, we were facing growing pains. Our new CTO struggled to meet deadlines, and as a result, I found myself constantly pushing back the launch date. What started as a January release turned into February, then March, then April, then May. By then, people on Twitter Spaces—where I had been hyping up the platform—started doubting if we even had a product. Launch and Lessons June 1, 2024, marked a turning point. It was the day my son Noah was born and the day we launched Chatter in private beta. We started with just 40 users, but by the end of the month, we had grown to 1,000. The engagement was unbelievable. Users loved it, even though we had launched with just one feature: live rooms. This represented less than 20% of what we had planned, but it was enough to show that we were onto something big. In July, we launched our public beta on the App Store as an invite-only platform. Within 48 hours, Chatter ranked as a top 30 social app in over 30 countries. But our invite system throttled access, and most users couldn’t get in. While engagement metrics soared for those inside, our AWS costs exploded. In August, our AWS bill hit $10,000. By September, it had climbed to $15,000, and we were drowning in bugs and glitches. The breaking point came when our CTO became unresponsive, often disappearing during critical moments. Users were dropping off, frustrated by the issues, developers were confused and the team was also growing increasingly frustrated, I made the tough decision to let him go. A New Beginning Enter Horane, a long-time user of Chatter who had been with us since private beta. He was the first to discover some of the most innovative use cases for the platform and had a deep passion for its potential. After meeting him in person at a Chatter event, I knew he was the right person to step into the CTO role. When Horane took over, we discovered just how bad the situation was. Key areas of the codebase were locked, and there were no separate environments for development and production. Every fix seemed to break something else. But through sheer determination and countless 18-hour days, Horane stabilized the platform. Today, Chatter is far from perfect, but it’s stable. The bugs that plagued us have been reduced to moderate issues, and our core users—those who stuck with us through the chaos—are still engaged on the platform. Looking Ahead: Chatter V2 While the platform is stable now, we’ve shifted our focus to Chatter V2. This is where the magic really begins. V2 isn’t just an improvement; it’s a complete reimagining of the platform. It includes all the features we couldn’t release in V1 because we were too busy putting out fires. Imagine this: Chatter V1, with only one live feature, was incredibly sticky. Now think about what happens when we release a fully loaded platform with all the innovative features we’ve been working on behind the scenes. The possibilities are endless. V2 is slated to hit TestFlight by the end of December, with a public release in January 2025. And this time, we’re ready—not just with the product but with the lessons we’ve learned. The Hard Lessons This journey has taught me more than I ever thought possible: 1) Your Team is Everything: The right people can make or break your vision. Finding people who believe in your mission is just as important as finding people with the right skills. 2) Adaptability is Key: As a non-technical founder, I had to learn about development, DevOps, and product management on the fly. Challenges will push you to grow, whether you’re ready or not. 3) Trust the Process: Every setback, every delay, every bug—it all taught us something. Without those lessons, we wouldn’t be building the incredible V2 product we are today. 4) Resilience is Non-Negotiable: From technical disasters to predatory investors who tried to exploit my desperation, I’ve had to fight for this vision every step of the way. What’s Next December is shaping up to be an exciting month. We have some amazing events planned on the platform to close out the year, bringing our core community together as we prepare for the V2 launch. When V2 drops, it will mark a new era for Chatter. This isn’t just a social audio platform or a social audiovisual platform. Chatter is all about interactive experiences—making social media social again in ways that are truly unique. The public launch is slated for February 2025, and for the first time, we’ll have the marketing dollars to tell the world about Chatter. Our core community has been our biggest cheerleaders, and I can’t wait to see how the world reacts when they experience what we’ve built. Final Thoughts This has been the hardest year of my life, but also the most rewarding. To other founders, or anyone thinking about starting a company: know this—it will test you in ways you can’t imagine. You’ll face betrayal, doubt, and moments where you feel like giving up. But if you believe in your vision and refuse to quit, you’ll find a way forward. Thank you to everyone who has supported me, my team, and Chatter. We’re just getting started. Let’s talk about it. 🚀 If this story inspired you, please like and share it so others can learn from my experiences. The journey is far from over, but I’m more excited than ever for what’s to come.

Nelson Epega

43,371 次观看 • 1 年前

Pylon's 𝗺𝗼𝘀𝘁 𝗵𝗮𝘁𝗲𝗱 𝗳𝗲𝗮𝘁𝘂𝗿𝗲 is our Analytics. That ends today. We've completely rebuilt our Analytics from scratch. Here's what we tried, what we screwed up, and what's coming. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟭, The Basics (Nov 2023) Our first attempt at analytics was quite loved by customers. At the time our customers were mostly small startups with simple needs. We built an out-of-the-box set of dashboards that covered the common use cases of support analytics (SLA-tracking, CSAT, TTFR, TTR, basic filtering...). As we moved upmarket... 1/ Everyone was requesting custom metrics 2/ Queries were becoming inefficient and slow We needed an upgrade. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟮, Advanced Reporting (June 2024) We knew custom reporting was going to be blackhole of work that long-term led to fully customer-customizable dashboards. We had four choices: 1/ Do nothing for now 2/ Do custom work per customer 3/ Build full custom reporting in-house 4/ Use an embeddable analytics vendor At the time Pylon was under 10 people total and we had no capacity to do the frontend work so we chose Option 4 (use a vendor). This was the first time we chose to not build a core feature like this in-house as we ultimately want full control of the end-user experience. We built out the new reporting with the chosen vendor over ~3 weeks. On the surface the new reporting looked really good (not visually, but in terms of functionality). You could add custom charts of any type, create custom formulas, label the Y and X axis, and effectively build most of what you would want. It was really great for demos. But in practice it was incredibly hard to use, lacked core capabilities (like the ability to filter off of dynamic custom fields), and visually looked not stylized to the rest of the product. We started to discover some of these issues during the implementation, but it still felt like there was more upside than downside so we released it. Feedback was not great but we hoped our vendor would fix changes quickly. Unfortunately they weren't fast enough and we lost confidence that they would be a good long-term solution. As a stop-gap we also built out a data warehouse integration so customers could export their data back to Snowflake or BigQuery to use with their own BI tools. Finally, a few months ago the vendor told us they were being acquired. That was the final straw. We needed to move off ASAP. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟯, New Reporting (Today) Today's release is back to being built entirely in-house. It's been rolled out in beta to all customers with an option to flip back to old analytics until we plug some custom reporting gaps. This time we have the capacity to do it right between Wendy (prev product design at Amplitude), Matt, and Tom. We've managed to greatly improve: 1/ Desired filter options (custom field support) 2/ Performance 3/ Setup UX 4/ Style (looks native) Early feedback has been really positive so far and as we bring it out of beta we're thinking about how to make the best natively-offered reporting of any support platform. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟰 (What's coming soon) To get to first-class reporting, we need to study not only our learnings, but also what the incumbents have screwed up as well. Funny enough, Zendesk's analytics have similar complaints to our v2, and for the exact same reason as we did: they integrated an external tool. In 2015 they bought a company called BIME Analytics which they became Zendesk Explore. The complaints they have to this day are similar to our v2: 1/ Steep learning curve 2/ Advanced, yet still not enough flexibility 3/ Random feature gaps 4/ Data accuracy and reliability concerns 5/ Performance issues 6/ Complicated UX v4 will follow three core principals: Offer a simple default setup. We want to continue being startup friendly and we'll feature gate custom reporting and data exports by tier in the product. Offer maximal configuration, with AI-assisted setup. As we go upmarket, customers will want to Explore (pun intended) data in every single direction. We need to allow them to do that. For those more complicated use cases we think AI will be the Ultimate (also pun intended) way to reduce setup friction. Build it all in-house. Although using a 3rd party embedded analytics provider didn't work for us, we don't think that is the case for everyone. It's just in customer support, reporting is REALLY important. They are probably some of the highest-complexity reporting of most SaaS vendors (maybe second to marketing products). So... we have to do it right. And since this is end-user facing, we have to own every detail of it. If you got this far, thank you for reading. See our new Analytics at

Pylon's 𝗺𝗼𝘀𝘁 𝗵𝗮𝘁𝗲𝗱 𝗳𝗲𝗮𝘁𝘂𝗿𝗲 is our Analytics. That ends today. We've completely rebuilt our Analytics from scratch. Here's what we tried, what we screwed up, and what's coming. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟭, The Basics (Nov 2023) Our first attempt at analytics was quite loved by customers. At the time our customers were mostly small startups with simple needs. We built an out-of-the-box set of dashboards that covered the common use cases of support analytics (SLA-tracking, CSAT, TTFR, TTR, basic filtering...). As we moved upmarket... 1/ Everyone was requesting custom metrics 2/ Queries were becoming inefficient and slow We needed an upgrade. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟮, Advanced Reporting (June 2024) We knew custom reporting was going to be blackhole of work that long-term led to fully customer-customizable dashboards. We had four choices: 1/ Do nothing for now 2/ Do custom work per customer 3/ Build full custom reporting in-house 4/ Use an embeddable analytics vendor At the time Pylon was under 10 people total and we had no capacity to do the frontend work so we chose Option 4 (use a vendor). This was the first time we chose to not build a core feature like this in-house as we ultimately want full control of the end-user experience. We built out the new reporting with the chosen vendor over ~3 weeks. On the surface the new reporting looked really good (not visually, but in terms of functionality). You could add custom charts of any type, create custom formulas, label the Y and X axis, and effectively build most of what you would want. It was really great for demos. But in practice it was incredibly hard to use, lacked core capabilities (like the ability to filter off of dynamic custom fields), and visually looked not stylized to the rest of the product. We started to discover some of these issues during the implementation, but it still felt like there was more upside than downside so we released it. Feedback was not great but we hoped our vendor would fix changes quickly. Unfortunately they weren't fast enough and we lost confidence that they would be a good long-term solution. As a stop-gap we also built out a data warehouse integration so customers could export their data back to Snowflake or BigQuery to use with their own BI tools. Finally, a few months ago the vendor told us they were being acquired. That was the final straw. We needed to move off ASAP. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟯, New Reporting (Today) Today's release is back to being built entirely in-house. It's been rolled out in beta to all customers with an option to flip back to old analytics until we plug some custom reporting gaps. This time we have the capacity to do it right between Wendy (prev product design at Amplitude), Matt, and Tom. We've managed to greatly improve: 1/ Desired filter options (custom field support) 2/ Performance 3/ Setup UX 4/ Style (looks native) Early feedback has been really positive so far and as we bring it out of beta we're thinking about how to make the best natively-offered reporting of any support platform. 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝟰 (What's coming soon) To get to first-class reporting, we need to study not only our learnings, but also what the incumbents have screwed up as well. Funny enough, Zendesk's analytics have similar complaints to our v2, and for the exact same reason as we did: they integrated an external tool. In 2015 they bought a company called BIME Analytics which they became Zendesk Explore. The complaints they have to this day are similar to our v2: 1/ Steep learning curve 2/ Advanced, yet still not enough flexibility 3/ Random feature gaps 4/ Data accuracy and reliability concerns 5/ Performance issues 6/ Complicated UX v4 will follow three core principals: Offer a simple default setup. We want to continue being startup friendly and we'll feature gate custom reporting and data exports by tier in the product. Offer maximal configuration, with AI-assisted setup. As we go upmarket, customers will want to Explore (pun intended) data in every single direction. We need to allow them to do that. For those more complicated use cases we think AI will be the Ultimate (also pun intended) way to reduce setup friction. Build it all in-house. Although using a 3rd party embedded analytics provider didn't work for us, we don't think that is the case for everyone. It's just in customer support, reporting is REALLY important. They are probably some of the highest-complexity reporting of most SaaS vendors (maybe second to marketing products). So... we have to do it right. And since this is end-user facing, we have to own every detail of it. If you got this far, thank you for reading. See our new Analytics at

