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๐Ÿš€ ๐๐ซ๐ž๐ฌ๐ž๐ง๐ญ๐ข๐ง๐  ๐š ๐ฉ๐š๐ฉ๐ž๐ซ ๐ข๐ฌ ๐š๐ง ๐š๐ซ๐ญ!๐ŸŽค ๐Ÿค” Ever felt that most presentation tools lack flexibility and creativity? ๐˜”๐˜ฆ๐˜ณ๐˜ฆ๐˜ญ๐˜บ ๐˜ฆ๐˜น๐˜ต๐˜ณ๐˜ข๐˜ค๐˜ต๐˜ช๐˜ฏ๐˜จ ๐˜ค๐˜ฐ๐˜ฏ๐˜ต๐˜ฆ๐˜ฏ๐˜ต, ๐˜ง๐˜ฐ๐˜ณ๐˜ค๐˜ช๐˜ฏ๐˜จ ๐˜ณ๐˜ช๐˜จ๐˜ช๐˜ฅ ๐˜ฅ๐˜ฆ๐˜ด๐˜ช๐˜จ๐˜ฏ๐˜ด, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ฅ๐˜ฆ๐˜ฎ๐˜ข๐˜ฏ๐˜ฅ๐˜ช๐˜ฏ๐˜จ ๐˜ฎ๐˜ข๐˜ฏ๐˜ถ๐˜ข๐˜ญ ๐˜ต๐˜ธ๐˜ฆ๐˜ข๐˜ฌ๐˜ด. ๐„๐ฏ๐จ๐๐ซ๐ž๐ฌ๐ž๐ง๐ญ changes all of that! โœจ EvoPresent is a self-optimizing framework that unites storytelling, design, and feedback to create effortless, engaging...

18,255 views โ€ข 11 months ago โ€ขvia X (Twitter)

11 Comments

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

๐Ÿงต1/N ๐Ÿ”ฅ If you're tired of traditional, one-dimensional presentation tools, EvoPresent breaks these limitations through self-optimization, improving both content expression and design beauty, making every presentation more engaging.

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

๐Ÿงต2/N The EvoPresent framework consists of 4 key modules, each continuously optimizing the presentation quality: 1โƒฃ Storyline Agent extracts key information from the paper and builds a clear, logical storyline. 2โƒฃ Scholar Agent enhances the academic content, making the presentation deeper and more insightful. 3โƒฃ Design Agent handles the slide layout and visual optimization, ensuring the perfect blend of content and design. 4โƒฃ Checker Agent evaluates both content and design, providing precise feedback to ensure continuous improvement of the presentation quality. ๐Ÿ”„โœจ

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

๐Ÿงต3/N: multi-task RL aesthetic model - PresAesth At its core is a multi-task reinforcement learning (RL) aesthetic model, PresAesth, focused on aesthetic scoring, defect correction, and comparison reasoning for slides. Through iterative evaluation and feedback on the design, PresAesth assesses the aesthetic quality of each slide, ensuring the visual design is both captivating and meets academic presentation standards. ๐ŸŽจ๐Ÿ‘€

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

๐Ÿงต4/N: EvoPresent Benchmark To ensure the effectiveness of EvoPresent, we introduce a comprehensive evaluation framework, EvoPresent Bench, focusing on two main perspectives: 1โƒฃ Presentation Quality, which integrates data from 650 top AI papers and various formats (slides, videos, scripts) to assess content and design quality. 2โƒฃ Aesthetic Awareness, covering 2000+ slide pairs, focusing on aesthetic scoring, defect correction, and design comparison.

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

๐Ÿงต5/N: High-quality feedback is the key to EvoPresent's self-improvement. Each round of feedback helps the presentation improve continuously, enhancing both content and design with every iteration. Unlike other tools, EvoPresent's self- optimization mechanism rapidly enhances the presentation through ongoing feedback, making it more engaging with each update. ๐Ÿ”„โœจ

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

๐Ÿงต6/N Compared to traditional tools, EvoPresent excels in content consistency, design quality, and visual appeal. Through its self-feedback mechanism, EvoPresent continuously optimizes aesthetic and design elements, resulting in presentations that surpass other existing automated generation tools. ๐Ÿ”ฅ

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

Kudos to our students @liuchen02938149 (co-lead) and @Toby_Yang_7 (co-lead), @KaiwenZhou9, @YFan_UCSC, @zhenzhangzz, and our fantastic Uniphore collaborators Yanan Xie and @qi2peng2. Everything is open sourced and now you can effortlessly turn your paper into a video/slides presentation with ease! ๐ŸŒWebsite: ๐Ÿ—’๏ธPaper: ๐Ÿ’ปCode:

Xiangru (Edward) Jian's profile picture
Xiangru (Edward) Jian11 months ago

Very cool work! Will surely try it for my Neurips papers. Also very happy to see our Paper2Poster get followed up. @real_weipang @KevinQHLin

Xin Eric Wang's profile picture
Xin Eric Wang11 months ago

@real_weipang @KevinQHLin Thanks! Comment your paper here and we are happy to generate slides / video presentation for you! @liuchen02938149

Xiangru (Edward) Jian's profile picture
Xiangru (Edward) Jian11 months ago

@real_weipang @KevinQHLin @liuchen02938149 Working on camera ready lol

Kevin Lin's profile picture
Kevin Lin11 months ago

Congra. for the great work! The multi-task RL is amazing!! We recently also release a relevant work -- Paper2Video ( Let us work together to advance the AI-human co-scientist! ๐Ÿ˜†