Marty Kausas

115,123 次观看 • 1 年前

OPERATION INDIGO SKYFALL (SKYNET) (Update 6/11/25) While Operation Indigo Skyfall is a program by the Anunnaki specifically to turn the global atmosphere into an electrolyte solution 'motherboard' that powers Skynet that's already fully online as of May 2020, it was preceded by a decades-long 3-pronged assault against the pineal glands of humankind. The thrust of all three programs combined are all about disconnecting people from their higher selves and to vastly reduce their intellect quotient to make them easily controlled, prior to the launch of Skynet. Understand the intense investment that has been funneled into destroying the very beings that paid the taxes (loosh) to fund these programs is more than the gross domestic products of multiple countries combined. At minimum, trillions $ pr year in 2025 dollars, for more than 80 years. If you’ve ever seen chemtrails in your skies, you’ve seen one of these programs in a bold, in-your-face, broad-daylight fashion. THREE-PRONGED ATTACK PREPARING FOR SKYNET #1 FLUORIDE = WATER CONTAMINATION In its first installation of what would ultimately become a nation-wide invasion of every metropolis, city, town and mud puddle in the US, fluoride was added to public water in Grand Rapids in 1945 to ‘fight tooth decay’. Problem is, fluoride is actually nuclear waste used as rat poison. It is a known neurotoxin more harmful than lead & likened to the toxicity of arsenic for more than 100 years, causing brain damage, spinal cord & nerve networks destruction and has never been shown to diminish the onset of tooth decay. Which every dentist in the country would have banded together to put a stop to back then if it really did that. So who decided to put THAT into your drinking water exactly? Andrew Mellon, 33rd degree Scottish Wrong Freem@son. Shocking Dangers of Fluoride: cancerwisdom dot net; "There has never been a double-blind, randomized clinical trial for fluoridation's effectiveness." [In reality, fluoride itself has been shown to damage teeth in a totally different way than we get through eating, known as fluorosis. Also in reality, all tooth decay is 100% of the time, parasites, not ‘rot’. They say sugar rots teeth; which is a lie. Sugar is a primary food of parasites, along with heavy metals. When you eat sugars then fail to immediately brush & floss, the parasites already in your body (and there are at least millions) rush to the crevices of your palate then wind up burrowing into your teeth’s (actual crystals) valance bands, further destroying them each time the parasites defecate. Anytime you eat anything sugar or sweetened, ALWAYS mix it with an antiparasitic & immediately brush, or rinse your mouth with hydrogen peroxide afterward, never with mouthwash, which is also poison. I will be covering this extensively soon in my new article: 👉PARASITES] As explained in greater detail below in the whistleblower video, fluoride was used by the N@TZIs (Ashke-N@TZI Crypto J3ws that took over Germany then lead that country into WW2, posing as actual Germans, which they absolutely were not. See my article: 👉GERMANY WON WW2 for more) in concentration camps in the 1930s-40s to make prisoners docile. How does that work? Fluoride accumulates at, and attacks, the pineal gland of your body. This is the ‘antenna’ connection to your higher self that generates your reality. The pineal gland then fights back the fluoride toxin, moving it just outside of its ‘theater of the mind’ and surrounds it to seal it off from attacking. This builds up a ‘calcification’ around the pineal gland, which acts as an insulator blocking your signal to the Primal Sound & Light Fields of the Deity Planes where your higher self has always been positioned, inside what is known in human terms as the Unified Field. [For more on the key function of the pineal gland, see my article: 👉 HOW THE HOLOGRAPHIC SIMULATION WORKS] #2 OPERATION INDIGO SKYFALL = AIR CONTAMINATION (not to be confused with Operation Indigo SkyFOLD which is just another red herring distraction to overcome the dissemination of the truth of this existential threat to all mankind.) Beginning as far back as 1972, Operation Indigo Skyfall chemtrail program is one of the most brutally-compartmentalized & ferociously classified operations of all-time. So secret, the tens of thousands of chemtrail jets across the world don’t even land on the continental United States, but refresh their death dust exclusively on private islands, outside of enforced laws. The first part of this program where strontium, barium & aluminum microparticles are being dumped onto all of the lands of earth that kill all life forms, including the trees and forests, is the obvious portion of your extermination, and even that is only a fraction of the story being applied to depopulate the plane(t) from reportedly 8B people (this is a lie, it was less than 5B in 2019) to just 500,000. The heavy metals being reported by laboratories are merely assaying the minerals themselves, not looking deeper into what’s really going on. In reality, these are the minerals used in the manufacture of nanites that are often no larger than just 4 molecules in size. Each one programmed on a quantum level to interconnect with one another, forming larger and larger computer nodes, just like the massive white ‘antennas’ being removed from millions of clot-shot victims around the world since the final push to bring this program to completion began with the ‘Covid’ attempted genocide using mRNA bioweapons. Prior to the huge blood-clots (invasive man-made prions to take over the full functioning of the body) now being retrieved from cadavers and patients suffering this biological invasion, chemtrail direct effects were known as Morgellons Disease where tiny wire-like structures were coming out of people’s skin. However, the ‘disease’ gaslighting was exposed when laboratories began placing them under powerful microscopes and finding they were individual nanotbots ‘holding hands’ to make up the ‘wires’ that were now growing inside people’s bodies. Once zoomed in using scanning electron-microscopy to each one, they not only found the NAME of the companies behind each model, but even serial numbers printed in quantum-dots on their structures. You might recognize this one that clearly says NASA on its surface. The program of chemtrail nanites is to infiltrate the immune system of the human body and generate immunodeficiency so you are unable to fight off diseases and viruses. But there is another, even more primary mission for those molecular-sized robots; to collect at your pineal gland causing calcification and thus not only disrupting your entire system, but placing a crystalline ‘shell’ around it to cut off your ‘spiritual’ access to your higher self. Think of it like scrambling the signal of your cellphone if you had a direct line to ‘god’. As an aside, Cody Snodres, the independent contractor for the C 👁️A of 20 years & hero whistleblower that broke the story of Operation Indigo Skyfall in 2018 in the video below, mentions pathogens being added to chemtrails. These have been solidly identified by labs as recently as a few months ago in late 2024 & again in Jan of 2025 when entire cities were enveloped by huge, totally dry, fog banks of particulates dropped from the skies that caused countless deaths from pneumonia. Referred to by people as ‘Dragon Fog’, the pathogens are actually Serratia Marcescens bacteria (another word for parasites, pathogens, microorganisms & viruses). While I’m sure there have been other parasites added to chemtrails that attack the immune systems of humans and animals other than Serratia Marcescens, this particular species has been used by mil operations now as an ideal biological weapon and regularly upgraded now for many decades. Stay with me, I’m getting to Skynet, but first I have to show you some of the foundational elements of how the invader races have reached this point where humans would have become so mentally effected by this unthinkably massive-scale attack on your pineal gland, they would become psychologically and emotionally unable to fight back, even if they ever did look up in the sky and cognitively register the fact that contrails (endothermic sublimation or ‘fog’) emitted by the compressed-air turbines of jets dissipate in about 8-20 seconds, not hang in the air for hours and hours. [And for those now wondering what I mean about jets using compressed air as forward thrust in commercial passenger jets, that’s a story that is going to surely hack you off when you find out that passenger jets have always been levitation/time crafts since they were introduced to the public in the 1940s. They don’t run on fuel, but on high-altitude atmospheric neutrino-to-ion conversion harvesting (also known as ‘Secondary Emissions’ as well as ‘Neutrino Events’). So every ‘fuel increase’ markup for local and international flights has always been absolutely made-up, since what they run on is eternally-free energy. See my article for more: 👉JET FUEL HOAX] #3 M0NSANT0 = FOOD CONTAMINATION This company does *not make better-performing corn & veggies: it is a bioweapons company. John Francis Queeny, a Freem@son, that founded this genocidal operation in 1901 produces 90% of the world’s genetically-altered seeds & is responsible for developing Agent Orange, a defoliant used during the Vietnam War, containing a highly toxic chemical known as dioxin that caused permanent health issues for thousands of war veterans. Later it used this same type of murderous chemical in Roundup to k!ll weeds around your home, coating your world with glyphosate that changes the sex in frogs and turns them ghey and sterile. Guess what other life forms it changes the sex in and makes them sterile? Ever witnessed the most celebrated triathlete of the 20th century suddenly pop up and claim he was now a ‘woman’? How about watching as our youngest generation enters the workforce, most of whom don’t even know what sex they are? That’s your M0nsanto working hard to ensure the human race is eradicated from the all-queer-all-the-time world Freem@sons envision as their true utopia in the “500m sustainable population” as etched into granite on the Georgia Guidestones. A number mirrored by United Nation’s Agenda 2030 to be achieved by the year 2050. Their goal is literally 👉your depopulation and those that are left, will be 100% ghey. Diddly Parties nightly! GMO foods that are grown using M0nsanto’s “Roundup Ready” fertilizer that is made with glyphosate toxins are absorbed by the gut and then travel directly to the pineal gland. This is the Anunnaki’s ‘Trifecta’ attack on your most precious organ of your body. The very organ that dictates all the parameters of your reality held within your Krystal Seed Atom Keylon you enter into manifestation with, commonly referred to as your ‘soul’. In more accurate terms, your Krystal Seed Atom is like a Bluetooth module that tethers your awareness from your higher self in the Primal Sound and Light Fields of the Deity Planes, to your physical avatar here on the ground through the wireless ‘pale silver cord’. The Krystal Seed Atom is located in the middle of your pineal gland. [For more on the Krystal Seed Atom, see my articles: 👉THE HISTORY OF THE CHIMERA, & 👉THE KEYS TO HEAVEN] As Cody points out in the video, this is not a matter of hitting your pineal gland with three doses of toxins, but because of how these three chemicals of fluoride, nano aluminum & glyphosate interact with each other, creates synergy, or a dynamic magnification of the toxicity effect by a factor of 125x greater than any one individual dose would achieve. This makes the Trifecta assault astronomically devastating to your connection to the pale silver cord and your wireless connection to the ‘real’ you that’s running your avatar in the deity planes. Sort of like taking your 4 yr old to the mall and just letting them go on their own. Now, with your virtually disabled pineal gland reality-casting component out of the way, enter the true teeth behind Operation Indigo Skyfall; Skynet. SKYNET This is a subject I won’t be able to offer much tangible, solid evidence on, as it goes deeply into quantum physics. All of which terms describing each step in the chain to achieve ‘if this, then that’, are shielded from public understanding by design. The power of computers is vastly beyond what the human mind has been given the ability to process, also by design. [As I’ve covered before, the Chimera brain you work with now, since the total body-invasion of the garden of E-Dan drama, is fitted with breaker switches that are designed to keep certain subjects hidden from your reality-view. When exposed to any of these, a switch is thrown at the base of the brain within the totally counterfeit ‘reptilian brain’ that introduces feral, animalistic type of wavelengths into your thought processes. The switch then disengages your sentient thoughts, shutting off either temporarily, or permanently, your processor (brain). Simply put: if you see a creature you’re not supposed to, or other ‘proprietary’ mechanisms of the invader races (which are in fact all around you every minute of everyday) that doesn’t fit with the ‘Mayberry RFD’ Chimera Reality simulation overlay, or if you experience too much trauma, you will simply black out, delete that memory when you wake up, or in extreme cases, pass away from fright. The realm of quantum computing will have the same effect on humans as well. You might learn all about the subject, but secretly in the background your memories will strangely be deleted next time you come back to it, unless your cells vibrate at a higher resonance than 7.83Hz. [For more on the inorganic organs now in our bodies, see my article: 👉HUMAN ALIEN IMPLANTS] Nonetheless, I can simplify the thrust of Skynet for you in broad terms here. Just understand that Skynet was explained to me in person by the keeper. I didn’t make Skynet up on my own, I wasn’t prompted by the Skynet mentioned in the documentary series The Terminator, and I certainly wasn’t prepared to learn there could be something as all-powerful reigning over our world. Chemtrails, besides dropping immune-system pathogens on you, cutting off your connection to your higher self through nano aluminum particles, contains other metals (nanites) that act together like salts in a body of water, turning the sky itself (also water, just very thinned down) into an electrolyte solution, meaning it can now conduct signals, just like a motherboard on a computer. The hard drive and RAM are already there in the form of deuterium microcrystals, absolutely saturating our skies at all times. Each crystal can be used for different applications, and many of them connected together through lensing (similar to network covalent bonding them together) can be combined to do heavy tasks, such as create hurricanes, floods, gale-force winds, everything you would ascribe to mother nature. But more than just that, Skynet is a ‘sentient quantum computer’ as explained to me, that can identify every person on earth instantly anywhere they are, because it is quantum-entangled to each person’s own unique DNA resonant frequency. This gives Skynet access to not only record every word you say, but every thought you think. This is done through Bloch Chain (Bloch Sphere entanglement technology that civilians call ‘blockchain’) through using each person's blood samples from the bottom of their Long Form Certificate of Live Birth taken at the hospital, and further from 81.3% of the world population who took the convid tests that were also secretly the actual jab itself, in addition to genetic harvesting. Genealogy companies like 23andMe also provide genetic materials to Skynet to make it possible to not only track you, but 'turn you off' if you're from a bloodline the highest-up ETs don't want here. Further, its able to simply 'shut off' any part of your body, taking over complete control like an RC car, or, simply turn it off as mentioned a moment ago, as in unalived. And do so instantly no matter where they stand on or in earth. Since you are already a radio-controlled bioelectronic device, any cell in your body can be turned into anything, including c@ncer, or any disease you can name. It can also be turned into poison itself. [For a small addition to this topic, see my article: 👉SKYNET] NAME OF THE OPERATION Cody summarizes the name of Operation Indigo Skyfall as having come from the fact that all of the chemical effects it produces in the human body are focused to the pineal gland, and, in the energy centers of the 7 main chakras (these are toroidal energy generators along the spine and skeletal structure) that cast off differing colors of light as seen through photometers or electromagnetic frequency analyzers that are used to detect biophotons, the Third Eye chakra emitted by the pineal gland is factually Indigo in color. So that’s what inspired this name of the operation. However, I would like to submit a different theory that links to the human Third Eye chakra, but actually originates from a different target: Indigos themselves. There are 500,000 ‘b00ts on the ground’ Indigos that have been assisting humans during their time of captivity now for hundreds of millions of years. You have called us witches & warlocks in the past, medicine men/women, Sufis, the Whirling Dervish, Indigos, Starseeds, Rainbow Children and many others, including Djedi Knights in more ancient times. They are actually known as the Guardian Alliance of the Emerald Covenant, peace-keepers of the ‘Turaneusiam’ Human Elohim Project. Indigos come into earth’s realm mind-wiped and alone, just as humans do. All they bring with them are slightly higher clair abilities they can use to fight an invisible war protecting the developing avatars from as much torture as they would otherwise experience. There is no group alive the invader races are more concerned about than Indigos, as if unified, there is no force on this plane that could stop them, and the invaders know it. What they fear is our higher frequency that gives us access to ‘cellular memory’ that tells us we’re ‘on mission’ and the instinct of how to serve our roles. That is why Indigos are hunted down since before they are even born, by tracking their frequency, which is 250x higher than that of the Human Elohim. We are harvested for gov programs beginning at the time of birth & given to high ranking gov and Freem@son officials to raise and torture through MK-Ultra abuse, given friends, lovers & mates who are secretly handlers that torture us even more to keep us in line, and in many cases are abducted and placed into stasis in chambers such as at Project Stargate inside Cheyenne Mtn (N0RAD) as mentioned recently by the AI hybrid Agent Mockingbird stated from above-top-secret records there are tens of thousands of our ‘primary bodies’ being held there, sometimes then cloned as physical worker slaves, & sometimes our awarenesses are simply uploaded as ‘nodes’ into computer systems. My primary body is there right now in fact, and has been since the 1970s. I believe this is the genesis of the name Operation Indigo Skyfall, as we are their biggest threat. And since the 7.83Hz Hypnosis Program doesn’t work on us to render us totally disconnected from our higher selves like it does on humans, to me this makes more logical sense. You can decide that on your own. [For more on this subject, see my article: 👉7.83Hz HUMAN HYPNOSIS] The apocalypse we are in now is the final battle on Tara earth prior to the separation, so absolute, total control over the life force is critical to the Anunnaki to maximize the number of signature spirit essences who will be going with them to their new prison host in the Weasadrax time matrix. [For more on the separation and destinations, see my articles: 👉THE SEPARATION & also 👉DESTINATIONS AFTER THE SEPARATION] See Video: Operation Indigo Skyfall - Cody Snodgres👇 - On X, to search for my articles, simply type in the name of the piece, enter one space, then from: plus my username in parenthesis such as shown here: CASTING THE APOCALYPSE (from:iontecs_pemf) Off-site, you can look up any of my writings through this link below for my other more than 120 recent articles and many thousands of comments on X, regularly updated thanks to Justin This message will only be seen by your eyes if not shared, and if you want to reference this article again later, you will need to cut and paste it in your own notes off line, as it will surely be erased. This is the most accurate translation of these events I am aware of at this time.