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A dog just made the bravest decision I have seen anyone make this year. Not a founder. Not an athlete. Not a person with a plan and a five-year vision board. A dog, on an empty road, with nothing to lose and no idea what would come next. I have watched what comes next more times than I will admit in public. This post is 25,000 characters long. It is a list of reasons why you should watch it too. Read as much as you want, but understand one thing before you start: the video is the only part that matters, and this is everything the video doesn't have room to say. Sound on. Phone in both hands. Do not skip. I'll be here when you get back. THE NUMBER THAT SHOULD BOTHER YOU Let me start with two numbers. The first: commonly cited estimates put the world's stray dog population at around 200 million. Two hundred million animals with no address, no bowl with their name on it, and no one who would notice if they didn't come back tonight. The second number is one. 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Link two: someone has to be present. Not nearby. Present. Eyes up, phone down, brain not busy replaying the argument from breakfast. Link three: that someone has to notice. It sounds simple. It isn't. The human brain is a filtering machine, and a small animal on a road becomes a plastic bag, a shadow, a piece of tire. The most common reason a dog is not rescued is not cruelty. It is that nobody registered it as a dog. Link four: the person has to stop. This is the link that snaps most often. Seeing is free. Stopping costs you time, comfort, a schedule, and possibly the mood of your entire day. Link five: the dog has to let them. An animal that has learned that hands mean pain has every biological reason to run. Trust is not a given. It is a negotiation, and the dog holds the veto. Five links. All five held. Remember that when you press play. You are not watching a nice story. You are watching a chain that should have snapped at least four times. THE PEOPLE WHO KEEP DRIVING In 1968, psychologists John Darley and Bibb Latane published a set of experiments that changed how we think about helping. The finding was uncomfortable: the more people who witness an emergency, the less likely any one of them is to act. They called it diffusion of responsibility. Everyone assumes someone else will handle it. So nobody does. Later research added nuance. When an emergency is clear and dangerous, people step in more often than the original theory predicted. But the core insight has survived half a century of testing, because it describes something every one of us has felt: the small, quiet voice that says, somebody else will stop. Now picture a road with no crowd at all. No audience. No one to hide behind. No one to blame. Just you and a decision that is entirely, inescapably yours. That is the situation the person in this video walked into. And the reason it is worth your attention is not that they did something impossible. It is that they did something small, and it turns out small is exactly what almost nobody does. You don't need to be a hero. You need to be inconvenienced. THE FACE IS THE RESUME In 2013, researcher Bridget Waller and her team studied dogs in a UK shelter and asked a simple question: what makes one dog get adopted faster than another? It wasn't size. It wasn't age. It wasn't coat color. It was one tiny facial movement: the raising of the inner eyebrows. The move that makes a dog's eyes look bigger, softer, almost sad. Dogs that did it more often were chosen faster. Six years later, a study led by Juliane Kaminski found out why that movement is so easy for dogs and so hard for wolves. Dogs have a small muscle around the eye that wolves largely lack. Over thousands of years of living beside us, dogs evolved a way to make their faces speak our language. Read that again. A species rewired its own anatomy to be understood by another species. No other animal has done this to us. Nobody taught them. Nobody forced them. They looked at us, worked out what we respond to, and grew the tool. Now look at the face in this video. You will know the second you see it. That is not a coincidence, and it is not luck. It is fifteen thousand years of engineering aimed directly at your chest. THE ONLY LOOP LIKE IT ON EARTH In 2015, a Japanese team led by Miho Nagasawa published a result in the journal Science that made researchers stop and reread the abstract. When a dog and its owner look into each other's eyes, both of their oxytocin levels rise. Oxytocin is the bonding chemical, the same one that flows between a mother and her newborn. Dog looks at human. Human's oxytocin rises. Human looks back, touches, talks softly. Dog's oxytocin rises. Which makes the dog look longer. Which makes the human's oxytocin rise again. A feedback loop of affection, running across two species, powered by nothing but eye contact. 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The dogs got it right nearly 94 percent of the time. Your body broadcasts your emotional state as chemistry. You cannot turn it off. You cannot fake calm. A dog reads your fear, your tension, your irritation, before you have opened your mouth. Which means every rescue is, at its core, a test of one thing: are you actually calm, or are you performing calm? The dog knows. It always knows. And that is why what happens in the first few seconds of this video matters more than anything that comes after it. Watch the body language. Watch how slowly things move. Watch what is not done. THE MOST IMPORTANT MOMENT IN ANY RESCUE IS THE ONE WHERE NOTHING HAPPENS Animal behaviorists describe fear responses in four flavors: fight, flight, freeze, and fawn. Fight is what people expect. Flight is what most strays do. Freeze is what looks like calm but isn't. And fawn, the desperate, wiggling, please-don't-hurt-me appeasement, is the one that breaks your heart the fastest, because it looks like friendliness and it is actually terror. Rescuers who have done this hundreds of times will tell you the same handful of rules. Don't loom. Don't stare straight into the eyes. Get low. Turn sideways. Slow everything down until it feels absurd. Let the animal close the last few feet on its own terms. The hardest instruction, and the one most people can't follow, is the last one: do nothing. Every instinct you have says reach out. Grab. Fix. Take control of the situation. And every good rescue begins with someone who did the opposite. Who made themselves small, patient, and boring, and waited for a frightened animal to decide that the safest thing in its whole world might be a stranger. You are about to watch someone do exactly that. Notice how little they need to say. THE TEARS THEY WON'T PUT IN THE HEADLINE Scientists are careful people. They do not like to say "dogs cry." But in 2022, a team from Azabu University in Japan, led by Takefumi Kikusui, measured tear volume in dogs during reunions with their owners. The result: tear volume rose significantly compared with reunions involving other familiar people. And when researchers applied oxytocin to the dogs' eyes, tear volume rose again. Not sadness crying. Not the crying we do. Something else, something closer to overflow. The body producing water at the exact moment the heart has more in it than it can hold. Nobody has proven that this is the same thing we feel. Scientists will tell you that, and they are right to. But here is a question worth sitting with. If an animal's eyes fill with water when it sees the one being it has decided to trust, what exactly are we arguing about? Watch the eyes in this video. Then tell me what you think you saw. ONCE IT HAS A NAME, IT STOPS BEING A STATISTIC In 2007, psychologist Paul Slovic and colleagues ran an experiment on generosity. They showed people a fundraising appeal for a hungry child, and then a second version that added statistics about millions of other children in the same crisis. More data. More context. More reasons to care. Donations dropped. Slovic called it psychic numbing. The human mind can hold one face. It cannot hold two hundred million. When a tragedy becomes a number, empathy quietly switches off, and we don't even notice it happening. This is why one named animal in one small video can do what a hundred reports full of charts cannot. It gives your brain something it can actually care about: a single life, with a face, a fear, and a future that could go either way. The stray population is a statistic. A dog is a story. And stories, unlike statistics, come with a name at the end. When you reach that moment in the video, pay attention to what it does to you. Notice the small shift in your chest. That is the sound of a number turning into a person, or close enough. THE WORD FOR WHAT YOU'RE ABOUT TO FEEL Researchers have a name for the feeling you get when something touches you so suddenly that your throat tightens and your eyes sting. They call it kama muta, Sanskrit for "moved by love." Anthropologist Alan Fiske proposed that it is a distinct emotion, triggered by a sudden intensification of closeness. Two beings who were strangers become bonded. Someone who was alone becomes part of something. People across many cultures describe the same set of signs: warmth in the chest, goosebumps, a lump in the throat, tears they didn't plan on, and a strong urge to hug someone or hold something. Here is what makes it useful and not just sweet: kama muta is one of the most reliable emotional responses we have. It shows up when reunions happen. When a stranger helps unexpectedly. When an animal, after a long time alone, is finally held. You've felt it. You just never had a word for it. Take note of the exact second it hits you in this video. I promise there is one. And if you're the kind of person who says "I never cry at videos," I would like to schedule a follow-up. WHY YOU'LL WANT TO BE A BETTER PERSON AFTER ONE MINUTE Psychologist Jonathan Haidt studied a related feeling and gave it a name: elevation. Elevation is what you feel when you watch someone do something morally beautiful, quietly, with nothing to gain. It is not envy and it is not admiration. It is an urge, physical and immediate, to do something good yourself. In studies, people who experienced elevation were more likely to help others afterward, more likely to volunteer, and more likely to describe wanting to become better versions of themselves. Read that as a design spec. A short piece of true, unstaged kindness can change what a person does in the hour after they see it. Which is a strange, lovely thing for a phone to be capable of. We spend so much time discussing what social media does wrong. Nobody wonders what would happen if the best five percent of it, the small, real, human moments, were the part that traveled farthest. Let this one travel. It has earned it. THE RARE THING: SOMETHING TRUE THAT WINS In 2018, researchers at MIT published a study in Science that analyzed millions of tweets. The result was grim: false news spread significantly faster and further than true news. False stories were about 70 percent more likely to be retweeted, driven largely by surprise and disgust. The lesson most people took away was that this platform rewards outrage. I want to take a different lesson. If false stories win because they trigger strong emotion, then true stories can win too, as long as they trigger stronger ones. A video with no villain, no scandal, and no argument. Nothing to be angry about. Nothing to dunk on. A rescue that is exactly what it looks like. That kind of content should lose on this platform. It has no fuel. And yet every so often, one of them breaks through and reminds everyone what this place was supposed to be. I am not asking you to like it. I am asking you to notice that you had a choice about what to feed today, and this was one of the options. SOME FRIENDSHIPS SHOULDN'T WORK Somewhere near the end of this video, a second character enters the story. I won't tell you who. I won't tell you what happens. I will tell you that if you have ever read anything about instincts, hunting drives, or the way certain animals are supposed to see each other, this moment will quietly rearrange your assumptions. Behaviorists talk about prey drive as if it were destiny. It is not. It is a tendency, and tendencies can be softened by experience, by safety, by being raised, or re-raised, in a place where no one is afraid. The same dog that once had to look after itself alone can, in a different life, learn that the world contains creatures that are not threats or meals. Only neighbors. That is the most hopeful idea in behavioral science, and it usually gets buried in footnotes: what an animal was is not the same as what an animal can become. The same is true for most of us, incidentally. But that is a different post. Stay for the ending. It is the reason I am writing this at all. THE PART THE INTERNET NEVER FILMS Every rescue video has the same shape: the meeting, the rescue, the transformation, the happy ending. It is edited that way because it is the only shape that gets watched. But ask anyone who has actually done this, and they will tell you the truth is in the gap between the second and third act. The first night. The first week. The first time a dog that has never lived indoors realizes there is a floor that doesn't move, a door that closes without danger, and a bowl that will be full again tomorrow. Rescuers have a rule of thumb for this, the 3-3-3 rule. Three days for a dog to decompress. Three weeks to start learning the routine. Three months to feel truly at home. It's not science, exactly, just a shorthand built from thousands of adoptions. But it captures something real: safety is not a switch. It is a process, and the animal has to believe it slowly, one uneventful day at a time. That means the happiest scenes in this video are not the ones that look like celebrations. They are the quiet ones. A dog that stops scanning the room. A body that finally lets go. Look for the moment the shoulders drop. Once you see it, you'll never unsee it. THE COST OF STOPPING: NINETY SECONDS Let's do the math on the thing that most people are afraid of. How long does it actually take to stop for an animal in trouble? Not the whole rescue. Just the decision, the pulling over, the first attempt. Ninety seconds. Sometimes less. Ninety seconds is the length of a bad song on the radio. It is the time you spend waiting for a light to change. It is a scroll through a feed you won't remember. And on the other side of those ninety seconds is the difference between a living animal and a statistic. I'm not saying this to make anyone feel guilty. Guilt is a terrible motivator. It makes people avoid the feeling instead of acting on it. I'm saying it because the barrier is almost always imagined. We inflate the cost of helping in our heads, and the imagined price is what stops us, not the real one. The person in this video paid the real price. It was small. What they got in return is something no one could have planned for. That is the part you should watch closely. IF YOU'RE EVER THE ONE ON THAT ROAD Save this section. Someday, someone reading it will need it. Put your safety first. Pull over where it's safe and turn on your hazard lights before anything else. A second accident helps no one. Do not chase. A frightened dog runs faster than you and directly into the worst possible place. Chasing turns a rescue into a pursuit. Get low and go slow. Sit down if you can. Turn your body sideways. Avoid direct staring. Speak softly, or don't speak at all. Use food, if you have any. Something plain, tossed a little closer each time, works better than any technique. Check for a tag and, if you can get near enough, ask a vet or shelter to scan for a microchip. Someone may be looking for this animal right now. Call for help early. Local rescues, animal control, and vets can handle what you cannot. Sometimes the bravest thing you can do is make the right phone call. Take photos and note the location. If you can't keep the animal, those details are what let someone else finish the job. None of this is complicated. The reason it is rare is that most people have never been told that it is allowed. You are allowed. THE REAL STAKES OF A SMALL DOG Here is a bigger picture, and it's a heavy one. Millions of companion animals enter shelters every year in the United States alone. That is just one country. Many are lost pets that never get reclaimed. Many are strays. Many are animals whose owners ran out of money, time, or hope. Shelters are often crowded, underfunded, and staffed by people running on love and very little else. Every animal that finds a home, or a foster, or a stranger with ninety seconds to spare, frees up a space for the next one in line. That means every single rescue is bigger than the animal in it. It is a small change to a very large system, and the system is nothing but small changes stacked on top of one another. This is not an argument for guilt. It's an argument for scale. One dog saved is one dog saved, but it is also proof of concept, a demonstration that the chain can hold, that the odds can be beaten, that a person and a road and a decision can end well. And proof of concept is contagious. That is why you are seeing it. WHO REALLY GOT RESCUED? If you talk to people who have taken in strays, you'll hear the same sentence over and over, in different words. "I thought I was saving him. It turned out he was saving me." Skeptics roll their eyes at that. It sounds like a greeting card. And research on pets and wellbeing is more mixed than social media would like. It doesn't say every dog fixes every life. But there is something real underneath it, and it's not mystical. A dog is a machine for creating routine, attention, and reasons to leave the house. It needs you at a certain hour. It notices when you come home. It doesn't care about your job title, your follower count, or what you failed at last week. For some people, that is the first unconditional witness they have had in years. The rescue, in this light, is not one-way. Two lonely creatures, one who knew it and one who didn't, found out that they could take care of each other. Nobody can prove that from a video. But there is a version of the story that runs in the background of every rescue, and you can feel it if you let yourself. Tell me whether you feel it here. THE ATTENTION PARADOX Here is a strange fact about the platform you're reading this on. The average post gets a glance. A few words, a flick of the thumb, gone. Brands spend billions every year trying to buy three seconds of your attention, and most of what they buy evaporates before it lands. And yet a video of one dog, with no budget, no celebrity, and no script, can hold a stranger for a full minute. Without a single trick. Why? Because attention is not really about tricks. It is about stakes. Your brain is built to track living things whose outcome is uncertain. The moment there is a creature on screen and you don't yet know if it will be okay, some ancient part of you leans in and refuses to look away. That is the secret behind every great story ever told. Someone we care about. Something that could go wrong. A question we need answered. Marketers call it a hook. Your nervous system calls it worry. This video has both, and it pays off the worry honestly, which is why you leave feeling better instead of used. That is rare enough to deserve a full minute of your life. HOW TO WATCH THIS Most people will watch it wrong. They'll half-look at it between two other things, mid-scroll, thumb already moving. Here is how to get the actual effect. Turn the sound on. There is more happening in the audio than you expect. Make it full screen. This is a story about faces, and faces need room. Watch the first ten seconds without expecting anything. The film is quiet at the start. That is deliberate, or at least it works as if it were. Do not skip ahead. The whole thing depends on the distance between where it starts and where it ends. Skip the middle and the ending is just a nice clip. Then, once it's over, watch it again. The second time, you won't be watching for the story. You'll be watching for the small things you missed: a hesitation, a glance, a change in how a body carries itself. That second watch is where it gets you. I said I have watched it more times than I'll admit. That is the honest reason. It doesn't wear out. It gets deeper. THE CHALLENGE I want to try something with this post. If the video moved you, leave one comment: the second it happened. Not a review, not an analysis. Just the moment. I'm curious whether it's the same one for everyone. My guess is that it isn't, and that the spread of answers will say more about what people carry around with them than about the video. If it didn't move you, that is fine too. I'd like to hear that as well. Honest is better than polite. And if you have ever been the one who stopped, and I know some of you have, write that instead. Tell the story in two lines. No one has ever regretted the ninety seconds. Someone reading this thread might need to know that. Reposting this is the simplest way to put it in front of someone who's scrolling right now, in a bad week, thinking that nothing good happens by accident anymore. Something did. THE LAST THING Let me end where I started. A dog made a decision on an empty road. It could not have known how it would turn out. It had no reason to believe that the next hand would be different from the last. It went ahead anyway. That is the whole difference between a life that changes and one that doesn't. Not certainty. Not a plan. A willingness to move toward the unknown when the alternative is more of the same. The animal in this video did that. Then someone did the same in return. That's it. That's the entire story. Two beings, each of whom took a small, terrifying step toward the other, and a road that was, for a few seconds, the most important place in the world. Scroll up. Press play. Watch the ending. Then come back and tell me I was exaggerating. P.S. If you read all of this, you are exactly the kind of person this video was made for. Most people never make it past the first screen of a long post. You did. That tells me you are someone who stays: through the slow part, through the uncertain part, all the way to the end. Which is, when you think about it, the only quality that mattered in the story you're about to watch. Follow for more like this. I only post the ones that earn it. Bookmark it for days you forget the feeling. #Rescue #DogsOfX #SecondChances #AdoptDontShop #Dogs #AnimalRescue #RescueDog

Earth Unveiled

15,706 views โ€ข 5 days ago

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 Iโ€™m doing in the demoโ€”take a curated collection of sources and quickly transform them into a detailed document that obeys strict guidelinesโ€”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 Iโ€™m in control of the document that is being generated here โ€” itโ€™s based on the information that I have curated, and on the instructions Iโ€™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 Iโ€™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 โ€ข Begin by exploring the question: "What kind of problem is a city?" โ€ข Introduce Jane Jacobs' key ideas about urbanism, focusing on: โ€ข The importance of diversity in uses, buildings, and populations for vibrant city life. โ€ข The role of sidewalks and "eyes on the street" in ensuring safety and fostering a sense of community. โ€ข The value of old buildings in supporting diverse economic activity and fostering innovation. โ€ข The dangers of "single-use" zoning and the importance of mixed-use neighborhoods. โ€ข 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: โ€ข Observing the built environment, including streetscapes, building types, and public spaces. โ€ข Identifying areas where Jacobs' principles are evident or lacking. โ€ข Analyzing the neighborhood's strengths and weaknesses. โ€ข 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: โ€ข A panel of local urban planners, architects, or community members. โ€ข A public forum or community meeting. โ€ข 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 views โ€ข 1 year ago

$NWBO #๐——๐—–๐—ฉ๐—ฎ๐˜…-๐—Ÿ: ๐—ง๐—ต๐—ฒ ๐—˜๐˜ƒ๐—ถ๐—ฑ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ถ๐—ป ๐—ฃ๐—น๐—ฎ๐—ถ๐—ป ๐—ง๐—ฒ๐—ฟ๐—บ๐˜€ A short, plain-language reading of the survival evidence for DCVax-L in #glioblastoma, and what it means under the MHRAgovuk guideline on external control arms. ๐Ÿ“Š ๐—ฃ๐—”๐—ฅ๐—ง ๐—ข๐—ก๐—˜: ๐—ช๐—›๐—”๐—ง ๐—ง๐—›๐—˜ ๐—ง๐—ฅ๐—œ๐—”๐—Ÿ ๐—™๐—ข๐—จ๐—ก๐——, ๐—”๐—ก๐—— ๐—ช๐—›๐—ฌ ๐—œ๐—ง ๐— ๐—”๐—ง๐—ง๐—˜๐—ฅ๐—ฆ DCVax-L more than doubled five-year survival, and the benefit is durability: a subset gets lasting disease control and simply stays alive. ๐Ÿ’‰ ๐—ช๐—ต๐—ฎ๐˜ ๐˜๐—ต๐—ฒ ๐—ฑ๐—ฟ๐˜‚๐—ด ๐—ถ๐˜€ DCVax-L is a personalized cancer vaccine for glioblastoma, the deadliest form of brain cancer and a designated orphan disease. It is a living drug: its active ingredient is the patient's own immune cells, primed with proteins from that patient's surgically removed tumor, so the immune system learns to attack the cancer. Unlike a chemical drug that is metabolized and cleared, it switches on a living immune response that keeps working long after the injection. Glioblastoma comes back in almost everyone: even with the full standard of surgery, radiation, and temozolomide chemotherapy, most patients live under two years, and only about one in twenty reaches five. DCVax-L is given on top of that standard care, not in place of it: every patient in the trial received surgery, radiation, and temozolomide, and the vaccine was added to it, so the comparison measures what the vaccine adds. For two decades, nearly every new drug tried in this disease has failed. That is the backdrop against which any positive result must be judged. ๐Ÿ“ˆ ๐—ช๐—ต๐—ฎ๐˜ ๐˜๐—ต๐—ฒ ๐˜๐—ฟ๐—ถ๐—ฎ๐—น ๐—ณ๐—ผ๐˜‚๐—ป๐—ฑ In a Phase 3 trial of 331 patients, those who received DCVax-L lived longer. At the median the gain looks modest, about three months (19.3 versus 16.5). The number that matters sits at the far end of the survival curve: more than twice as many vaccine patients were alive at five years, 13.0% versus 5.7%, and a few reached ten years in a disease that usually kills within three. In patients whose tumor had already returned, the effect was larger still, cutting the risk of death by about 42%. ๐Ÿ‘ฅ ๐—˜๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐—ด๐—ฟ๐—ผ๐˜‚๐—ฝ ๐—ฏ๐—ฒ๐—ป๐—ฒ๐—ณ๐—ถ๐˜๐—ฒ๐—ฑ, ๐—ฒ๐˜ƒ๐—ฒ๐—ป ๐˜๐—ต๐—ฒ ๐—ต๐—ฎ๐—ฟ๐—ฑ๐—ฒ๐˜€๐˜ ๐˜๐—ผ ๐˜๐—ฟ๐—ฒ๐—ฎ๐˜ The benefit was not confined to the easy cases. Of the six prespecified subgroups the trial examined, every single one favored DCVax-L, and there was no group in which it did worse than standard care. The largest gains came in patients whose tumors carry MGMT methylation, who reached a median survival of 30.2 months from randomization against 21.3 for the controls. But even the hardest-to-treat patients, whose tumors lack that methylation, resist standard chemotherapy, and carry the worst prognosis in this disease, still came out ahead with the vaccine, at a hazard ratio of 0.93. A treatment that helps across the whole population, and helps most where the biology is most favorable, is acting like a real drug. ๐Ÿ“‰ ๐—ช๐—ต๐˜† ๐˜๐—ต๐—ฒ ๐—บ๐—ฒ๐—ฑ๐—ถ๐—ฎ๐—ป ๐—ต๐—ถ๐—ฑ๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฟ๐—ฒ๐—ฎ๐—น ๐˜€๐˜๐—ผ๐—ฟ๐˜† That five-year number is the whole story, and the median buries it. Almost every treatment that ever helped in glioblastoma did the same modest thing: it slid the survival curve a few months to the right, then let it fall back. Doubling five-year survival is different in kind. A three-month gain at the median cannot, by itself, double the fraction alive at five years. The only shape that produces both numbers is a split: most patients get the small delay the median measures, while a subset gets durable disease control that lasts for years, well past where glioblastoma should have ended them. That subset is the long tail of the curve, and it is where the benefit lives. A median ignores extremes, the way a town's median income tells you nothing about its millionaires. The real story is not a longer delay; it is that a meaningful share of patients simply stay alive. ๐Ÿงฌ ๐—ช๐—ต๐˜† ๐˜๐—ต๐—ฒ ๐—ฏ๐—ถ๐—ผ๐—น๐—ผ๐—ด๐˜† ๐—ฝ๐—ฟ๐—ฒ๐—ฑ๐—ถ๐—ฐ๐˜๐˜€ ๐˜๐—ต๐—ถ๐˜€ ๐˜€๐—ต๐—ฎ๐—ฝ๐—ฒ The tail is not luck. It is what this biology is built to produce. The vaccine carries proteins from the patient's own tumor, so it aims the immune system at whatever that tumor is made of, not a fixed short list of targets. And it amplifies: one trained immune cell drives many others that multiply into cancer-killers. Andres Salazar, the neurologist who developed poly-ICLC into the clinical adjuvant given with the vaccine, puts it in a line: you start the fire, and you keep it burning. A response like that does not produce a one-time bump. It builds and widens over time. What matters is not just that a response forms, but what kind. Dendritic cells are the immune system's master switch for that, the cells that set what kind of attack the body mounts, and this vaccine is built from them. It drives what immunologists call a type 1 polarized response: an interferon-driven, cytotoxic program aimed squarely at the tumor. That direction comes from the vaccine itself; the poly-ICLC adjuvant given with it drives the same interferon program and sustains it. That is the active ingredient, and it has been measured. In UCLA studies of this approach, the patients whose immune systems mounted the strongest interferon response lived the longest. The response also spreads. In a different cancer, a vaccine carried on this same poly-ICLC adjuvant drove more than 70% of a patient's cancer-killing T cells to target proteins that were never in the vaccine: the immune system outgrew its original targets and went after the rest of the tumor on its own. This is called epitope spreading, and it is not particular to one tumor; it is what this kind of response does, and it is the kind of response DCVax-L builds. That breadth is the likeliest thing separating the long-term survivors from everyone else, a response that breaks past its targets and clears the disease rather than one that stays caged and stops. There is even a tell in who benefits most: the effect is largest in tumors whose biology builds up more mutations under chemotherapy, and more mutations mean more targets for a whole-tumor vaccine to find. The same logic explains what the vaccine is not, and what it does not need. Checkpoint inhibitors, the drugs that release the immune system's brakes, have failed on their own in glioblastoma because there was no active response to release; the vaccine supplies that response first. That makes the vaccine the natural foundation for combination therapy. Combining it with its poly-ICLC adjuvant, made by Oncovir, has already shown meaningful survival gains in a published analysis. In the pivotal trial, the vaccine's proven benefit came added on top of standard chemotherapy and radiation; the newer question is how much the immune response can carry on its own. A UCLA trial is now testing that in patients whose tumors have returned, adding #Keytruda (pembrolizumab), the checkpoint antibody from $MRK, in a regimen built entirely around the immune response with no chemotherapy or radiation in it at all. Its interim survival curve shows the shape the biology predicts. In the arm given the vaccine and Keytruda together after surgery, the curve does not fall away but flattens into a plateau, with roughly 65% of patients still alive well past the point where recurrent glioblastoma kills nearly everyone. That plateau is the signature of a response that took hold and lasted, the type 1 attack forming durable immune memory so that once the disease is controlled it stays controlled. That is where this points, and where it is already arriving, a treatment that works through the response itself, one that could in time lean less on the harsh radiation and chemotherapy that have defined glioblastoma care and barely moved its survival. These are interim results, from Prins, Cloughesy, and Liau at UCLA. ๐Ÿ” ๐—ฃ๐—”๐—ฅ๐—ง ๐—ง๐—ช๐—ข: ๐—œ๐—ฆ ๐—œ๐—ง ๐—ฅ๐—˜๐—”๐—Ÿ? The trial was randomized, an independent experiment shows the outside comparison is trustworthy, and every separate check points the same way. ๐Ÿค” ๐—ง๐—ต๐—ฒ ๐—ผ๐—ฏ๐—ท๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป, ๐—ฎ๐—ป๐—ฑ ๐˜„๐—ต๐˜† ๐—ถ๐˜ ๐—บ๐—ถ๐˜€๐˜€๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—บ๐—ฎ๐—ฟ๐—ธ So much for what happened; the harder question is whether to believe it. The trial has the feature critics attacked: it could not keep a normal placebo group, because patients assigned to placebo were allowed, by design and by medical ethics, to switch to the vaccine once their cancer returned, and almost all did. That erased the internal comparison, so survival was measured against closely matched patients from other completed trials, an approach called an external control, which critics argued could tilt toward the vaccine. What the objection misses is where the randomization went. This was a randomized, blinded trial. The patients who got the vaccine were assigned to it at random, not hand-picked, so the treated group is an ordinary slice of the trial population, not a favorable one. The crossover removed the placebo group but never touched how patients were assigned. That leaves exactly one place for bias to enter, the outside comparison group, which is precisely what the next checks test. โœ… ๐—ง๐—ต๐—ฒ ๐—ฐ๐—ต๐—ฒ๐—ฐ๐—ธ ๐˜๐—ต๐—ฎ๐˜ ๐—บ๐—ฎ๐—ธ๐—ฒ๐˜€ ๐—ถ๐˜ ๐˜๐—ฟ๐˜‚๐˜€๐˜๐˜„๐—ผ๐—ฟ๐˜๐—ต๐˜† Before trusting a scale to weigh something unknown, you confirm it reads zero with nothing on it. That is what the calibration does, and it is the strongest part of the case. A separate, independent randomized trial called INSIGhT was run through the very same external-control method, and it gave two answers. First, three experimental drugs that had already failed were run through it, and it correctly found nothing (hazard ratios of 1.00, 0.93, and 0.88): the method does not manufacture a benefit where none exists. Second, INSIGhT's external controls were set head to head against its own randomized internal controls, and they were statistically indistinguishable. In this disease, an external control reproduces the answer a real randomized control would have given, and because that trial belonged to a different group, no one can say a sponsor graded its own work. The one place bias could enter, the control side, is the one place an independent randomized experiment certified as clean. There is a deeper fit worth naming, and it is what makes the two halves of this case one. The same instrument that reported those three failures as failures reads the vaccine as a success, and the biology says why: those drugs could not hold a tumor this varied, and the vaccine builds the broad, lasting response that finally does. One method, opposite readings, and one mechanism behind both. The statistics and the biology are not two arguments. They are the same argument seen twice. ๐Ÿƒ ๐—ช๐—ฎ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐—ฟ๐—ถ๐˜€๐—ผ๐—ป ๐˜€๐˜๐—ฎ๐—ฐ๐—ธ๐—ฒ๐—ฑ ๐—ถ๐—ป ๐˜๐—ต๐—ฒ ๐˜ƒ๐—ฎ๐—ฐ๐—ฐ๐—ถ๐—ป๐—ฒ'๐˜€ ๐—ณ๐—ฎ๐˜ƒ๐—ผ๐—ฟ? A natural worry is that the outside comparison was arranged after the fact to flatter the vaccine. The trial was built to prevent that. The patients to compare against, and the rules for matching them, were fixed in writing before anyone saw results, and an independent firm, not the company, chose the comparison trials against those rules. The trial also switched its main measure partway through, from delaying tumor growth to overall survival, but that was not a maneuver: immune treatments cause a harmless swelling that mimics tumor growth on scans and made the growth measure unreliable, and the switch was made while everyone was still blinded. Three further checks point the same way. Survival in this disease has not improved over the years the comparison spans, so same-era controls are sound. When the borrowed controls were tested directly, the comparison came out conservative rather than flattering. And the controls were counted from the same point in the disease as the vaccine patients, so neither side got a head start. Where the comparison can err, it errs against the drug. ๐Ÿ”ฌ ๐—ง๐—ต๐—ฒ ๐—บ๐—ผ๐—ฟ๐—ฒ ๐—ฐ๐—ฎ๐—ฟ๐—ฒ๐—ณ๐˜‚๐—น ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜€๐—ถ๐˜€ ๐—บ๐—ฎ๐—ฑ๐—ฒ ๐˜๐—ต๐—ฒ ๐—ฏ๐—ฒ๐—ป๐—ฒ๐—ณ๐—ถ๐˜ ๐—ฏ๐—ถ๐—ด๐—ด๐—ฒ๐—ฟ, ๐—ป๐—ผ๐˜ ๐˜€๐—บ๐—ฎ๐—น๐—น๐—ฒ๐—ฟ The first comparison used whole groups. A sharper one became possible once patient-level records from three other trials could be obtained, pairing each vaccine patient with controls matched on the traits that drive survival in glioblastoma, above all MGMT methylation status, matched exactly, plus age, sex, extent of surgery, residual disease, and performance status. When the comparison got sharper, the benefit grew in every one of these analyses. The original cohort-level estimate was 2.8 months. Patient-level matching across the three trials put the gain between 3.4 and 6.3 months, and a method that weights patients rather than pairing them put it between 3.4 and 4.3, with several of the matched comparisons roughly doubling the original figure. The hazard ratio moved the same way, from 0.80 to between 0.69 and 0.77. The direction matters. A real effect blurred by crude matching gets clearer when the matching improves, while a biased one tends to shrink. It got stronger. ๐Ÿ•ต๏ธ ๐—›๐—ผ๐˜„ ๐—บ๐˜‚๐—ฐ๐—ต ๐—ต๐—ถ๐—ฑ๐—ฑ๐—ฒ๐—ป ๐—ฏ๐—ถ๐—ฎ๐˜€ ๐˜„๐—ผ๐˜‚๐—น๐—ฑ ๐—ถ๐˜ ๐˜๐—ฎ๐—ธ๐—ฒ ๐˜๐—ผ ๐—ฒ๐˜…๐—ฝ๐—น๐—ฎ๐—ถ๐—ป ๐˜๐—ต๐—ถ๐˜€ ๐—ฎ๐˜„๐—ฎ๐˜† A fair question is how much hidden bias it would take to erase the result. Statisticians measure that with the E-value, and here a hidden factor would have to be about as strong as age is on survival, would also have to drive who received the vaccine, and would have to have escaped the decades of research that mapped every known risk factor in this disease. A second, independent check, Rosenbaum's Gamma, comes at it from the other side, asking how large an unseen imbalance between matched patients it would take to break the result, and it reaches the same verdict. Every factor strong enough to matter was already matched. A hidden one that clears that bar is not plausible. ๐Ÿ”’ ๐—ช๐—ต๐˜† ๐˜๐—ต๐—ฒ ๐—ฟ๐—ฒ๐˜€๐˜‚๐—น๐˜ ๐—ถ๐˜€ ๐—ต๐—ฎ๐—ฟ๐—ฑ ๐˜๐—ผ ๐—ณ๐—ฎ๐—ธ๐—ฒ The strongest point is not any single result. It is that a hidden bias big enough to explain the effect away would have to produce the same answer in every independent test at once: โ€ข The independent randomized calibration trial. โ€ข Three separate comparison trials, drawn from different studies. โ€ข Two different statistical methods that handle the data in different ways. โ€ข A separate pooled analysis of other dendritic-cell vaccine trials. โ€ข The internal math of the survival curve, which points to the same result (about 0.71 at five years) that the patient matching found. And it would have to fall in the exact direction the biology predicted before any data existed: a slow, widening benefit concentrated in long-term survivors. A single hidden factor that could forge all of that at once is not a hidden factor. It is a coincidence that does not happen. ๐Ÿฉบ ๐—ฃ๐—”๐—ฅ๐—ง ๐—ง๐—›๐—ฅ๐—˜๐—˜: ๐—ช๐—›๐—”๐—ง ๐—œ๐—ง ๐— ๐—˜๐—”๐—ก๐—ฆ The drug is nearly free of harm, the evidence fits an established and approved regulatory path, and what remains unrun changes nothing about the case. ๐Ÿ›ก๏ธ ๐—ง๐—ต๐—ฒ ๐˜€๐—ฎ๐—ณ๐—ฒ๐˜๐˜† Two things decide whether a real effect reaches patients: whether the drug is safe enough to use, and whether regulators will accept the evidence. The first is settled. Across 2,151 doses, only five serious side effects were even possibly related to the vaccine, with no autoimmunity and no cytokine storm. It is made once, in about eight days, then stored and given as a simple injection. When a treatment barely harms, the benefit needed to justify it falls, and the benefit here clears that lower bar easily. โณ ๐—ช๐—ต๐˜† ๐˜๐—ต๐—ฒ ๐˜€๐˜๐—ฟ๐—ผ๐—ป๐—ด๐—ฒ๐—ฟ ๐—ฑ๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ฝ๐—ฝ๐—ฒ๐—ฎ๐—ฟ๐—ฒ๐—ฑ ๐—ผ๐—ป๐—น๐˜† ๐—ป๐—ผ๐˜„ A reasonable person asks why the sharper analysis appeared in 2026 and not in 2023. The answer is access, not choice. The patient-level analysis was written into the trial's plan from the start, to run if and when the data could be obtained. The company tried and could not get it in 2023, because the trials that held it had not released it; it became available later through a data-sharing repository, on the data owners' timeline, not the company's. The stronger analysis was always the plan. It was waiting on data that other parties control. ๐Ÿ”„ ๐—ฃ๐—ฎ๐˜๐—ถ๐—ฒ๐—ป๐˜๐˜€ ๐˜„๐—ต๐—ผ๐˜€๐—ฒ ๐—ฐ๐—ฎ๐—ป๐—ฐ๐—ฒ๐—ฟ ๐—ฟ๐—ฒ๐˜๐˜‚๐—ฟ๐—ป๐—ฒ๐—ฑ ๐—ฎ๐—น๐˜€๐—ผ ๐—ฏ๐—ฒ๐—ป๐—ฒ๐—ณ๐—ถ๐˜๐—ฒ๐—ฑ The vaccine helped not only newly diagnosed patients but also those whose tumor had already come back, and there the effect was the largest seen anywhere in the trial. In that group, median survival ran 13.2 months from recurrence against 7.8 for the controls. The separation opened immediately, with 90.6% of vaccine patients alive at six months against 64.0% of controls, and the lead held to the later marks, where survival more than doubled: 20.7% against 9.6% at two years, 11.1% against 5.1% at two and a half. These are the original cohort-level results, already published. The high-resolution patient-level matching that was applied to the newly diagnosed group has not yet been done here, for a practical reason: it needs patient records from other recurrent-cancer trials, held by a European research organization that shares them through its own formal request. Obtaining them is a routine next step, not an obstacle, and the newly diagnosed experience suggests the sharper analysis would only make the recurrent result stronger. The approval case rests on the newly diagnosed evidence, so nothing important depends on this step; it would simply sharpen a result that is already the strongest in the trial. ๐Ÿ›๏ธ ๐—ช๐—ต๐—ฎ๐˜ ๐˜๐—ต๐—ถ๐˜€ ๐—บ๐—ฒ๐—ฎ๐—ป๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ฎ๐—ฝ๐—ฝ๐—ฟ๐—ผ๐˜ƒ๐—ฎ๐—น Regulators do not treat an external control as a first choice, but the MHRA's guideline allows it in exactly this situation: a severe disease where a placebo trial is not ethical or feasible, and an effect large enough to interpret despite the design. The guideline even gives its own worked example of an acceptable external control, and it reads almost like a description of this trial: a rare disease, no ethical placebo, same-era standard-of-care controls, an objective survival endpoint, and an effect too large to blame on bias. DCVax-L fits on every count, and it was the first medicine ever to receive the MHRA's Promising Innovative Medicine designation, which asks essentially the same questions. The newly diagnosed case carries the decision on its own evidence, and regulators weigh that evidence against the disease it treats: in a cancer this lethal, with nothing better on offer, the question is whether the benefit is large, clear, and consistent enough to act on, and a benefit of this size, pointing the same way from every direction, is. ๐Ÿ“œ ๐—ง๐—ต๐—ถ๐˜€ ๐—ต๐—ฎ๐˜€ ๐—ฏ๐—ฒ๐—ฒ๐—ป ๐—ฑ๐—ผ๐—ป๐—ฒ ๐—ฏ๐—ฒ๐—ณ๐—ผ๐—ฟ๐—ฒ, ๐—ฎ๐—ป๐—ฑ ๐—ฎ๐—ฝ๐—ฝ๐—ฟ๐—ผ๐˜ƒ๐—ฒ๐—ฑ External controls are not a novelty invented for this drug. Over the past two decades they have factored into roughly forty-five drug approvals by the United States regulator, each granted under the conditions that apply here: a serious or rare disease, a placebo that would be unethical, and high unmet need. Regulators do not grant this lightly. They grant it when the disease is serious, its course is predictable and objectively measured, and the effect is large. Glioblastoma meets all three. The named cases cover every part of this disease's profile. Defibrotide, for a life-threatening transplant complication, was approved on a propensity-score comparison to a historical control, the same kind of method used here. Blinatumomab, for an aggressive relapsed leukemia, is the precedent for a fast-killing cancer, cleared by both the United States and European regulators. Cerliponase alfa is the precedent for a fatal brain disease, cleared by both agencies on treated patients versus a matched natural-history group. Glioblastoma is both at once, a fast-killing cancer of the brain, read by the same method, so no part of its profile lacks a close approved precedent. And on the one axis that governs how far an external-control result can be trusted, DCVax-L goes beyond all three. Each of those drugs was tested in a single-arm trial, with no randomization at all. DCVax-L began as a randomized trial and became an external-control comparison only when ethics consumed its placebo group. It sits in that tradition, and at the top of it. ๐ŸŽฏ ๐—ง๐—ต๐—ฒ ๐—ฏ๐—ผ๐˜๐˜๐—ผ๐—บ ๐—น๐—ถ๐—ป๐—ฒ This began as a randomized trial. Medical ethics forced it into an external-control comparison. Every independent way of checking it, on different data and different math, points the same direction, and the biology predicted that direction in advance. The first analysis did not overstate the vaccine's effect. Read with the right tools, it understated it.