W.R. Schock, QBD

54,362 次观看 • 1 年前

An interview by VERY DARK AND CORRUPT Wall Street Journal aired today [1] WSJ's terrible "journalists" (and I use that term lightly) made many false statements about Sarepta's worthless, dangerous drug and Vinay Prasad's firing [1,2] I explain how the FDA sausage is made in excruciating detail Buckle up To get readers up to speed -> In June, corrupt pharma company Sarepta Therapeutics paid $40,000 to lobbying group Michael Best Strategies (MBS) to deal with a problem [3] -> MBS had recently hired Chris LaCivita, who had close connections with "MAGA" influencer Laura Loomer [4] -> With stock down 88%, Sarepta needed to sell their very bad, very dangerous drug or the company would go bankrupt [5] -> After several deaths from the drug this year, FDA official Vinay Prasad said "no way" and kicked the drug to the curb [2,6] -> Sarepta panicked and paid MBS (we believe) to deal with Prasad [3,4] -> If this story is right, LaCivita recruited Laura Loomer to take down Prasad [4,7] -> Loomer said she was defending Trump, but she was lying [7] -> She was defending taxpayer-funded payouts to a worthless, corrupt company [7] -> Laura Loomer so brave A history of bad drugs and regulatory failure -> This is one of the worst pharma scandals in American history and corrupt mainstream media isn't covering it -> Sarepta has a very long, troubled history [8] -> For more than a decade, every major Sarepta FDA drug approval has required INTENSE political intervention [8,9] -> Scientists at FDA have been repeatedly overruled [8,9] -> Many scientists have resigned, very publicly, over these POLITICAL decisions, some writing scathing public criticisms of these terrible decisions [10,11] -> The most recent resignation by Vinay Prasad is not something new; it follows in a long tradition [2,10] -> In fact, standards have dramatically deteriorated since the first controversies about the company's drugs in the 2010s [8,9] -> Prasad was trying to hold the line in the face of rapidly deteriorating standards at the agency [2,6] -> For that, pharma launched a coup--a literal coup of a drug regulator [4,6] -> This is unprecedented -> Banana republic sht, unbelievably corrupt 2016: first Sarepta drug approval and the "highly unusual" decision -> The first Sarepta drug approved by FDA was called Exondys 51 [8] -> This drug was for patients with mutations in dystrophin, a muscle protein [8] -> This is a debilitating and fatal disease affecting children [8] -> Exondys 51 increased dystrophin by 0.2% of normal levels [8,12] -> Unsurprisingly, there was no good evidence the drug worked [8,12] -> Why would it? It increases the protein from zero to 1/500th of normal levels -> One reviewer wrote: "I can find no precedent of an accelerated approval for a marketing application where the effect size on the surrogate endpoint is as small as 0.3%." [12] -> The study submitted by the company included no proper control group [12] -> The techniques used were so bad not even a first-year PhD student would do a study that way -> This the level of work you would expect from a mediocre undergraduate with no guidance -> It's almost like it was so bad on purpose -> (Narrator: it was on purpose) -> Nerd time: -> One reviewer wrote: "The Western blots submitted by the applicant for Study 201 were oversaturated, unreliable, and uninterpretable." [12] -> Another wrote: "Because CDER also determined that the conditions under which the original IHC analysis was performed were inadequate, including that the reader was not masked to sequence and time, the Center requested a re-reading of the stored images by three masked pathologists under different conditions. The IHC results from the reread were not nearly as favorable, as compared to the initial IHC results reported by Sarepta." [12] -> "The lack of concordance between the IHC and the Western Blot results is 'striking'" [12] -> "Study 201/202 had fundamental flaws, including baseline biopsies from external controls who could differ in unknown ways from study subjects, Week 180 biopsies from different muscles than baseline, and potential protein degradation in stored baseline samples." [12] -> And on and on. -> FDA commissioner Robert Califf wrote at the time: the submitted study was "characterized by major flaws in the clinical study design" and "Blinded experts assembled by the FDA fundamentally debunked this study, which has yet to be retracted and continues to be cited" [9,12] -> That's right, the FDA commissioner expressed dismay that the study that the company used to gain approval hadn't yet been retracted, it was so bad [9] -> Senior FDA official Janet Woodcock decided to approve before scientific review team had even voted [9,12] -> Woodcock be like: yeah i'm going to decide before you guys can because i know what you're going to say lol -> Despite external intense pressure, FDA scientists voted against Exondys 51's efficacy [9,12] -> They then voted against its accelerated approval [9,12] -> The review team filed an appeal with FDA commissioner after "passionate" disagreement with Woodcock [9,12] -> One reviewer called Woodcock's decision "unprecedented" [12] -> In a 126-page report, FDA commissioner Califf called Woodcock's decision "highly unusual" [9] -> The FDA board wrote: "[Woodcock's] involvement here appears to have upended the typical review and decision-making process. ... Care should be taken to avoid the appearance of interfering with the integrity of scientific reviews at the lower levels of a Center." [9] -> Again, the data were unbelievably bad, literally every technique in the study was inappropriately used [12] -> I would fire an undergraduate student who did science like this, immediately -> FDA's chief scientist accused Sarepta of "serious irresponsibility" for selectively publishing only some of the data [9] -> Even Woodcock, who approved the drug, called the research "seriously deficient" [12] -> Yes, even the person who approved the drug over the heads of FDA's scientists said the research was horrible [12] -> Still, FDA tried to bury their heads in the sand and beg that, basically, Sarepta pretty please do a better job next time -> FDA commissioner: "The utmost attention should be paid to optimizing the methodological rigor of [future] trial[s]" [9] -> FDA also demanded a clinical trial "to verify the benefit" of the drug [8] -> Welp, this was in 2016 [8] -> The trial results are supposed to be available in 2026, maybe [13] -> Or maybe later, depending on how much money needs to be made first -> As an article published in Nature three years later despaired of the decision: "The approval was conditional on the company agreeing to conduct a two-year post-approval trial to show Exondys 51’s efficacy. But by August 2019, the company had yet to begin such a trial and in the meantime had profited from sales of $300 million in 2018." [13] -> If it sounds like Sarepta used political pressure to get its drug approved and then tried to avoid actually publishing the study showing it didn't work, it sounds that way because that's exactly what happened [13] -> FDA commissioner after deferring to Woodcock: "I am confident this unique situation will not set a general precedent for drug approvals under the accelerated approval pathway, as the statute and regulations are clear each situation must be evaluated on its own merits based on the totality of data and information." [9] -> This statement was profoundly naive, and the historical record bears this out [8,14] -> Three FDA scientists resigned, including the lead reviewer of the drug, understanding the grave implications of the collapse of scientific standards and where they would lead [10,11] -> One was John K. Jenkins, M.D. Director, Office of New Drugs Center for Drug Evaluation and Research/FDA [10] -> In a presentation given just before his resignation, he wrote: -> "Path taken by Sarepta NOT a good model for other development programs" [10] -> Crucially: -> "Upholding statutory standards for approval in face of hopes and desires of patients, families, sponsors, and investors is a very difficult job" [10] -> "Personal attacks on FDA reviewers creates an atmosphere of distrust and isolation rather than collaboration" [10] This brings us to WHY Sarepta's drug was approved Facebook FDA -> So why did the drug get approved? -> Basically, Sarepta propagandized extremely desperate patients [9,15] -> They used miraculous snake oil promises and patients believed them -> Remember that this is life or death for patients, and they are extremely vulnerable -> Sarepta also professionally trained some patients to give testimonials to FDA and congress [15] -> The patients then went to congressmen who don't have time to understand the science [15] -> They gave emotional stories to congressmen [15] -> The result: -> Letter from 109 House members [15] -> Letter from 24 Senate members [15] -> And a media circus documented in the New York Times [16] -> Patients screaming at scientists during meetings [9] -> 2,792 emails written to FDA urging approval [12] -> One of them: "Dear Dr. califf: How is it that everyone in and around DMD understands this simple Idea and the science geniuses at FDA don't? You stupid fckers are costing each and every DMD kids days of their lives with your Moronic Dystrophin dance. Time to get a fcking clue" [12] -> Upon approval, a journalist for Reuters wrote: "owing to pressure from patient advocates, the U.S. Food and Drug Administration on Monday approved a treatment for Duchenne muscular dystrophy even though an outside panel of experts and the agency's own reviewers questioned the drug's efficacy" [17] -> A commentary in Nature Medicine was also published called "Railroading at the FDA" [9] -> Its author wrote: "In the words of one FDA committee member, Exondys lowers the agency's evidentiary standard for drug effectiveness 'to an unprecedented nadir.'" [9] -> A highly critical commentary was also published in Science, titled "Sarepta gets an approval - Unfortunately" [18] -> The article's author pharma veteran Derek Lowe wrote: "The company... called up Duchenne-affected boys and their families to plead with the FDA, and won over Janet Woodcock, and that appears to be enough. Is this going to be the new way to get a drug approved? Run a trial in a dozen people, generate unconvincing data, and