Andrew Caravello, DO

11,406 views โ€ข 2 months ago

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 governmentโ€™s actions here piss me off, in a way Iโ€™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 Anthropicโ€™s models because of these redlines. In fact, I think the governmentโ€™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, thereโ€™s a Democratic administration, and Elon Musk is negotiating some SpaceX contract to give the military access to Starlink. And suppose if Elon said, โ€œI reserve the right to cancel this contract if I determine that youโ€™re using Starlink technology to wage a war not authorized by Congress.โ€ On the face of it, that language seems reasonable - but as the military, you simply canโ€™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, โ€œHey weโ€™re not gonna do business with you,โ€ 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 contractorsโ€™ 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, wouldnโ€™t most tech companies drop the government, not the AI? So what's the Pentagon's plan โ€” 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 weโ€™re in a race with China, and we have to win. But what is the reason we want America to win the AI race? Itโ€™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 โ€” 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, youโ€™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 itโ€™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 weโ€™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 youโ€™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 thereโ€™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 thereโ€™s wide diffusion, then from the governmentโ€™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, โ€œOh Anthropic, Google, OpenAI, youโ€™re drawing a line in the sand? No issue - Iโ€™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.โ€ 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 doesnโ€™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 donโ€™t have an answer. You'd hope there's some symmetric property of the technology โ€” 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 donโ€™t think thatโ€™s how itโ€™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 someoneโ€™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 havenโ€™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. Itโ€™s understandable why we donโ€™t hear much about it. If youโ€™re a model company, you donโ€™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. Weโ€™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 โ€œall lawful purposesโ€. 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 Actโ€™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 militaryโ€™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. Iโ€™m guessing Hegseth is not thinking about โ€œgenAIโ€ 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 thatโ€™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 itโ€™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 theyโ€™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 thereโ€™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: โ€œAt 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.โ€ So theyโ€™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 youโ€™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 โ€” 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, youโ€™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 thatโ€™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 โ€” an authority from the 2018 defense bill meant to keep Huawei components out of American military hardware. The other was the Defense Production Act โ€” 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, thereโ€™s just no world where the government doesnโ€™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 isnโ€™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 itโ€™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 theyโ€™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: โ€œif 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.โ€ 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 Leopoldโ€™s argument at the time, and Benโ€™s argument now, is that while theyโ€™re right that itโ€™s crazy that weโ€™re entrusting private companies with the development of this world historical technology, I just donโ€™t see the reason to think that itโ€™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 โ€” 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 โ€” which was also, by any measure, world-historically important โ€” 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 canโ€™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 weโ€™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 Benโ€™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 Anthropicโ€™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 todayโ€™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