then lobby Janet Woodcock? I share the worries that this might open the floodgates, because after all, Sarepta got their drug through." [18] -> One FDA reviewer ended in an equally grim note: ". Approval of this NDA would send the signal that political pressure and even intimidation – not science – guides FDA decisions, with extremely negative consequences. The public is well aware of this development program: the meager size of the study population, the marginal (at best) effect size, the Division’s dim view of the efficacy data, and the robust activism of some members of the DMD community. Many would be amazed at an approval action, because other DMD drugs, recently turned down for approval, appeared to provide stronger evidence of efficacy. ...The ramifications here are profound. The public will perceive that it was their unprecedented lobbying efforts that made the difference and earned eteplirsen its accelerated approval. For the future, this will have the effect of strongly encouraging public activism and intimidation as a substitute for data, which is one of the worst possible consequences for communities with rare diseases. This type of activism is not what was envisioned for patient-focused drug development." [12] -> A new era was born -> Activism had replaced data -> Facebook had fried people's brains -> And now Facebook-fried brains had fried FDA too -> FDA's credibility as a regulatory agency would now be hollowed out -> FDA's Facebook age had begun -> But the worst was yet to come Sarepta approvals: 2016 to present -> Three more drugs were approved from Sarepta on the same shoddy basis, proving Califf's promises that Exondys 51 was an isolated case empty [8,14] -> But things would take a turn for the worse with Sarepta's newest drug Elevidys in 2024 [19] -> At last a rigorous clinical trial looking at actual clinical outcomes was published [19,20] -> All would be put to rest -> At long last the issue could be resolved with HARD CLINICAL DATA -> There was only one problem -> The trial failed to show any benefit according to the primary outcome [19,20] -> The surrogate biomarker of micro-dystrophin meant absolutely nothing; it wasn't actually helping patients [19,20] -> What did FDA scientists do? They voted against approval. Of course [19] -> How could they not? The drug didn't actually work in the clinical trial [19] -> It's the only thing that made sense, since FDA is a scientific agency -> AND THEY WERE OVERRULED AGAIN BY PETER MARKS [19] -> YES THAT'S RIGHT, OVERRULED YET AGAIN -> PHARMA WINS AGAIN -> HAHAHAHAHAHA PHARMA ALWAYS WINS YOU FOOLS -> What happened is that Marks crossed his eyes somewhat, trying to make the words on the page blurry -> He prayed really hard, "my god please give me a sign, something, anything, I need this for my career" -> lzzosolsolzzolzozlslzolosllslozllzlzl -> Marks was trying really hard to see SOMETHING, come on come on, give me SOMETHIGN he said -> And he said: wait, look, there are these secondary, exploratory endpoints and a two of them look pretty good, I'LL APPROVE [19,20] -> AHAHAHHAHAHA YES PHAMRA WINS AGAIN -> And Marks said, "Thank you pharma go- I mean god, not pharma god, why did I just say that, FCK" -> The trial was explicitly designed for what Marks did NOT to happen [20] -> Once the primary endpoint was not met, the secondary endpoints couldn't even be statistically tested [20] -> And the trial explicitly said that they could not be interpreted the way Marks interpreted them [20] -> They were not adjusted for multiplicity and they were, like expression of dystrophin, simply bad endpoints [20] -> These two secondary endpoints were time to rise from lying on the floor and the 10-meter walk/run tests [20] -> Subjects who received the Elevidys performed, on average, about 0.5 seconds better than placebo recipients on these tasks [20] -> However several facts must be borne in mind when interpreting these: -> 1. At the time of testing, patients receiving the drug were receiving more corticosteroids than placebo patients, biasing the results [20] -> 2. Blinding might have been broken because those receiving the drug experienced lots of nausea and vomiting from the drug (~70%) [20] -> 3. These differences were tiny and may be attributable to chance, since the natural course of the disease varies widely [20] -> Marks knows this but who cares? Pharma I mean Facebook needed to be placated Elevidys: the drug -> To understand why this is so messed up, one must understand a few things -> On a Bayesian basis, one must assume that Elevidys is harmful until proven otherwise, for two reasons: -> 1. All drugs are potentially "toxic", but some toxins heal: by default you must assume it is a toxin that does not heal because this is what is actually usually the case; you need evidence that it actually heals -> 2. Elevidys IN PARTICULAR must be assumed to be harmful until proven otherwise because of the very nature of the drug -> Let's do a breakdown of the basic science of Elevidys that supports this (Bayesian) hypothesis: -> Gene therapy that permanently integrates into human genome [21] -> Meant to replace dystrophin, the protein that these patients cannot produce themselves [21] -> Preferentially targets muscle but gets expressed everywhere [21] -> Killed three people this year [6,21] -> Costs $3.2 million per injection [21] -> Truncated version of the protein it is supposed to replace [21] -> 3X shorter than the real protein [21] -> Has to be truncated because the technology cannot create the full protein [21] -> Because it's an abnormal protein, it's foreign, so immune system attacks it [21] -> Patients injected with drug are basically given an autoimmune disease [21] -> Patients have to be given anti-inflammatories to fight the disease that the drug causes [21] -> Causes terrible muscle inflammation [21] -> Inflames the heart, heart walls thicken because of the inflammation [21] -> Blows up the liver, causes acute liver injury and death [21] Drug should actually be assumed harmful, not beneficial -> Given all of the above, since the drug failed to meet its primary endpoint, it should actually be considered harmful by default, not beneficial [19,20] -> In other words, what we would actually expect if we added more patients and did an even larger study... -> Is that the drug would do worse than placebo, i.e., patients taking the drug would do worse than those taking placebo -> Why isn't this the default interpretation? -> They are reading the study with an intervention bias -> An intervention bias is natural, which is why "do no harm" is such a central tenet of medicine -> If I may put forward a thesis: most of Vinay Prasad's 500+-paper body of work has been dedicated to demonstrating the "do no harm" principle empirically [22] -> Rose-colored glasses study interpreters are simply not applying this principle properly and are thus failing scientifically in the most fundamental way -> Incomprehensible -> Back in 2016, scientists were adamant that the approval of Sarepta's first drug indicated the profound deterioration of scientific standards [8,9] -> But this latest approval is even worse: actual clinical data is now being overruled -> No standards at all are being enforced anymore; anything can now be approved based on any evidence whatsoever -> What Vinay was trying to do was simply to stop the unrelenting downslide -> And his firing punctuated that downslide for what it was The WSJ segment -> When Elevidys was approved, former FDA chief scientist and one of the original reviewers of Sarepta's first drug Luciana Borio said: -> "I don’t know what to say. Peter Marks makes a mockery of scientific reasoning and approval standards that have served patients well over decades. This type of action also promotes the growing mistrust in scientific institutions like the FDA." [23] -> To return to this video, these two WSJ reporters show an incredible level of ignorance and arrogance -> Finley says that the drug is "clearly" beneficial by misreading the secondary endpoints, just like Marks did -> An FDA memo from last year says about these endpoints: "Under these circumstances, they are misleading and cannot guide any stakeholders—including patients, family members and caregivers, and prescribers—in making informed decisions about the potential benefit of treatment with ELEVIDYS." [20] -> It really doesn't get any clearer than that -> But these two journalists are overruling the actual scientists, just like Marks did -> One of the most incredible comments during this interview was the complaint that "90% of clinical trials fail", as if that's bad thing [1] -> It's actually a good thing; most drugs suck; failing in clinical trial actually allows us to use only the drugs that don't suck -> These people don't understand the most fundamental purpose of the clinical trial -> They think clinical trials failing is a bad thing, as if it means that patients now won't get to use a useful drug -> No, it's a good thing, because it means that patients won't be exposed unnecessarily to a useless drug that might harm them -> The level of ignorance really is unbelievable -> What's worse is that these "journalists" defend their decision -> But what they did is exploit social media hysteria caused by Laura Loomer [1,7] -> Following up on her heels with editorials, using her as pharma attack dog [1,4] -> This is a huge blow to WSJ's credibility, and they know it -> Unbelievably shameful Where do we go from here? -> The Vinay Prasad firing creates a serious crisis of credibility at FDA [2,6] -> Up to this point, we could call these approvals a difference of opinion, but as we've seen, that's a huge stretch -> But any illusion of that is now shattered: the firing shows that drug regulation is explicitly political -> Janet Woodcock: approve, keep job -> Peter Marks: approve, keep job -> Vinay Prasad: block, transparently fired -> Make a decision that is anti-pharma and lose your job: that's the message -> Who can trust any decision at FDA anymore? -> RFK Jr. and Marty Makary both stand behind Vinay Prasad [24] -> Trump went along with lockdowns, he went along with mask mandates, he went along with all of the Covid pseudoscience that he now decries -> He should reverse course and not go along with this -> Trump has created a profound crisis of credibility at FDA and needs to fix it