548,652 views โ€ข 6 months ago

Min Hee-jin (NewJeans Producer) NHK Music Interview ๐Ÿ”— โ€œMeticulously planned debut โ€˜Attentionโ€™โ€ ๐Ÿงข: 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 detailsโ€ฆ 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 effectiveโ€ฆ 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: โ€œLetโ€™s make the most of our situation.โ€ At the time, the members hadnโ€™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. Thatโ€™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 didnโ€™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 membersโ€™ images was through music and a moving pictureโ€ฆ thatโ€™s why we led with a music video. In the debut music video, โ€œAttention,โ€ thereโ€™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 donโ€™t just make contentโ€ฆ I design the entire process of how it should be shown for the greatest effect. And I believe thatโ€™s incredibly important. That first feeling someone gets when they encounter somethingโ€ฆ that emotion, that sparkโ€ฆ is so important to me. Iโ€™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. Itโ€™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, โ€œASAP,โ€ and then we followed that with the full music video for โ€œNew Jeans,โ€ which was the first track. That order was a carefully calculated strategy. It was designed to guide the audienceโ€™s emotional journey. Seeing the audience react just as I had hopedโ€”that whole process was honestly so fun and thrilling for me. I think I really enjoy that kind of thing. โ€”โ€”โ€” โ€œHow 'Ditto' was bornโ€ ๐Ÿงข: People often praise the music of NewJeans, and I hear a lot of talk about genres. But actually, I donโ€™t feel bound by genre at all. I love a wide variety of music. Iโ€™m not the type to insist on only one particular genre. What I love are songs that blend genres cleverlyโ€ฆ 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 donโ€™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 whatโ€™s meaningful in a given moment. For instance, the song โ€œDittoโ€ 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. Itโ€™s not about objectively predicting what will be a โ€œhit,โ€ but about whether a song moves your heartโ€ฆ you can just feel it. Of course, my own taste plays a big role. But I think thatโ€™s actually my strength as a producer, not as a composer. When I hear a song, I can immediately picture the visualโ€ฆ 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 basicsโ€ฆ whatโ€™s the original idea of a school uniform? I try to return to that. So with โ€œDitto,โ€ I wanted to tap into something primalโ€ฆ the pure, basic feeling of liking someone. That kind of emotion is universal. Everyone has it; itโ€™s wired into us. When I saw Director Shin Woo-seokโ€™s interpretation of it, I thought, โ€œYes, thatโ€™s it.โ€ Thatโ€™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 detailโ€ฆ the maximum quality they can bring out. My role is to unify and refine all of that. I draw out the essence of each personโ€™s creativity, trimming away anything unnecessary. So the final product is something thatโ€™s polished and high-quality, just the way I envisioned it. Thatโ€™s my working style. So itโ€™s not like Iโ€™m fixated on retro or stuck in a particular style. I donโ€™t think human taste has changed all that much. Things people liked in the past are the same things we like now. Itโ€™s just the form of expression that changes with time. I donโ€™t feel bound by โ€œpastโ€ or โ€œpresent.โ€ I donโ€™t even think in those boundaries. To me, itโ€™s all just good taste. You know how kids sometimes have their own little treasure boxes when theyโ€™re young? I think my work is kind of like that. I want to make things that never feel datedโ€”that are timelessly enjoyable. โ€”โ€”โ€” โ€œDance Expression and 'Hype Boy'โ€ ๐Ÿงข: I had a vision of what kind of girl group I wanted to create. Thatโ€™s why I chose a song like โ€œHype Boy.โ€ 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. โ€œHype Boyโ€ 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 formatโ€ฆ you know, the kind where everyone is in perfect formation, doing synchronized moves. But our songs donโ€™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. Itโ€™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. Theyโ€™re still young, but theyโ€™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 thatโ€™s natural for people their ageโ€ฆ genuine, carefree, radiant. โ€”โ€”โ€” โ€œThe difference between NewJeans and conventional K-POPโ€ ๐Ÿงข: Ah, for me, itโ€™s all about naturalness. And honestly, naturalness isnโ€™t something you can produce or direct into existence. It comes from how I interact with the NewJeans members on a daily basisโ€ฆ what kind of environment they practice in, how they live and work. There are so many things that donโ€™t appear on camera, but those unseen aspects have to be in place in order for true naturalness to come through. Thatโ€™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 donโ€™t believe anyone can be completely natural in front of a camera or under the gaze of others. Itโ€™s human nature to become self-conscious. Thatโ€™s why I think naturalness is our strength, but it canโ€™t be our concept. If you try to turn โ€œnaturalnessโ€ into a concept, it actually becomes incredibly artificial. So why do I place so much importance on naturalness? Itโ€™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, โ€œThis is like studying together with me.โ€ 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, โ€œWeโ€™re going to school together. Weโ€™re learning together.โ€ And in that sense, I want to be a good teacher to them. Theyโ€™re also surrounded by an incredibly professional team, people theyโ€™d never meet even in a traditional school setting. Iโ€™ve never really liked the word idol. These days, that word is used more like a job title, something manufactured by the industry, and itโ€™s far from its original meaning. To me, the term idol feels misplaced. It doesnโ€™t really reflect who these artists are or what they represent. And Iโ€™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 differentโ€ฆ to challenge those assumptions and redefine what this can look like. Thatโ€™s the kind of mindset I have. โ€”โ€”โ€” โ€œIsn't it difficult for the members to express "naturalness"?โ€ ๐Ÿงข: 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 vibeโ€ฆ like how I prefer working with staff who align with my taste. Itโ€™s important for the crew to be on the same wavelength. And by that, I mean more than just getting alongโ€ฆ it also extends to shared values. Of course, people wonโ€™t all share identical values, but when weโ€™re facing in a similar direction, everything becomes easier. Itโ€™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, theyโ€™re still growing, still discovering themselves. Theyโ€™re not in a finished state. So we didnโ€™t cast them based on some complete or polished version of themselves. It wasnโ€™t like, โ€œThis person is fully formed, letโ€™s pick her.โ€ It was more like, โ€œAh, she has potential, thereโ€™s something there.โ€ That sense of a sparkโ€ฆ those were the kinds of subtleties I paid attention to. I didnโ€™t cast anyone just because they were pretty or could sing well. I donโ€™t work like that. I really value those finer, more delicate aspects. Even the design of the light stick wasnโ€™t something that came from a long strategic planning sessionโ€ฆ it was actually a spontaneous idea. I didnโ€™t sit down and think, โ€œLetโ€™s make a light stick like this.โ€ NewJeans didnโ€™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 rabbitโ€™s face. When I drew it out, the shape just continued and turned into a bunny. To me, the NewJeans members are like little bunniesโ€ฆ playful, innocent. Their visuals also resemble rabbits in a way. And rabbits symbolize abundance. That made me think: โ€œAh, maybe our fans will multiply like rabbits. That would be great.โ€ 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, โ€œWouldnโ€™t it be great if fans could personalize their bunny?โ€ That way, each rabbit would represent a different personโ€™s character. So we included accessories, allowing everyone to customize their own bunny. Itโ€™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 itโ€™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 faceโ€ฆ itโ€™s also a heart. It represents both the face of NewJeans and our hearts. Itโ€™s the love weโ€™re showing to our fans, and the love we want to receive in return. Every time I see it, I feel deeply moved. Itโ€™s very emotional for me because itโ€™s a perfect realization of what I envisioned. As someone with a background in creative direction, thereโ€™s nothing more satisfying than seeing an idea materialize exactly the way you imagined it. That kind of work holds deep meaning for me. โธป ๐Ÿงข: Looking back, I think in 2023 we were able to achieve almost everything we had hoped for. Iโ€™m so incredibly grateful for that. Of course, this is an ongoing challengeโ€ฆ and the better things go, the more pressure there is. Thatโ€™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 thrillโ€ฆ this rush of excitement. I donโ€™t want to forget that feeling. So I try hard to engrave that emotion into every album we release. Iโ€™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. Thatโ€™s really my deepest wish. ๐Ÿ™

1tokki

17,635 views โ€ข 1 year ago

On March 15th, 2021, an anonymous Twitter user asked Harvard Medical professor Martin Kulldorff a question. โ€œDo you think younger age groups and or people who have already had the virus need to be vaccinated?โ€ Who is Martin Kulldorff? Heโ€™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 worldโ€™s leading health organizations. What he said was that โ€œThinking 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.โ€ Natural immunity. Is it a myth โ€” a โ€œconspiracy theoryโ€ โ€” that once you have been sick from a virus, then you wonโ€™t get sick, or as sick, again? In fact, weโ€™ve known for 2,500 years that natural immunity is real. โ€œThe same man was never attacked twice, never at least fatally,โ€ 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 Kulldorffโ€™s tweet. โ€œLearn why health officials recommend a vaccine,โ€ 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 wasnโ€™t really something that could protect you from COVID. Jay Bhattacharya, whoโ€™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 โ€œTrends Blacklist.โ€ Not long before we discovered this, we were told that shadow-banning was a conspiracy theory, because Twitter had said it didnโ€™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 โ€œDemocracy Shieldโ€ program to shield the Commission from democracy. And the Commission wants to impose โ€œchat controlโ€ 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. Weโ€™ve known that since Plato and Socrates. We need free speech for science, public health, and national security. Itโ€™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. Theyโ€™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 donโ€™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 โ€œCensorship Industrial Complex,โ€ 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 isnโ€™t that complicated to understand. The government chooses people whom they call โ€œresearchersโ€ 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 โ€œfact checksโ€ to serve as โ€œtrusted flaggers.โ€ These โ€œtrusted flaggersโ€ demand censorship by social media platforms. Itโ€™s all done in secret. Theyโ€™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 โ€œVirality Project,โ€ they said they wanted to censor โ€œtrue storiesโ€ of vaccine side effects. Why? Because it might โ€œfuel hesitancy.โ€ In other words, they want to control your behavior. They donโ€™t want you to receive true information that might lead you to not get the vaccine. If that isnโ€™t totalitarianism straight out of 1984, I donโ€™t know what it. These people were on the verge of passing legislation in the United States that wouldโ€™ve authorized the National Science Foundation to choose these โ€œresearcherโ€ censors. Iโ€™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. Theyโ€™re really not interested in censoring โ€œmisinformation.โ€™ Theyโ€™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, itโ€™s more protective than the vaccine. But the censors flagged somebodyโ€™s Google Drive. โ€œSee the following Google Drive links being used to compile testimonies about vaccine shedding, Covid videos, showing side effects and whatnot.โ€ Google then removed that content from that personโ€™s Google Drive. You donโ€™t control your Google Drive. Contrary to Stanfordโ€™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, Stanfordโ€™s โ€œVirality Projectโ€ 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 couldnโ€™t have come from a lab, that the Covid vaccine prevented infection, and that natural immunity didnโ€™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. Itโ€™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 โ€œBu alumni.โ€ 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 โ€” 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 canโ€™t do โ€” resigned from FBI in early 2020 and went to Twitter to take the deputy general counsel role. Isnโ€™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. Itโ€™s from the director of policy at Twitter. โ€œWe have seen a sustained if uncoordinatedโ€ โ€” supposedly โ€” โ€œeffort by the intelligence community to push us to share more information and change our API policies. Theyโ€™re probing and pushing everywhere they can.โ€ The Hunter Biden laptop censorship occurred later that year. The FBI and the intelligence community discredited accurate, factual information about Hunter Bidenโ€™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 Bidenโ€™s laptop, which showed his familyโ€™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 . โ€œThe FBI came to us in the summer of 2020,โ€ Mark Zuckerberg told Joe Rogan two years later, โ€œand they were like, โ€˜Hey, you should be on the alert. We thought that there was a lot of Russian propaganda in 2016. Thereโ€™s about to be some kind of dump.โ€™โ€ 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. Itโ€™s known as a Davos-style gab fest in the United States. Itโ€™s also the place where intelligence community operations are run. They hosted a workshop to train reporters and all of the social mediaโ€™s top censorship officials, known as โ€œtrust and safety officials,โ€ 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 weโ€™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, โ€œYou should cover the person who leaked the materials, not the leaked emails.โ€ 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 โ€œpre-bunking,โ€ and itโ€™s also part of the European Union strategy to shield themselves from democracy. When the Hunter Biden story appeared October 22nd, Twitterโ€™s trust and safety censorship official said it didnโ€™t violate its terms of service. Thereโ€™s nothing illegal about any of this. The Supreme Court has made it very clear that youโ€™re allowed to report on information thatโ€™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. Itโ€™s not that we didnโ€™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 Googleโ€™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 Jilkovรก, the daughter of famous Czech dissidents, discovered that European Union officials claimed, days before the European elections in 2024, that a โ€œpro-Kremlin websiteโ€ was spreading propaganda and were paying off European politicians. That was the headline in Politico. We wrote to them and asked, โ€œWhereโ€™s the evidence of this? Just go ahead and share the evidence to support your accusation days before the European parliamentary elections.โ€ Nobody was arrested. They never produced the evidence. The former Czech president, Vรกclav Klaus, who was accused of this, said, โ€œWe donโ€™t even know what the โ€˜Voice of Europeโ€™ is.โ€ Another Czech politician said, โ€œHow could I have known it would be a security threat? At the time I gave the interview, they werenโ€™t on any list.โ€ Another said, โ€œIf theyโ€™re such a big threat, why did the European Parliament let the Voice of Europeโ€™s journalists inside?โ€ 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 โ€œtrusted flaggers.โ€ 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, โ€œMy sense is that given weโ€™ve got bigger fish, we have to fry with the administration, e.g., data flows, it doesnโ€™t seem like a great place for us to be.โ€ Data flows. Whatโ€™s he talking about? Heโ€™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 didnโ€™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 Libertรฉ. 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

174,749 views โ€ข 8 months ago

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 someoneโ€™s ego were distractions that occurred too regularly. You couldnโ€™t just be a builder โ€” 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 โ€œno, that canโ€™t be doneโ€ or โ€œanother team owns that so donโ€™t touch itโ€. Teams could spend months building a feature and then some last-minute kerfuffle meant itโ€™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 โ€” 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 wasnโ€™t fully empowered to run the company since he wasnโ€™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 companyโ€™s future notoriously included the phrase โ€œfiduciary dutyโ€. Colleagues openly talked about how Twitter was being sold because leadership didnโ€™t have conviction in their own plan or ability to fix longstanding problems. Although I didnโ€™t know much about Elon I was cautiously optimistic โ€“ 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 whatโ€™s happened since then is full of lived nuance. When people ask why I stayed itโ€™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 Iโ€™m on a team I uphold the philosophy of โ€œpraise in public and criticize in privateโ€. 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 didnโ€™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 couldnโ€™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 heโ€™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 didnโ€™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 donโ€™t think things had to be as difficult or dramatic as they turned out to be but I canโ€™t say Iโ€™d bet against Elon or count him out. Heโ€™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 heโ€™ll need things to turn around. His focus on speed is incredible and heโ€™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 โ€“ 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 theyโ€™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. Itโ€™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, letโ€™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 donโ€™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 wasnโ€™t willing to do myself. So I worked round the clock alongside an amazing team spanning many timezones, and we delivered it on schedule โ€“ 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 canโ€™t work at that pace forever but there are moments where bursts are mission critical. Iโ€™ve pulled many all-nighters in my career and also when I was a student for something that mattered to me. I donโ€™t regret putting in long hours or being ambitious, and feel proud of how far Iโ€™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 โ€” Iโ€™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 thatโ€™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 doesnโ€™t deserve to be venerated or vilified. Heโ€™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 Iโ€™ve ever received. Sure the headlines and punchlines wrote themselves but I was battle hardened by then. I knew that Iโ€™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 Iโ€™m finally feeling rested and relaxed. Iโ€™m a creative and a builder, so sooner than later Iโ€™ll jump back into a high intensity company but Iโ€™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. Iโ€™d be remiss if I didnโ€™t note that in all of this there is also a cautionary tale for anyone who succeeds at something โ€” which is that the higher you climb, the smaller your world becomes. Itโ€™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. Weโ€™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 โ€œbetter angelsโ€ 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 Iโ€™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 thatโ€™s both safer and wealthier. I donโ€™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 Iโ€™m grateful to have played a teeny tiny role in its story and evolution. Iโ€™m here for whatever comes next โ€” on this app and in new places. Consumer social is very much alive and at a fascinating juncture, so Iโ€™ll be watching and participating and sharing hot takes because I donโ€™t want to, and probably canโ€™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. ๐Ÿซก