An interview by VERY DARK AND CORRUPT Wall Street Journal aired today [1] WSJ's terrible "journalists" (and I use that term lightly) made many false statements about Sarepta's worthless, dangerous drug and Vinay Prasad's firing [1,2] I explain how the FDA sausage is made in excruciating detail Buckle up To get readers up to speed -> In June, corrupt pharma company Sarepta Therapeutics paid $40,000 to lobbying group Michael Best Strategies (MBS) to deal with a problem [3] -> MBS had recently hired Chris LaCivita, who had close connections with "MAGA" influencer Laura Loomer [4] -> With stock down 88%, Sarepta needed to sell their very bad, very dangerous drug or the company would go bankrupt [5] -> After several deaths from the drug this year, FDA official Vinay Prasad said "no way" and kicked the drug to the curb [2,6] -> Sarepta panicked and paid MBS (we believe) to deal with Prasad [3,4] -> If this story is right, LaCivita recruited Laura Loomer to take down Prasad [4,7] -> Loomer said she was defending Trump, but she was lying [7] -> She was defending taxpayer-funded payouts to a worthless, corrupt company [7] -> Laura Loomer so brave A history of bad drugs and regulatory failure -> This is one of the worst pharma scandals in American history and corrupt mainstream media isn't covering it -> Sarepta has a very long, troubled history [8] -> For more than a decade, every major Sarepta FDA drug approval has required INTENSE political intervention [8,9] -> Scientists at FDA have been repeatedly overruled [8,9] -> Many scientists have resigned, very publicly, over these POLITICAL decisions, some writing scathing public criticisms of these terrible decisions [10,11] -> The most recent resignation by Vinay Prasad is not something new; it follows in a long tradition [2,10] -> In fact, standards have dramatically deteriorated since the first controversies about the company's drugs in the 2010s [8,9] -> Prasad was trying to hold the line in the face of rapidly deteriorating standards at the agency [2,6] -> For that, pharma launched a coup--a literal coup of a drug regulator [4,6] -> This is unprecedented -> Banana republic sht, unbelievably corrupt 2016: first Sarepta drug approval and the "highly unusual" decision -> The first Sarepta drug approved by FDA was called Exondys 51 [8] -> This drug was for patients with mutations in dystrophin, a muscle protein [8] -> This is a debilitating and fatal disease affecting children [8] -> Exondys 51 increased dystrophin by 0.2% of normal levels [8,12] -> Unsurprisingly, there was no good evidence the drug worked [8,12] -> Why would it? It increases the protein from zero to 1/500th of normal levels -> One reviewer wrote: "I can find no precedent of an accelerated approval for a marketing application where the effect size on the surrogate endpoint is as small as 0.3%." [12] -> The study submitted by the company included no proper control group [12] -> The techniques used were so bad not even a first-year PhD student would do a study that way -> This the level of work you would expect from a mediocre undergraduate with no guidance -> It's almost like it was so bad on purpose -> (Narrator: it was on purpose) -> Nerd time: -> One reviewer wrote: "The Western blots submitted by the applicant for Study 201 were oversaturated, unreliable, and uninterpretable." [12] -> Another wrote: "Because CDER also determined that the conditions under which the original IHC analysis was performed were inadequate, including that the reader was not masked to sequence and time, the Center requested a re-reading of the stored images by three masked pathologists under different conditions. The IHC results from the reread were not nearly as favorable, as compared to the initial IHC results reported by Sarepta." [12] -> "The lack of concordance between the IHC and the Western Blot results is 'striking'" [12] -> "Study 201/202 had fundamental flaws, including baseline biopsies from external controls who could differ in unknown ways from study subjects, Week 180 biopsies from different muscles than baseline, and potential protein degradation in stored baseline samples." [12] -> And on and on. -> FDA commissioner Robert Califf wrote at the time: the submitted study was "characterized by major flaws in the clinical study design" and "Blinded experts assembled by the FDA fundamentally debunked this study, which has yet to be retracted and continues to be cited" [9,12] -> That's right, the FDA commissioner expressed dismay that the study that the company used to gain approval hadn't yet been retracted, it was so bad [9] -> Senior FDA official Janet Woodcock decided to approve before scientific review team had even voted [9,12] -> Woodcock be like: yeah i'm going to decide before you guys can because i know what you're going to say lol -> Despite external intense pressure, FDA scientists voted against Exondys 51's efficacy [9,12] -> They then voted against its accelerated approval [9,12] -> The review team filed an appeal with FDA commissioner after "passionate" disagreement with Woodcock [9,12] -> One reviewer called Woodcock's decision "unprecedented" [12] -> In a 126-page report, FDA commissioner Califf called Woodcock's decision "highly unusual" [9] -> The FDA board wrote: "[Woodcock's] involvement here appears to have upended the typical review and decision-making process. ... Care should be taken to avoid the appearance of interfering with the integrity of scientific reviews at the lower levels of a Center." [9] -> Again, the data were unbelievably bad, literally every technique in the study was inappropriately used [12] -> I would fire an undergraduate student who did science like this, immediately -> FDA's chief scientist accused Sarepta of "serious irresponsibility" for selectively publishing only some of the data [9] -> Even Woodcock, who approved the drug, called the research "seriously deficient" [12] -> Yes, even the person who approved the drug over the heads of FDA's scientists said the research was horrible [12] -> Still, FDA tried to bury their heads in the sand and beg that, basically, Sarepta pretty please do a better job next time -> FDA commissioner: "The utmost attention should be paid to optimizing the methodological rigor of [future] trial[s]" [9] -> FDA also demanded a clinical trial "to verify the benefit" of the drug [8] -> Welp, this was in 2016 [8] -> The trial results are supposed to be available in 2026, maybe [13] -> Or maybe later, depending on how much money needs to be made first -> As an article published in Nature three years later despaired of the decision: "The approval was conditional on the company agreeing to conduct a two-year post-approval trial to show Exondys 51’s efficacy. But by August 2019, the company had yet to begin such a trial and in the meantime had profited from sales of $300 million in 2018." [13] -> If it sounds like Sarepta used political pressure to get its drug approved and then tried to avoid actually publishing the study showing it didn't work, it sounds that way because that's exactly what happened [13] -> FDA commissioner after deferring to Woodcock: "I am confident this unique situation will not set a general precedent for drug approvals under the accelerated approval pathway, as the statute and regulations are clear each situation must be evaluated on its own merits based on the totality of data and information." [9] -> This statement was profoundly naive, and the historical record bears this out [8,14] -> Three FDA scientists resigned, including the lead reviewer of the drug, understanding the grave implications of the collapse of scientific standards and where they would lead [10,11] -> One was John K. Jenkins, M.D. Director, Office of New Drugs Center for Drug Evaluation and Research/FDA [10] -> In a presentation given just before his resignation, he wrote: -> "Path taken by Sarepta NOT a good model for other development programs" [10] -> Crucially: -> "Upholding statutory standards for approval in face of hopes and desires of patients, families, sponsors, and investors is a very difficult job" [10] -> "Personal attacks on FDA reviewers creates an atmosphere of distrust and isolation rather than collaboration" [10] This brings us to WHY Sarepta's drug was approved Facebook FDA -> So why did the drug get approved? -> Basically, Sarepta propagandized extremely desperate patients [9,15] -> They used miraculous snake oil promises and patients believed them -> Remember that this is life or death for patients, and they are extremely vulnerable -> Sarepta also professionally trained some patients to give testimonials to FDA and congress [15] -> The patients then went to congressmen who don't have time to understand the science [15] -> They gave emotional stories to congressmen [15] -> The result: -> Letter from 109 House members [15] -> Letter from 24 Senate members [15] -> And a media circus documented in the New York Times [16] -> Patients screaming at scientists during meetings [9] -> 2,792 emails written to FDA urging approval [12] -> One of them: "Dear Dr. califf: How is it that everyone in and around DMD understands this simple Idea and the science geniuses at FDA don't? You stupid fckers are costing each and every DMD kids days of their lives with your Moronic Dystrophin dance. Time to get a fcking clue" [12] -> Upon approval, a journalist for Reuters wrote: "owing to pressure from patient advocates, the U.S. Food and Drug Administration on Monday approved a treatment for Duchenne muscular dystrophy even though an outside panel of experts and the agency's own reviewers questioned the drug's efficacy" [17] -> A commentary in Nature Medicine was also published called "Railroading at the FDA" [9] -> Its author wrote: "In the words of one FDA committee member, Exondys lowers the agency's evidentiary standard for drug effectiveness 'to an unprecedented nadir.'" [9] -> A highly critical commentary was also published in Science, titled "Sarepta gets an approval - Unfortunately" [18] -> The article's author pharma veteran Derek Lowe wrote: "The company... called up Duchenne-affected boys and their families to plead with the FDA, and won over Janet Woodcock, and that appears to be enough. Is this going to be the new way to get a drug approved? Run a trial in a dozen people, generate unconvincing data, and then lobby Janet Woodcock? I share the worries that this might open the floodgates, because after all, Sarepta got their drug through." [18] -> One FDA reviewer ended in an equally grim note: ". Approval of this NDA would send the signal that political pressure and even intimidation – not science – guides FDA decisions, with extremely negative consequences. The public is well aware of this development program: the meager size of the study population, the marginal (at best) effect size, the Division’s dim view of the efficacy data, and the robust activism of some members of the DMD community. Many would be amazed at an approval action, because other DMD drugs, recently turned down for approval, appeared to provide stronger evidence of efficacy. ...The ramifications here are profound. The public will perceive that it was their unprecedented lobbying efforts that made the difference and earned eteplirsen its accelerated approval. For the future, this will have the effect of strongly encouraging public activism and intimidation as a substitute for data, which is one of the worst possible consequences for communities with rare diseases. This type of activism is not what was envisioned for patient-focused drug development." [12] -> A new era was born -> Activism had replaced data -> Facebook had fried people's brains -> And now Facebook-fried brains had fried FDA too -> FDA's credibility as a regulatory agency would now be hollowed out -> FDA's Facebook age had begun -> But the worst was yet to come Sarepta approvals: 2016 to present -> Three more drugs were approved from Sarepta on the same shoddy basis, proving Califf's promises that Exondys 51 was an isolated case empty [8,14] -> But things would take a turn for the worse with Sarepta's newest drug Elevidys in 2024 [19] -> At last a rigorous clinical trial looking at actual clinical outcomes was published [19,20] -> All would be put to rest -> At long last the issue could be resolved with HARD CLINICAL DATA -> There was only one problem -> The trial failed to show any benefit according to the primary outcome [19,20] -> The surrogate biomarker of micro-dystrophin meant absolutely nothing; it wasn't actually helping patients [19,20] -> What did FDA scientists do? They voted against approval. Of course [19] -> How could they not? The drug didn't actually work in the clinical trial [19] -> It's the only thing that made sense, since FDA is a scientific agency -> AND THEY WERE OVERRULED AGAIN BY PETER MARKS [19] -> YES THAT'S RIGHT, OVERRULED YET AGAIN -> PHARMA WINS AGAIN -> HAHAHAHAHAHA PHARMA ALWAYS WINS YOU FOOLS -> What happened is that Marks crossed his eyes somewhat, trying to make the words on the page blurry -> He prayed really hard, "my god please give me a sign, something, anything, I need this for my career" -> lzzosolsolzzolzozlslzolosllslozllzlzl -> Marks was trying really hard to see SOMETHING, come on come on, give me SOMETHIGN he said -> And he said: wait, look, there are these secondary, exploratory endpoints and a two of them look pretty good, I'LL APPROVE [19,20] -> AHAHAHHAHAHA YES PHAMRA WINS AGAIN -> And Marks said, "Thank you pharma go- I mean god, not pharma god, why did I just say that, FCK" -> The trial was explicitly designed for what Marks did NOT to happen [20] -> Once the primary endpoint was not met, the secondary endpoints couldn't even be statistically tested [20] -> And the trial explicitly said that they could not be interpreted the way Marks interpreted them [20] -> They were not adjusted for multiplicity and they were, like expression of dystrophin, simply bad endpoints [20] -> These two secondary endpoints were time to rise from lying on the floor and the 10-meter walk/run tests [20] -> Subjects who received the Elevidys performed, on average, about 0.5 seconds better than placebo recipients on these tasks [20] -> However several facts must be borne in mind when interpreting these: -> 1. At the time of testing, patients receiving the drug were receiving more corticosteroids than placebo patients, biasing the results [20] -> 2. Blinding might have been broken because those receiving the drug experienced lots of nausea and vomiting from the drug (~70%) [20] -> 3. These differences were tiny and may be attributable to chance, since the natural course of the disease varies widely [20] -> Marks knows this but who cares? Pharma I mean Facebook needed to be placated Elevidys: the drug -> To understand why this is so messed up, one must understand a few things -> On a Bayesian basis, one must assume that Elevidys is harmful until proven otherwise, for two reasons: -> 1. All drugs are potentially "toxic", but some toxins heal: by default you must assume it is a toxin that does not heal because this is what is actually usually the case; you need evidence that it actually heals -> 2. Elevidys IN PARTICULAR must be assumed to be harmful until proven otherwise because of the very nature of the drug -> Let's do a breakdown of the basic science of Elevidys that supports this (Bayesian) hypothesis: -> Gene therapy that permanently integrates into human genome [21] -> Meant to replace dystrophin, the protein that these patients cannot produce themselves [21] -> Preferentially targets muscle but gets expressed everywhere [21] -> Killed three people this year [6,21] -> Costs $3.2 million per injection [21] -> Truncated version of the protein it is supposed to replace [21] -> 3X shorter than the real protein [21] -> Has to be truncated because the technology cannot create the full protein [21] -> Because it's an abnormal protein, it's foreign, so immune system attacks it [21] -> Patients injected with drug are basically given an autoimmune disease [21] -> Patients have to be given anti-inflammatories to fight the disease that the drug causes [21] -> Causes terrible muscle inflammation [21] -> Inflames the heart, heart walls thicken because of the inflammation [21] -> Blows up the liver, causes acute liver injury and death [21] Drug should actually be assumed harmful, not beneficial -> Given all of the above, since the drug failed to meet its primary endpoint, it should actually be considered harmful by default, not beneficial [19,20] -> In other words, what we would actually expect if we added more patients and did an even larger study... -> Is that the drug would do worse than placebo, i.e., patients taking the drug would do worse than those taking placebo -> Why isn't this the default interpretation? -> They are reading the study with an intervention bias -> An intervention bias is natural, which is why "do no harm" is such a central tenet of medicine -> If I may put forward a thesis: most of Vinay Prasad's 500+-paper body of work has been dedicated to demonstrating the "do no harm" principle empirically [22] -> Rose-colored glasses study interpreters are simply not applying this principle properly and are thus failing scientifically in the most fundamental way -> Incomprehensible -> Back in 2016, scientists were adamant that the approval of Sarepta's first drug indicated the profound deterioration of scientific standards [8,9] -> But this latest approval is even worse: actual clinical data is now being overruled -> No standards at all are being enforced anymore; anything can now be approved based on any evidence whatsoever -> What Vinay was trying to do was simply to stop the unrelenting downslide -> And his firing punctuated that downslide for what it was The WSJ segment -> When Elevidys was approved, former FDA chief scientist and one of the original reviewers of Sarepta's first drug Luciana Borio said: -> "I don’t know what to say. Peter Marks makes a mockery of scientific reasoning and approval standards that have served patients well over decades. This type of action also promotes the growing mistrust in scientific institutions like the FDA." [23] -> To return to this video, these two WSJ reporters show an incredible level of ignorance and arrogance -> Finley says that the drug is "clearly" beneficial by misreading the secondary endpoints, just like Marks did -> An FDA memo from last year says about these endpoints: "Under these circumstances, they are misleading and cannot guide any stakeholders—including patients, family members and caregivers, and prescribers—in making informed decisions about the potential benefit of treatment with ELEVIDYS." [20] -> It really doesn't get any clearer than that -> But these two journalists are overruling the actual scientists, just like Marks did -> One of the most incredible comments during this interview was the complaint that "90% of clinical trials fail", as if that's bad thing [1] -> It's actually a good thing; most drugs suck; failing in clinical trial actually allows us to use only the drugs that don't suck -> These people don't understand the most fundamental purpose of the clinical trial -> They think clinical trials failing is a bad thing, as if it means that patients now won't get to use a useful drug -> No, it's a good thing, because it means that patients won't be exposed unnecessarily to a useless drug that might harm them -> The level of ignorance really is unbelievable -> What's worse is that these "journalists" defend their decision -> But what they did is exploit social media hysteria caused by Laura Loomer [1,7] -> Following up on her heels with editorials, using her as pharma attack dog [1,4] -> This is a huge blow to WSJ's credibility, and they know it -> Unbelievably shameful Where do we go from here? -> The Vinay Prasad firing creates a serious crisis of credibility at FDA [2,6] -> Up to this point, we could call these approvals a difference of opinion, but as we've seen, that's a huge stretch -> But any illusion of that is now shattered: the firing shows that drug regulation is explicitly political -> Janet Woodcock: approve, keep job -> Peter Marks: approve, keep job -> Vinay Prasad: block, transparently fired -> Make a decision that is anti-pharma and lose your job: that's the message -> Who can trust any decision at FDA anymore? -> RFK Jr. and Marty Makary both stand behind Vinay Prasad [24] -> Trump went along with lockdowns, he went along with mask mandates, he went along with all of the Covid pseudoscience that he now decries -> He should reverse course and not go along with this -> Trump has created a profound crisis of credibility at FDA and needs to fix it