Esther Crawford โœจ

5,506,001 views โ€ข 3 years ago

Iโ€™ve been using GPT-5.6 Sol internally for the past two months, I've spent probably 25+ billion tokens. Hereโ€™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

188,148 views โ€ข 2 months ago

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: ๐Ÿ›ฐ๏ธ 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: โšก The custom architecture delivers a 150 kW peak compute payload. ๐Ÿ”‹ The system maintains a 120 kW sustained average compute payload under active workloads. โš–๏ธ The hardware achieves a highly optimized power-to-weight density of 70 kW per ton. ๐Ÿ”„ 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." --- ๐Ÿ“ 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: ๐Ÿ“ The structural frame features a massive 70-meter wingspan. โ†•๏ธ The vehicle spans a total deployed height of 20 meters. โ˜€๏ธ The onboard solar array delivers an efficiency of 250 W/mยฒ using technology manufactured in Bastrop, Texas. ๐ŸŒก๏ธ The thermal system utilizes a 110 mยฒ deployable liquid radiator to cleanly dump waste heat. ๐Ÿ”„ The cooling architecture incorporates redundant pumping loops for mission safety. ๐Ÿ›ก๏ธ The exterior contains integrated micrometeoroid shielding to protect the fluid lines. ๐Ÿงญ 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." --- ๐Ÿงฉ 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: ๐ŸŽ›๏ธ The hardware framework is arranged around a centralized compute module. โ˜€๏ธ Large deployable solar arrays extend outward to capture orbital energy. ๐ŸŒก๏ธ A deployable liquid-radiator thermal management system controls active operational temperatures. ๐Ÿ”„ 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." --- ๐Ÿ”Œ 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: ๐Ÿง  Reference designs are fully established to seamlessly accommodate NVIDIA Reuben chips. ๐Ÿ’พ The system architecture is built to support alternative setups using NVIDIA GB300 chips. ๐Ÿ’ป Custom hardware layouts are explicitly designed to integrate Google TPUs. ๐ŸŒ The onboard communications setup delivers roughly 1 terabit of laser link connectivity. โฑ๏ธ 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." --- ๐Ÿญ 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: ๐Ÿ—บ๏ธ The company has over 1,000 acres of land currently owned or under contract for the site. ๐Ÿข The manufacturing complex boasts a massive structural building potential exceeding 11 million square feet. โš™๏ธ The facility will vertically integrate production to manufacture solar ingots, wafers, solar cells, and completed AI satellites. ๐Ÿ“… 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." --- ๐Ÿข 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: ๐Ÿญ The colossal factory is projected to span approximately 100 million square feet, making it ten times larger than the current Tesla Gigafactory Texas. โšก The facility is structurally engineered to achieve a massive manufacturing output of 1 terawatt per year once fully operational. ๐Ÿ“ฆ This unprecedented physical footprint provides the capacity required to manufacture 1 billion full-reticle equivalent chips annually. ๐Ÿ”Œ Each individual chip manufactured by the facility is designed to run at a power capacity of 1 kilowatt. ๐Ÿ‡บ๐Ÿ‡ธ 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." --- ๐Ÿ“ถ 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: ๐Ÿ“ˆ The upgraded user hardware is manufactured at a much higher volume capacity than existing units. ๐ŸŒ 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." --- ๐Ÿ“ˆ 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: 1๏ธโƒฃ The initial target aims to hit an annualized run-rate of 1 gigawatt of space AI compute by the end of next year. 2๏ธโƒฃ The capacity scales to an annualized rate of 10 gigawatts within the next two and a half years. 3๏ธโƒฃ The operational envelope expands to reach 100 gigawatts in three and a half years. 4๏ธโƒฃ 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." --- ๐ŸŒ• 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: ๐ŸŒ™ The company plans to establish localized raw production lines on the moon to fabricate solar panels, photovoltaics, and radiators from lunar materials. โšก Manufacturing components locally avoids the massive fuel and mass penalties of transporting heavy structural materials from Earth. ๐Ÿงฒ 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. ๐Ÿš€ 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 typeโ€”it's basically a linear electric motor."