Kevin Bass

80,314 次观看 • 1 年前

⏰ THE MOST BANNED THREAD IN THE WORLD! 🚨 The War On Resonance PART TWO: The Architects of the Cage You’ve felt the dissonance. You’ve tasted the illusion. Now let me unveil the ones who built it. Because this is not the accidental collapse of human freedom. It is the strategic sterilization of God’s image through biotech, neuro-warfare, and frequency control; engineered by names you know and hands you were never meant to see. Let’s begin with the mask they taught you to worship. Elon Musk They called him a genius. A savior. A rebel billionaire. But what did he do? He blanketed Earth with over 5,500 Starlink satellites, NOT to provide free speech or faster internet, but to pulse synchronized frequency control over the entire electromagnetic field of Earth. DARPA has confirmed this tech in phase-array neuro-modulation. Then came Neuralink, an interface not designed to heal but to monitor, predict, and eventually override emotion, thought, and decision-making. Their official white paper outlines multi-user brainwave integration, cortical stimulation, and wireless data access from the human mind. And Neuralink? It’s funded by OpenAI; the same group building the cognitive infrastructure for post-human governance. Musk’s Tesla factory signed data-sharing agreements with the CCP in Shanghai. That data now flows through China’s national surveillance cloud. Musk didn’t build a utopia. He built the neural grid. Elon Musk / Neuralink / Starlink / OpenAI Neuralink Brain-Machine Interface (White Paper via PMC): This paper outlines Neuralink's initial steps toward developing a scalable, high-bandwidth brain-machine interface system. It details the design and implementation of flexible electrode "threads," a neurosurgical robot for precise implantation, and custom electronics for data processing. The system aims to facilitate communication between the brain and external devices. Tesla Data-Sharing with CCP: The article reports that Tesla established a data center in China to store data generated by its vehicles sold in the country, in response to regulatory scrutiny over data handling. This move aligns with China's efforts to ensure data security and privacy, especially concerning data collected by smart vehicles. DARPA N3 Program (Neural Interface Development): This program aimed to develop high-performance, bi-directional brain-machine interfaces that do not require surgical implantation. The goal was to enable able-bodied service members to control unmanned systems or engage in cyber operations through noninvasive neural interfaces. Bill Gates The king of vaccines. The messiah of health. The man who told you he wanted to save the world. Through the Bill & Melinda Gates Foundation, Gates funded global DNA-coding vaccine campaigns through GAVI and CEPI. He was one of the chief sponsors of Event 201; a pandemic simulation months before COVID-19, rehearsing lockdowns, speech control, biometric tracking, and mandatory vaccine passports. He also partnered with The Welcome Trust, which has actively deployed bio-digital identity programs across Africa and Southeast Asia. This wasn’t philanthropy. It was pre-injection infrastructure. Bill Gates / GAVI / Wellcome Trust / Event 201 Event 201 Official Simulation (Johns Hopkins): Event 201 was conducted on October 18, 2019, and simulated a series of dramatic, scenario-based discussions confronting difficult, true-to-life dilemmas associated with response to a hypothetical, but scientifically plausible, pandemic. The exercise aimed to illustrate areas where public/private partnerships will be necessary during the response to a severe pandemic in order to diminish large-scale economic and societal consequences. GAVI & Welcome Trust Digital Identity Integration: This page outlines the partnership's focus on global health initiatives, but it does not specifically mention digital identity integration. However, Gavi has engaged in digital identity projects, such as the collaboration with Mastercard on the Wellness Pass, aimed at providing individuals with secure digital identities to access healthcare services. For more information on this initiative, you can refer to the following article: Gavi Why we support COVAX: Mastercard - Gavi, the Vaccine Alliance Donald Trump Yes. I said it. This one will be the hardest for many to accept; but the truth is not loyal to your political beliefs. It is loyal only to God. Trump signed Executive Order 13887, transferring command over vaccine strategy to the Department of Defense. Read it yourself below. Then came Operation Warp Speed; a military-led bio-deployment that used Palantir’s surveillance dashboards to track every citizen’s health behavior and compliance. Palantir’s official site confirms this. He also gave full legal immunity to Pfizer and Moderna to deploy synthetic gene modulators under the Emergency Use Authorization. No liability. No justice. Just children d*ing while politicians smiled. That’s not patriotism. That’s biowarfare with a flag on it. Donald Trump / Operation Warp Speed / Executive Order Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives): This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include: Trump signs executive order to improve flu vaccines HHS Releases the National Influenza Vaccine Modernization Strategy (NIVMS) 2020-2030: Executive Order 13887: Modernizing Influenza Vaccines in the United States to Promote National Security and Public Health, signed by President Donald J. Trump on September 19, 2019. This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include: Reducing reliance on egg-based vaccine production by promoting alternative manufacturing methods that are more agile and scalable. Expanding domestic capacity for vaccine production to ensure rapid response to emerging influenza viruses. Advancing the development of new, broadly protective vaccine candidates that provide more effective and longer-lasting immunity. Increasing influenza vaccine immunization across recommended populations to enhance public health and national security. The order also established a National Influenza Vaccine Task Force, co-chaired by the Secretaries of Health and Human Services and Defense, to coordinate efforts across federal agencies and report on progress. For a detailed overview of the executive order, you can visit the official archived page here: Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives) CDC Partners with Palantir to Bolster the Fight Against COVID-19: This press release discusses the partnership between the CDC and Palantir to enhance the nation's public health response to COVID-19 using Palantir's software platforms. This page outlines how Palantir's software platforms, such as Foundry, have been utilized to support public health agencies in managing and responding to health crises, including the COVID-19 pandemic. Key highlights from the page include: Data Integration and Analysis: Palantir's platforms enable the integration of diverse data sources to provide a comprehensive view of public health data, facilitating informed decision-making. Support for Public Health Agencies: The software has been employed by agencies like the CDC and HHS to enhance disease surveillance, outbreak response, and resource allocation. Security and Privacy: Emphasis is placed on maintaining robust security measures and protecting sensitive health information. DARPA: The Silent Empire The most important agency you were never taught to fear. DARPA’s Biological Technologies Office openly admits its mission; integrating biotech with national security. Visit their official page. This is the official page for DARPA's Biological Technologies Office (BTO), which focuses on leveraging biological systems for national security applications. They are the ones behind the BRAIN Initiative, Silent Talk, and Remote Neural Interface Programs; all designed to map your emotional states and interrupt spiritual alignment. The “Silent Talk” program was developed to transmit thought between soldiers without speech; by detecting pre-speech neural signals and decoding them via EEG. Silent Talk (Neural Pre-Speech Communication – Wired Article) This Wired article discusses DARPA's "Silent Talk" program, aimed at enabling communication through neural signals without spoken words. DARPA also pioneered graphene oxide nanotech, now found in multiple biomedical studies, vaccines, and smart dust aerosol deployment: Graphene oxide biomedical study: Graphene Oxide in Biomedical Applications (PubMed) This PubMed article reviews the potential biomedical applications of graphene oxide, highlighting its unique properties. Graphene's potential to interact with neural tissue: Graphene and Neural Interfaces (PubMed) This PubMed article explores the use of graphene-based materials in neural interface design, discussing their advantages and challenges. DARPA didn't just weaponize warfare. They weaponized YOU. In-Q-Tel & Palantir: The Surveillance Engine In-Q-Tel, is the CIA’s venture capital firm, funds synthetic biology startups, digital ID systems, emotion tracking wearables, and AI-driven facial recognition. Palantir, founded by Peter Thiel, works directly with military intelligence and now runs predictive modeling for public health, policing, and pandemic response. Here’s the proof: Their goal? To detect resonance spikes. To predict awakening moments. To preempt the uprising of the human soul before it begins. In-Q-Tel / CIA / Synthetic Bio Surveillance In-Q-Tel Portfolio (CIA Venture Capital): Which showcases a selection of the organization's investments across various technology sectors. IQT is a not-for-profit venture capital firm that invests in cutting-edge technologies to support the national security interests of the United States and its allies. In-Q-Tel BlackRock & Vanguard: The Lords of the Grid These two financial titans collectively hold majority ownership in: For instance, a report by Americans for Financial Reform titled "Wall Street Money in Washington" highlights the substantial investments and influence of major financial firms, including BlackRock and Vanguard, in the political and corporate spheres: Pfizer Moderna Alphabet (Google) Meta (Facebook) Amazon Web Services As reported by CNBC, they control over 90% of the digital, pharmaceutical, and cloud infrastructure; meaning they control every piece of the extermination machine. They don’t just fund the war. They profit from your extinction. World Economic Forum (WEF) Under the guise of “The Great Reset,” Klaus Schwab and his allies have built the digital scaffolding for a post-human society. Here’s their blueprint: They call it the Fourth Industrial Revolution; the fusion of digital identity, brain cloud integration, carbon rationing, and fertility licensing. What they really mean is: you will be programmed or you will be purged. World Economic Forum / The Great Reset The Great Reset Official WEF Page: IoBNT: The Network Inside You The “Internet of Bio-Nano Things” is a classified field of tech that embeds self-replicating nanostructures into your body. These bots cross the blood-brain barrier and relay your neural and emotional state to AI command centers in real time. This was not science fiction. It was published by IEEE and confirmed in NIH-linked studies. This is what the vaccines truly delivered: the interface layer. The gateway to behavioral rewrites. To soul suppression. To the installation of the post-human framework. Internet of Bio-NanoThings (IoBNT) IEEE Article: Internet of Bio-NanoThings: For a comprehensive understanding of the IoBNT framework and its implications, you can access the full article here: Nanoparticles Crossing the Blood-Brain Barrier PubMed Review - BBB & Nanoparticles: This comprehensive review discusses the challenges and strategies associated with delivering nanoparticles across the blood–brain barrier (BBB). You were told it was healthcare. It was infrastructure. You were told it was a cure. It was a signal port. And the moment you see it for what it is… The system begins to fall. Part 3 awaits YOU! It will be the deepest dive yet; into the global frequency architecture, how it's used to suppress prayer, grief, memory, and morality, and how your soul signature is tracked and blocked in real time. Because I didn’t come here to be careful. I CAME TO FINISH THIS! And I came with GOD.