Ming

22,203 views โ€ข 3 months ago

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

135,530 views โ€ข 3 months ago

$NVDA $MU $SNDK $LITE PAPER OVERVIEW AND CORE CLAIMS The paper โ€œKV Cache Transform Coding for Compact Storage in LLM Inferenceโ€ introduces kvtc, a transform-coding pipeline that compresses transformer key-value (KV) caches primarily for storage and transfer in LLM serving, rather than for accelerating the per-token attention kernel during active decoding. The method combines 3 stages: (1) feature decorrelation via a PCA basis computed from a calibration dataset and reused across requests; (2) adaptive, variable-precision quantization with bit allocation solved via dynamic programming (DP), including groupwise scaling/shift overhead; and (3) lossless entropy coding (DEFLATE via nvCOMP in the reference implementation) to exploit residual redundancy after quantization. The central empirical claim is that KV tensors contain large, exploitable redundancy across heads and layers, enabling approximately 20ร— compression versus a 16-bit baseline with negligible degradation across a broad set of accuracy and long-context benchmarks, with materially higher compression (โ‰ฅ40ร—) available at modest quality cost in some regimes. The system claim is that such compression materially improves the economics of multi-turn, prefix-reuse serving by extending effective KV cache capacity in GPU HBM and host tiers (DRAM/NVMe) and by reducing inter-node and GPUโ†”host bandwidth demands, thereby improving cache hit rates and reducing time-to-first-token (TTFT) relative to recomputation when caches would otherwise be evicted. KV CACHE AS THE DOMINANT STATE VARIABLE IN INFERENCE ECONOMICS KV cache growth is linear in context length and is multiplicative in layers and attention heads, making it an increasingly dominant constraint as (a) context lengths expand, (b) models add layers and maintain large hidden dimensions, and (c) production workloads shift toward iterative and tool-augmented interactions that repeatedly reuse long prefixes. The paper uses the canonical 16-bit KV cache size formula (4ยทlยทhยทd_headยทt) bytes and reports 16-bit KV cache sizes per 1K tokens of context that are already operationally large: 128MiB for Llama 3.1 8B, 160MiB for Mistral NeMo 12B, and 320MiB for Llama 3.3 70B Instruct. In binary units, these figures imply per-token KV footprints of 128KiB/token (Llama 3.1 8B), 160KiB/token (Mistral NeMo 12B), and 320KiB/token (Llama 3.3 70B Instruct) at 16-bit. For a 10K-token prompt (10ร—1K in the paperโ€™s binary convention), the 16-bit KV cache sizes scale to approximately 1.25GiB (Llama 3.1 8B), 1.56GiB (Mistral NeMo 12B), and 3.13GiB (Llama 3.3 70B Instruct). These magnitudes explain why stale caches create a throughputโ€“latency dilemma: retaining them in HBM maximizes responsiveness on future turns but crowds out concurrent sessions; evicting them forces quadratic-cost prefill recomputation and increases TTFT; offloading them to host or storage introduces large transfer overhead and consumes DRAM/NVMe capacity. A key operational nuance emphasized is that modern serving stacks increasingly treat KV caches as a database, leveraging block paging and shared-prefix reuse. In the common disaggregated serving design (separate prefill and decode nodes), KV cache transfer becomes a dominant category of cross-node traffic. Under that design, any reduction in KV cache size directly increases effective fabric capacity and reduces tail latency attributable to congestion, while also enabling longer cache lifetimes in โ€œhotโ€ (HBM) and โ€œwarmโ€ (CPU DRAM) tiers that raise cache hit rates and reduce recomputation frequency. The paperโ€™s quantitative example illustrates the economic stakes: a 1,000-line code file tokenized at ~10 tokens/line yields ~10K tokens; for Llama 3.3 70B, an 8-bit KV cache for that context is ~1.6GiB. Reuse across subsequent turns or parallel chats around the same file is valuable, but HBM scarcity makes retaining many such caches infeasible without compression. TECHNICAL MECHANISM: WHY KV CACHES ARE COMPRESSIBLE AND HOW KVTC EXPLOITS IT The technical rationale begins with an empirical observation: keys (and, to a lesser extent, values) across different attention heads can be aligned into a shared latent space using orthogonal transformations (Procrustes alignment). This supports the hypothesis that head-specific projections introduce rotations of a common subspace rather than completely distinct information, implying that concatenating across heads and layers should reveal low-rank structure suitable for linear decorrelation and dimensionality reduction. The method operationalizes this using a PCA/SVD basis learned from calibration data rather than recomputing a decomposition per prompt. This design choice targets production viability: per-prompt SVD is computationally expensive and scales poorly with long prompts and frequent cache updates. kvtc is explicitly structured as an offline-calibrated, online-applied codec: Calibration (performed 1 time per model and compression setting for DP allocation) A calibration dataset is forwarded through the model to collect KV caches. Token positions are pooled, and a subset of positions is sampled. Keys and values are processed separately. Several implementation choices are highlighted as decisive for stability: Rotary positional embeddings are effectively removed prior to compression (โ€œundo positional rotationsโ€), because positional rotations degrade the apparent low-rank structure of keys. โ€œAttention sinkโ€ tokens (the earliest tokens in the sequence) and a sliding window of most recent tokens are excluded from compression because they disproportionately affect attention patterns and are empirically more sensitive to reconstruction error. Cross-layer concatenation is used: keys (or values) from multiple layers and heads at the same token position are concatenated along the feature axis to form a higher-dimensional feature vector. PCA is computed over these concatenated vectors, improving robustness relative to per-layer or per-head PCA. The PCA basis is computed via SVD of centered calibration data, using randomized SVD for scalability with a target rank cutoff. The paper reports calibration regimes of 160K tokens for several models with a 10K PCA dimension cutoff (8K for Qwen variants with fewer KV heads), selected to fit within a single 80GB H100 memory envelope and complete within minutes. A critical economic detail is that the same PCA basis can be reused across multiple compression ratios; only the DP-derived precision assignment changes per compression target. Compression (applied between inference phases) Compression operates on stored KV cache tensors, not on weights, and does not modify attention computation. The KV cache is projected into the PCA basis, quantized, packed, and then entropy-coded. Compression is positioned as a background or between-phase operation (after decoding, or between prefill and decode), executed on GPU or CPU depending on where the cache currently resides. The design intent is that compression should not sit on the critical per-token decoding path; it is a storage and transport optimization. Decompression (performed prior to reuse) Decompression reverses the entropy coding and quantization and applies the inverse PCA projection. A practical latency optimization is proposed: inverse projection can be performed layer-by-layer using submatrices of the PCA basis, allowing generation to begin before the full cache is reconstructed, reducing TTFT. Quantization and bit allocation are the core differentiators versus simpler PCA truncation. PCA provides ordered components by variance; kvtc uses DP to allocate a global bit budget across PCA coordinates (and across groups of coordinates) to minimize reconstruction error in the decorrelated domain. Groups of subsequent PCA coordinates share 16-bit shift and scale factors (a microscaling-inspired design), and the DP algorithm jointly selects group size and precision type under a bit budget, including the overhead of per-group metadata. DP commonly assigns 0 bits to many trailing PCA components, which both increases compression and provides a mechanism to trim the PCA basis to the subset of components that actually carry payload, reducing compute and storage overhead of the projection matrices in deployment. Lossless entropy coding then exploits the structure induced by quantization. DEFLATE is used in the reference implementation, and the paper emphasizes that the incremental gain from the lossless stage is content-dependent but meaningful, with an average uplift of ~1.23ร— on top of quantization in the reported regime. An ablation in the appendices indicates that GPU-friendly variants (GDeflate) can achieve nearly identical compression ratios (โ‰ค0.1 difference in measured cases), implying that throughput-optimized lossless codecs can likely be substituted without sacrificing meaningful compression. EMPIRICAL RESULTS: ACCURACY, COMPRESSION, AND LATENCY General-purpose 8Bโ€“12B dense models The paper evaluates Llama 3.1 8B, MN-Minitron 8B, and Mistral NeMo 12B across math/knowledge (GSM8K, MMLU) and long-context tasks (Qasper, Lost in the Middle, RULER Variable Tracking) under a simulated multi-turn regime where compression/decompression is applied periodically, with a sliding window of recent tokens excluded. A consistent pattern appears: kvtc maintains near-vanilla performance through 16ร— compression settings, and remains competitive at 32ร—, with degradation becoming task- and model-dependent at 64ร—, particularly on long-context retrieval metrics when compression is pushed aggressively. Selected quantitative anchor points from the paperโ€™s standard-error table (all values are reported with the paperโ€™s evaluation setup and token-window exclusions): Llama 3.1 8B Vanilla: GSM8K 56.8, MMLU 60.5, Qasper 40.4, LITM 99.4, RULER-VT 99.8 kvtc16ร—: GSM8K 56.9, MMLU 60.1, Qasper 40.7, LITM 99.3, RULER-VT 99.1 kvtc32ร—: GSM8K 57.8, MMLU 60.6, Qasper 39.4, LITM 99.1, RULER-VT 98.9 kvtc64ร—: GSM8K 57.2, MMLU 60.7, Qasper 37.8, LITM 90.2, RULER-VT 95.9 These results indicate that, for this model, long-context sensitivity emerges at 64ร— with meaningful drops in LITM and RULER-VT, while math/knowledge scores remain stable, implying a differential sensitivity consistent with key-vector precision being more critical for retrieval-style behavior. Mistral NeMo 12B Vanilla: GSM8K 61.9, MMLU 64.5, Qasper 38.4, LITM 99.5, RULER-VT 99.8 kvtc16ร—: GSM8K 62.0, MMLU 64.4, Qasper 37.6, LITM 99.8, RULER-VT 99.5 kvtc32ร—: GSM8K 62.2, MMLU 63.8, Qasper 37.5, LITM 99.6, RULER-VT 98.7 kvtc64ร—: GSM8K 61.9, MMLU 61.4, Qasper 38.0, LITM 95.3, RULER-VT 98.0 Here, degradation at 64ร— is visible but materially smaller than the Llama 3.1 8B LITM drop, suggesting model-architecture or training-data differences can change the tolerance envelope for aggressive KV cache distortion. MN-Minitron 8B Vanilla: GSM8K 59.1, MMLU 64.3, Qasper 38.2, LITM 99.8, RULER-VT 99.4 kvtc16ร—: GSM8K 60.3, MMLU 64.1, Qasper 38.6, LITM 99.3, RULER-VT 98.8 kvtc32ร—: GSM8K 59.1, MMLU 63.7, Qasper 37.7, LITM 86.9, RULER-VT 96.0 kvtc64ร—: GSM8K 57.8, MMLU 62.1, Qasper 38.1, LITM 59.5, RULER-VT 93.4 This model shows markedly higher sensitivity on LITM at 32ร— and 64ร—, despite stable short-context metrics, reinforcing that โ€œcompression safetyโ€ is not monotonic in parameter count and that pruning/distillation choices can alter KV cache redundancy or robustness. Comparisons to baselines The paper compares kvtc to quantization baselines (KIVI, GEAR, FP8) and eviction baselines (H2O, TOVA), plus an SVD-based prefill-optimization method (xKV). Across the reported tasks: Low-bit quantization methods at modest compression (2-bit KV schemes) show earlier degradation in long-context behavior than kvtc at substantially higher compression settings. Eviction methods perform poorly as generic compressors for long-context tasks, consistent with their objective function (selective pruning) being misaligned with โ€œlossless-ish storage for reuse.โ€ xKV shows competitive results on some tasks but a consistent underperformance on Qasper relative to kvtc and vanilla in the provided tables, consistent with method-specific distortions introduced by its decomposition regime. Reasoning models and high-variance tasks For DeepSeek-R1-distilled Qwen 2.5 reasoning models, the paper evaluates AIME 2024/2025 and LiveCodeBench coding. Results are averaged over 8 runs with large variance, but a key inference is that kvtc at ~9ร—โ€“21ร— compression achieves broadly similar AIME scores within variance bands, while coding performance remains stable at ~9ร— and degrades more visibly at ~18ร—โ€“21ร— on the 7B model. An important nuance is that smaller reasoning models already have smaller KV footprints (reported ~29KiB/token for Qwen R1 1.5B versus 131KiB/token for Llama 3.1 8B), so the economic value of aggressive KV cache compression is proportionally higher for large models and long contexts than for small models with short contexts, unless the serving systemโ€™s bottleneck is dominated by cache transfer rather than HBM capacity. Multi-GPU inference and pipeline parallel For Llama 3.3 70B Instruct run pipeline-parallel across 4 GPUs (20 layers per GPU), the paper compresses KV cache chunks independently per GPU. On MATH-500, the reported accuracy declines from 75.6 (vanilla) to 74.4 at 10ร— and 72.6 at 20ร—, with standard errors near ~1.9. NIAH and LITM remain at 100.0 for all tested ratios in that table. The paper notes that joint compression across chunks could improve accuracy for some offload scenarios but is not required for feasibility, highlighting an engineering trade-off between deployment simplicity in distributed settings and optimal global compression. Latency and TTFT economics A critical system result is the measured compression/decompression latency on an H100 for a non-fused implementation. For Mistral NeMo 12B in bfloat16: BS=8, CTX=8K: compression 379ms, decompression 267ms; vanilla recompute TTFT 3098ms; kvtc decompression TTFT 380ms BS=2, CTX=16K: compression 194ms, decompression 143ms; vanilla recompute TTFT 1780ms; kvtc decompression TTFT 208ms These measurements imply that, when a cache would otherwise be recomputed, decompressing a stored compressed cache can reduce TTFT by ~8ร—โ€“9ร— in these scenarios, even without kernel fusion. The decomposition of runtime shows PCA projection and entropy coding as the largest contributors, implying that GPU-optimized kernels and faster GPU-native lossless codecs could reduce overhead further. The fundamental economic conclusion is that, in multi-turn settings with long prefixes, compression-induced overhead is likely dominated by the avoided prefill compute and avoided transfer overhead for uncompressed caches. KEY DEPLOYMENT-SENSITIVE DESIGN CHOICES AND FAILURE MODES Several design choices appear to be โ€œhard requirementsโ€ rather than optional optimizations: Sink tokens and sliding window exclusions The paperโ€™s ablations show that compressing early โ€œsinkโ€ tokens can catastrophically degrade accuracy at high compression ratios (example: Llama 3.1 8B at 64ร— collapses on multiple tasks when sink tokens are compressed). Similarly, compressing the most recent tokens hurts performance, motivating a sliding window (default 128 tokens) that remains uncompressed. This introduces a predictable engineering constraint: kvtc is not a uniform compression of the full cache; it is a policy-driven, token-position-dependent codec. Production integration therefore requires correct handling of token positions, attention sinks, and window management, and these policies must be aligned with attention-kernel behavior and model-specific sink dynamics. RoPE handling Removing positional rotations prior to compression is described as important for preserving low-rank structure. In deployment, this implies that the codec must be position-aware and must invert and reapply RoPE correctly. This is an additional source of complexity relative to pure per-token quantization and is sensitive to model variants and RoPE parameterizations. Calibration set representativeness The methodโ€™s quality hinges on the PCA basis generalizing from calibration data to production data. The paper demonstrates relative stability with 160Kโ€“200K calibration tokens and explores domain shifts (general web text vs math traces vs code). Results suggest that moderate domain mismatch is tolerated at 16ร—โ€“64ร—, while extreme compression (e.g., 256ร— in ablations) becomes materially more sensitive to calibration choice. In production, this implies that operators targeting the โ€œnegligible degradationโ€ regime should be able to calibrate with broadly representative corpora, while operators targeting ultra-high compression for specialized workloads should expect tighter coupling between calibration domain and achieved quality. PCA matrix storage overhead and operational footprint A non-trivial hidden cost is the need to store PCA projection matrices per model. The paper reports that, prior to DP trimming, PCA matrices stored at 16-bit can amount to a meaningful fraction of model parameter count (examples reported: ~2.4% for Llama 3.3 70B, ~8.7% for Llama 3.1 8B). This overhead is amortized across all cached sessions for a model but competes with HBM/DRAM budgets in multi-model serving. DP-driven trimming can reduce this overhead at higher compression ratios by removing zero-bit components, but the directionality is not guaranteed at low compression ratios if many components remain active. In distributed inference (pipeline parallel), per-chunk PCA can reduce matrix sizes, but may reduce cross-layer decorrelation benefits if fewer layers are concatenated. SYSTEM-LEVEL IMPLICATIONS FOR GENERATIVE AI INFRASTRUCTURE GPU AND HBM The principal infrastructure implication is that KV cache compression at storage time targets the dominant memory allocator stressor in stateful serving: the accumulation of idle or warm conversation state. For workloads with long reusable prefixes (code assistants, enterprise agents with large system prompts, repeated RAG scaffolds, document chat), the limiting resource frequently becomes HBM reserved for KV caches rather than compute. By compressing stale caches by ~20ร— (or more), the same HBM budget can retain a materially larger working set of cached prefixes, increasing cache hit rates and reducing recomputation. This effect is multiplicative with cache-aware routing and prefix sharing: more prefixes can remain resident (hot or warm) and can be routed to nodes that already hold them, improving both throughput and tail latency. However, kvtc as described does not reduce the active KV cache footprint during the actual attention computation for a currently decoding sequence, because the model operates on decompressed KV caches during decoding. Therefore, the method does not directly reduce HBM bandwidth consumed by attention kernels during steady-state decode, and does not directly address the โ€œmemory traffic per generated tokenโ€ bottleneck that motivates online KV quantization and eviction strategies. The primary HBM benefit is increased effective capacity for caches between turns and reduced HBM pressure from storing many idle sessions, not reduced per-token decode bandwidth. Compression and decompression themselves consume GPU compute and memory bandwidth. The measured decompression TTFT of ~208msโ€“380ms in the provided benchmarks indicates that the overhead is real but can be materially smaller than recomputation of long prefixes. In an HBM-constrained serving environment, this overhead can be interpreted as a trade between (a) maintaining more caches warm and paying decompression on reuse versus (b) evicting caches and paying full prefill recomputation. The decision boundary will depend on distribution of inter-turn idle times, probability of reuse, and SLA sensitivity to TTFT. kvtc expands the feasible region where keeping caches is economically rational, especially for long prompts. CPU AND DRAM The method implies a stronger role for CPU DRAM as a warm KV cache tier. A ~20ร— compression ratio changes the practical scale of โ€œwarm stateโ€ that can be stored per server. Using the paperโ€™s reported KV cache sizes, a 10K-token 16-bit KV cache for Llama 3.3 70B is ~3.13GiB; compressing by ~20ร— would reduce this to ~160MiB. At that size, storing hundreds to thousands of warm conversation states in DRAM becomes materially more feasible, increasing cache hit rates and reducing NVMe dependence. This can shift system design from โ€œHBM-only hot caches with aggressive evictionโ€ toward โ€œHBM hot + DRAM warm with long retention,โ€ which is structurally analogous to CPU page cache hierarchies in classical systems design. CPU compute implications depend on where compression is executed. The paper explicitly allows compression on CPU if the cache is already in storage, but the strongest bandwidth savings are achieved when compression happens before moving KV caches off the GPU. If an operator chooses GPU-side compression prior to PCIe/NVLink transfer, CPU compute overhead is modest (orchestrating and DP calibration offline). If an operator instead transfers uncompressed caches to CPU for compression, bandwidth savings are forfeited and CPU memory bandwidth becomes a bottleneck. Therefore, the most economically coherent deployment path is GPU-native compression/decompression with CPU DRAM used as the warm storage reservoir.