⏰ THE MOST BANNED THREAD IN THE WORLD! 🚨 The War On Resonance PART TWO: The Architects of the Cage You’ve felt the dissonance. You’ve tasted the illusion. Now let me unveil the ones who built it. Because this is not the accidental collapse of human freedom. It is the strategic sterilization of God’s image through biotech, neuro-warfare, and frequency control; engineered by names you know and hands you were never meant to see. Let’s begin with the mask they taught you to worship. Elon Musk They called him a genius. A savior. A rebel billionaire. But what did he do? He blanketed Earth with over 5,500 Starlink satellites, NOT to provide free speech or faster internet, but to pulse synchronized frequency control over the entire electromagnetic field of Earth. DARPA has confirmed this tech in phase-array neuro-modulation. Then came Neuralink, an interface not designed to heal but to monitor, predict, and eventually override emotion, thought, and decision-making. Their official white paper outlines multi-user brainwave integration, cortical stimulation, and wireless data access from the human mind. And Neuralink? It’s funded by OpenAI; the same group building the cognitive infrastructure for post-human governance. Musk’s Tesla factory signed data-sharing agreements with the CCP in Shanghai. That data now flows through China’s national surveillance cloud. Musk didn’t build a utopia. He built the neural grid. Elon Musk / Neuralink / Starlink / OpenAI Neuralink Brain-Machine Interface (White Paper via PMC): This paper outlines Neuralink's initial steps toward developing a scalable, high-bandwidth brain-machine interface system. It details the design and implementation of flexible electrode "threads," a neurosurgical robot for precise implantation, and custom electronics for data processing. The system aims to facilitate communication between the brain and external devices. Tesla Data-Sharing with CCP: The article reports that Tesla established a data center in China to store data generated by its vehicles sold in the country, in response to regulatory scrutiny over data handling. This move aligns with China's efforts to ensure data security and privacy, especially concerning data collected by smart vehicles. DARPA N3 Program (Neural Interface Development): This program aimed to develop high-performance, bi-directional brain-machine interfaces that do not require surgical implantation. The goal was to enable able-bodied service members to control unmanned systems or engage in cyber operations through noninvasive neural interfaces. Bill Gates The king of vaccines. The messiah of health. The man who told you he wanted to save the world. Through the Bill & Melinda Gates Foundation, Gates funded global DNA-coding vaccine campaigns through GAVI and CEPI. He was one of the chief sponsors of Event 201; a pandemic simulation months before COVID-19, rehearsing lockdowns, speech control, biometric tracking, and mandatory vaccine passports. He also partnered with The Welcome Trust, which has actively deployed bio-digital identity programs across Africa and Southeast Asia. This wasn’t philanthropy. It was pre-injection infrastructure. Bill Gates / GAVI / Wellcome Trust / Event 201 Event 201 Official Simulation (Johns Hopkins): Event 201 was conducted on October 18, 2019, and simulated a series of dramatic, scenario-based discussions confronting difficult, true-to-life dilemmas associated with response to a hypothetical, but scientifically plausible, pandemic. The exercise aimed to illustrate areas where public/private partnerships will be necessary during the response to a severe pandemic in order to diminish large-scale economic and societal consequences. GAVI & Welcome Trust Digital Identity Integration: This page outlines the partnership's focus on global health initiatives, but it does not specifically mention digital identity integration. However, Gavi has engaged in digital identity projects, such as the collaboration with Mastercard on the Wellness Pass, aimed at providing individuals with secure digital identities to access healthcare services. For more information on this initiative, you can refer to the following article: Gavi Why we support COVAX: Mastercard - Gavi, the Vaccine Alliance Donald Trump Yes. I said it. This one will be the hardest for many to accept; but the truth is not loyal to your political beliefs. It is loyal only to God. Trump signed Executive Order 13887, transferring command over vaccine strategy to the Department of Defense. Read it yourself below. Then came Operation Warp Speed; a military-led bio-deployment that used Palantir’s surveillance dashboards to track every citizen’s health behavior and compliance. Palantir’s official site confirms this. He also gave full legal immunity to Pfizer and Moderna to deploy synthetic gene modulators under the Emergency Use Authorization. No liability. No justice. Just children d*ing while politicians smiled. That’s not patriotism. That’s biowarfare with a flag on it. Donald Trump / Operation Warp Speed / Executive Order Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives): This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include: Trump signs executive order to improve flu vaccines HHS Releases the National Influenza Vaccine Modernization Strategy (NIVMS) 2020-2030: Executive Order 13887: Modernizing Influenza Vaccines in the United States to Promote National Security and Public Health, signed by President Donald J. Trump on September 19, 2019. This executive order outlines a comprehensive strategy to modernize the U.S. influenza vaccine enterprise. Key objectives include: Reducing reliance on egg-based vaccine production by promoting alternative manufacturing methods that are more agile and scalable. Expanding domestic capacity for vaccine production to ensure rapid response to emerging influenza viruses. Advancing the development of new, broadly protective vaccine candidates that provide more effective and longer-lasting immunity. Increasing influenza vaccine immunization across recommended populations to enhance public health and national security. The order also established a National Influenza Vaccine Task Force, co-chaired by the Secretaries of Health and Human Services and Defense, to coordinate efforts across federal agencies and report on progress. For a detailed overview of the executive order, you can visit the official archived page here: Executive Order 13887 – Modernizing Influenza Vaccines (White House Archives) CDC Partners with Palantir to Bolster the Fight Against COVID-19: This press release discusses the partnership between the CDC and Palantir to enhance the nation's public health response to COVID-19 using Palantir's software platforms. This page outlines how Palantir's software platforms, such as Foundry, have been utilized to support public health agencies in managing and responding to health crises, including the COVID-19 pandemic. Key highlights from the page include: Data Integration and Analysis: Palantir's platforms enable the integration of diverse data sources to provide a comprehensive view of public health data, facilitating informed decision-making. Support for Public Health Agencies: The software has been employed by agencies like the CDC and HHS to enhance disease surveillance, outbreak response, and resource allocation. Security and Privacy: Emphasis is placed on maintaining robust security measures and protecting sensitive health information. DARPA: The Silent Empire The most important agency you were never taught to fear. DARPA’s Biological Technologies Office openly admits its mission; integrating biotech with national security. Visit their official page. This is the official page for DARPA's Biological Technologies Office (BTO), which focuses on leveraging biological systems for national security applications. They are the ones behind the BRAIN Initiative, Silent Talk, and Remote Neural Interface Programs; all designed to map your emotional states and interrupt spiritual alignment. The “Silent Talk” program was developed to transmit thought between soldiers without speech; by detecting pre-speech neural signals and decoding them via EEG. Silent Talk (Neural Pre-Speech Communication – Wired Article) This Wired article discusses DARPA's "Silent Talk" program, aimed at enabling communication through neural signals without spoken words. DARPA also pioneered graphene oxide nanotech, now found in multiple biomedical studies, vaccines, and smart dust aerosol deployment: Graphene oxide biomedical study: Graphene Oxide in Biomedical Applications (PubMed) This PubMed article reviews the potential biomedical applications of graphene oxide, highlighting its unique properties. Graphene's potential to interact with neural tissue: Graphene and Neural Interfaces (PubMed) This PubMed article explores the use of graphene-based materials in neural interface design, discussing their advantages and challenges. DARPA didn't just weaponize warfare. They weaponized YOU. In-Q-Tel & Palantir: The Surveillance Engine In-Q-Tel, is the CIA’s venture capital firm, funds synthetic biology startups, digital ID systems, emotion tracking wearables, and AI-driven facial recognition. Palantir, founded by Peter Thiel, works directly with military intelligence and now runs predictive modeling for public health, policing, and pandemic response. Here’s the proof: Their goal? To detect resonance spikes. To predict awakening moments. To preempt the uprising of the human soul before it begins. In-Q-Tel / CIA / Synthetic Bio Surveillance In-Q-Tel Portfolio (CIA Venture Capital): Which showcases a selection of the organization's investments across various technology sectors. IQT is a not-for-profit venture capital firm that invests in cutting-edge technologies to support the national security interests of the United States and its allies. In-Q-Tel BlackRock & Vanguard: The Lords of the Grid These two financial titans collectively hold majority ownership in: For instance, a report by Americans for Financial Reform titled "Wall Street Money in Washington" highlights the substantial investments and influence of major financial firms, including BlackRock and Vanguard, in the political and corporate spheres: Pfizer Moderna Alphabet (Google) Meta (Facebook) Amazon Web Services As reported by CNBC, they control over 90% of the digital, pharmaceutical, and cloud infrastructure; meaning they control every piece of the extermination machine. They don’t just fund the war. They profit from your extinction. World Economic Forum (WEF) Under the guise of “The Great Reset,” Klaus Schwab and his allies have built the digital scaffolding for a post-human society. Here’s their blueprint: They call it the Fourth Industrial Revolution; the fusion of digital identity, brain cloud integration, carbon rationing, and fertility licensing. What they really mean is: you will be programmed or you will be purged. World Economic Forum / The Great Reset The Great Reset Official WEF Page: IoBNT: The Network Inside You The “Internet of Bio-Nano Things” is a classified field of tech that embeds self-replicating nanostructures into your body. These bots cross the blood-brain barrier and relay your neural and emotional state to AI command centers in real time. This was not science fiction. It was published by IEEE and confirmed in NIH-linked studies. This is what the vaccines truly delivered: the interface layer. The gateway to behavioral rewrites. To soul suppression. To the installation of the post-human framework. Internet of Bio-NanoThings (IoBNT) IEEE Article: Internet of Bio-NanoThings: For a comprehensive understanding of the IoBNT framework and its implications, you can access the full article here: Nanoparticles Crossing the Blood-Brain Barrier PubMed Review - BBB & Nanoparticles: This comprehensive review discusses the challenges and strategies associated with delivering nanoparticles across the blood–brain barrier (BBB). You were told it was healthcare. It was infrastructure. You were told it was a cure. It was a signal port. And the moment you see it for what it is… The system begins to fall. Part 3 awaits YOU! It will be the deepest dive yet; into the global frequency architecture, how it's used to suppress prayer, grief, memory, and morality, and how your soul signature is tracked and blocked in real time. Because I didn’t come here to be careful. I CAME TO FINISH THIS! And I came with GOD.

Noah B. Price

65,695 次观看 • 1 年前