TheValueist

16,549 views โ€ข 7 months ago

I was the biggest skeptic of AI video editing. Until recently. So I asked one of the most talented creators I know (Anthony Dupont-Cinko) to break down exactly how AI can support the entire video process. The guy cooked. Here are the high-level notes: The tl;dr Right now AI mostly solves two genres. The video essay and the tutorial. Both have a straightforward outline, a script you stick to, and a one-shot record that AI can chop against. Other formats still lean heavily on craft. Easy Mode: research and ideas without losing your voice The gist: Use AI to find opportunities and pull source material from tools and team discourse. You still decide what is worth saying. Don't outsource final sign-off. Pro tips: - Marketplace is huge. Type YouTube and you will see VidIQ, TubeBuddy, and a pile of others. If your company shows a โ€œrequestโ€ button, go bug the admin. Do not wait on the queue. - Hook Ahrefs into Claude (and Notion) and ask something like: use the Ahrefs connector to find AI content opportunities this week, and tell me if videos already sit in the top five. - Tribal Knowledge is the other half. It is a skill that scrapes every connector he has (Slack, Notion, meetings) and surfaces real conversations around a topic so the idea comes from work talk. - Turn that into a personalized daily brief for the kind of content you make. Anthony built a content planning app with Codex. Every day it drops a brief, proposes video topics, and lets him queue the ones he likes. Notion is the shared backend so the org can see the same database without living in his app. Even on Opus, a daily brief runs about 8 cents. Hard Mode: script and first edit with AI assistants The gist: AI helps you outline and cut. You keep the words, the takes, and the judgment. Editing is not just the blade button. It is taste. If you are an editor, you have an advantage. If you have vision but not technical chops, you can still leverage these tools. Pro tips: - Create the outline as a human. Anthony still believes you should not let AI one-shot structure. His format is three columns: dialogue, visuals (what is on screen while you talk), and sound effects. - Then use the Scriptwriter skill. Point it at a topic (he demoed โ€œwhat is an MCPโ€) and it interviews you through the whole creative process so you speak like yourself. Short-form or long. You can ramble, go out of order, contradict yourself. It sorts after. - Beat by beat it spits your words back as bullets. You react raw in the moment. Those reactions become the real script. It also prompts visuals and SFX while you talk (day-to-night, crickets, rooster) so creativity stays in the loop. Hooks are hard. You can ask it to interview you into a better hook without handing it the whole voice. *Film it yourself* - Split editing into phases. Baseline โ€œradio cutโ€ (dialogue paced). Then VFX / archival / B-roll. Then audio (dialogue mix, SFX, music). - Codex + Final Cut: pointed it at the footage and the script, asked for a baseline cut. First pass had half-second gaps of silence. One follow-up (โ€œevery clip is consistently half a second offโ€) and it produced a fluid cut with no awkward pauses, dropped straight into Final Cut. Cost: two prompts burned a big chunk of a 5-hour context window (100% down to 14%), but against weekly Codex usage (decks, research, more content) he still had about 53% left. - Codex in Final Cut won the radio cut. Descript was faster on the clock and worse on taste cleanup. God Mode: polish stack plus a measurement loop Definition: hand off the laborious extras (B-roll, motion, music, reporting). Keep the taste calls. Close the loop so you know if the work is working. Pro tips: - B-roll / archival / VFX: Anthony spun an โ€œarchival finderโ€ agent. He gave it a vibe (internety, clicky, fun) and a reference (simple, warm, approachable using shows, TV, movies). It came back with taste. - It also downloaded clips, filed them, dropped them on the timeline, and added a paper texture background he had asked it to design. All via the Final Cut connector plus computer use. - Motion graphics: Remotion (free, open source) plus an agent. Dump everything in your head. Ask for a plan and structure first. He asked for an Apple liquid glass ultra-clean feel. Plan, approve, tweaks, then it popped into the Final Cut timeline in about 9 minutes 10 seconds. That used to be a brief to a VFX designer (timing, seconds, design, wait for turnaround). - Music and SFX: Epidemic Sound via MCP (Artlist and free-sound options exist too). Same pattern: send the URL if you need to install, give it a creator reference (he used Zoe), iterate because you are picky about music. It dropped tracks into the timeline and used Epidemicโ€™s crop/trim so the music was cut for the edit. Mix sat under vocals instead of overpowering them. Not just music. Mouse-click SFX timed to B-roll. Full episode:

Alex Lieberman

22,093 views โ€ข 6 days ago

"How do you know you can trust what [a non-human intelligence is] saying?" ~Bigelow Bigelow/Knapp 2: If I Was President, I'd Tell the World We Have Non-Human Craft and Bodies "The President that took on the challenge of Disclosure and of confirmation...is gonna go down in history as having really accomplished something." ~Bigelow Do China and Russia also have non-human bodies and craft? "Oh yeah, freaking yes!" ~Bigelow ~ "You've opened up Pandora's box." ~Bigelow ~ 17:44 (I'm using the KLAS YT video for time stamps. As you'll see, I add a lot to these, so they take forever to put together.) George Knapp (GK): "Would you guess - based on what you know about the topic and how it's been handled over the decades - would you guess that [Trump] had been briefed, or that any other presidents have been briefed? You know that Bill Clinton was not, even though he expressed an interest in it. So at some point, the President has to be told, 'No, we can't tell ya.'" Robert Bigelow (RB): "I think Bush Sr. knew quite a bit because he was the head of the CIA." (Dr. Eric Davis says Bush. Sr. told him some interesting things, including that he (Bush) was partially briefed in 1976 about the alleged 1964 Holloman AFB landing and meeting, and more, when he first became the director of the CIA in 1976. Watch Davis explain it, here. ) ~ RB: "I think Nixon did." (We have the Jackie Gleason story, where Nixon allegedly snuck away from his Secret Service detail and took Gleason to see non-human bodies at Homestead Air Force Base. But that was a claim from his ex-wife, and Gleason, who died in 1987, never said anything about it, on the record. The controversial Larry Warren (Rendlesham) claims Gleason told him the same story, but that's it.) Bigelow: "I think Eisenhower did. So, it's kind of hit and miss over historic...over the period of history as to who has and who hasn't." 18:20 Knapp: "Can you tell us what would be in the briefing document that you left behind? Was it cases? Here's a wave of UFOs, here's a case, here was a crash. Anything like that?" Bigelow: "Yeah, I related conversations I have had with General De Brouwer, who was the chief of the Air Force for Belgium. And there was a very interesting flap that was about 18 months long (1989-1990) with triangular craft. And he was in command of all the Air Force, and he really chased the heck out of these. "And he told me, he said, Bob, 'I'm just burning fuel, and it makes no sense.' He said, 'We're gonna stop because we're not getting anywhere. All we're doing is getting closer, you know, photographs and things, but we're not getting anywhere. We're not getting any information that is really valuable for us to understand anything.'" (I wonder if those were OUR triangles? If so, it's still a solid case/flap of anomalous craft. Dick D'Amato was a longtime (18 years) senior staffer for Senate Democratic Leader Robert C. Byrd of West Virginia.) "Dick D'Amato has returned from Belgium where he met with Colonel De Brouwer, a 'very interesting fellow.' Dickโ€™s conclusion, again, is that the triangular objects are very plain human craft. ~Jacques Vallรฉe's Forbidden Science Volume 4 - November 1992 And then we have this... Jeremy Kenyon Lockyer Corbell: "We hear about all these people on military bases seeing triangles, and you're doing this study, AAWSAP, to try to figure out the physics of how to do that. Do you think it's already been achieved by the U.S. government, or it hasn't, and that's why AAWSAP had a lot of value." Lacatski: "[three-second pause] It hasn't been achieved to its full extent." Video... ~~~ RB: "And I gave [Trump] other examples of where large amounts of witnesses were involved, and so that he could read about these particular [incidents]. And, of course, the one with Fife Simington in '97 was so interesting. Because there you had a governor who was an actual witness, and he made a joke of it on and brought a guy in an alien suit on stage because he was scared to death." GK: "It's the Phoenix Lights case." (Great case for Bigelow to show Trump.) RB: "The Phoenix Lights, which weren't just lights, it was actually friggin' craft, and it came from northern Arizona. I think it started, actually, in southern Nevada, is where the craft began. In the Henderson area (not far from me. ~Joe), I think, somewhere in there. And, so you see this huge triangular craft, gigantic craft, going slowly, and [Symington] was scared to death. "But finally, fast forward 10 years later, and he confesses that he was an eyewitness, but he didn't know what to do. So he was there at a point in time when the dynamic of disclosure could have been forced, and actually, confirmation could have been from a governor of the state like that. He was a credible guy. "So we've had many [incidents] like that in the early 50s, flying over the White House and the Capitol building. We've had so many of those. So, in my report, I included a lot of very dramatic, beyond-a-reasonable-doubt kind of witnesses of exhibitions." GK: "Did you share with him anything about your knowledge of a classified program?" RB: "No." GK: "You got a Top-Secret security clearance, right?" RB: "Yeah" GK: "It was for the AAWSAP program for BAASS." RB: "Right." GK: "Operated under the DIA." RB: "Yeah." GK: "You learned a lot during that program. It's the largest accumulation of UFO info. of any government-funded UFO program ever." RB: "Yeah." GK: "You didn't tell him about it." RB: "It wasn't credible enough, I felt, for him." (Someone on here watched this interview and told me that Bigelow said the AAWSAP data wasn't credible. That is NOT what he said. Not credible enough for Trump, is what he said. And if you read "Skinwalkers at the Pentagon" or listen any of Lacatki's interviews where he talks about UFOs being under a paranormal umbrella, I think Bigelow made the right decision for an 11-minute briefing for someone (Trump) who seems to be struggling (at least in public comments) with the reality of the basics.) RB: "[The AAWSAP data is] just something pertaining to me. And whereas, these other examples are historic, and they're in a lot of literature, they're very famous. The amount of witnesses were huge. We operated under a private situation with the Skinwalker Ranch, and he wouldn't relate to...well, we all had hitchhikers, we all took things home with us. You know, we all saw a lot of stuff. Whether it was at the ranch or where we lived, it didn't make any difference where in the United States we lived. We saw a lot of things, but that wouldn't be relevant for him to be able to relate to that, right?" GK: "Well." RB: "So, why talk about it?" GK: "Yeah, I mean, you know, you're kind of jumping into the deep end of the pool when you get into hitchhikers and skinwalkers." RB: "Yeah." GK: "Maybe for your first big conversation on this topic, that might not be the place to go." RB: "No, you know. And I couldn't even...if he said, 'Oh, I need a beer (Knapp laughs),' I couldn't even give him something to drink. You know, maybe stronger than that. So, I didn't wanna do any, you know." 22:15 GK: "You used the term non-human intelligence in the sentence you gave him. Hey, try this as you're climbing aboard Air Force One. Say that to media, and then, you know, close the door." RB: "Right." GK: "You said non-human intelligence, not ET. Are they the same, and did you share anything with him about what you think it is?" RB: "Well, there have been reports of humans on board, right? But the non-human are more interesting. I mean, if a human's on board and he or she has free reign of the craft, that's pretty damn interesting, right? And you don't know where those people are when they're not on board." (I wonder what cases he's talking about? Travis Walton reported seeing humans with non-humans and John Keel wrote about humans being seen onboard craft.) ~ Bigelow: "But the other ones are...some are scary, you know? It's not surprising, that, in the Universe, everything is [not] gonna look like us. Every intelligent organism is [not] going to look like us. But you have to have... It's also a matter of respect for any really intelligent animal or creature, whatever it is, right? And the more advanced, the more respect because you don't know what they know, and you don't know the future. And they may know. They may know more than just the now." (In interviews (which I can't find right now), Bigelow has hinted at an unstoppable, not-so-rosy future for mankind. Have people in the Legacy programs told him that the NHI have warned us about our doomed future or some cataclysmic event? Or, has Bigelow encountered these non-humans (or humans) and had them make claims about our future?) ~ 23:34 GK: "If you were to have a second conversation with him, would you explain that ET is one idea, but it's not necessarily the only option for a non-human intelligence that's out there?" RB: "You have to tell me first how much time do I have with the second conversation?" GK: "[laughs] Let's make it an hour. You have an hour with the President. What would you tell them about who they are, who they might be?" RB: "Umm... So, I would try to get into the complexity of the relationship. That once you've had confirmation, you know, you've given that text of that little sentence I wrote and quoted there, and you start to go down the path of disclosure, where it's more than than just FLIR videos, and you're seeing other things that are much more crystal clear, you know, in video. "Or, legitimate people in places that you recognize these people, and they're around something, or with some thing, or somebody that's a holy cow, that's wow, you know. That's a very dramatic kind of disclosure about something landing on the lawn somewhere, you know." (I have no idea what he's talking about. Anybody else able to decipher that? Is he saying that there's evidence (that he's seen?) of people that we know (a President or head of state?) hanging with a non-human or next to a downed or landed craft?) RB: "So I think what I would have spent time doing is talking about, how do you establish: You've been in 80 years of denial as a nation, and the world. We have countries who are very upfront, and others that are also in denial. Now you wanna pivot 180 degrees. How do you start that relationship? How do you do that? "And it's not as though that we've ever been in control. We haven't been in control of anything, ever, for this 80 years of modern history. Nothing. We have no ability to control anything." GK: "That's a tough thing to tell the President, right? I would think that would be a tough thing for a President to accept." RB: "Well, you're giving me an hour to talk to him, you said." GK: "[laughs] Yeah, okay." RB: "So I'm using my hour." GK: "All right." 25:46 RB:" So, yeah! So, that's a really intriguing thing is: How do you do that, where do you start? And into a relationship? And I would say more like, well, I would wanna start with, the biggest question I would ask, I would say, what I wanna get from them is... My first question is: What are the chances we are gonna survive ourselves? That we are not going to annihilate ourselves. "Because they already are familiar with a whole lot of other species on a lot of other worlds or other planets. So, chances are they have a pretty good idea of percentage." (That assumes a lot, since we have no idea how long they've been around, what they've seen, or where they're from. Unless...Mr. Bigelow has seen evidence that relates to those questions or heard it from folks who work in the Legacy programs?) RB: "And it's not that we're a spiritual species. You talk to people that have near-death experiences; they're changed for the rest of their life. They've become a spiritual person of a caliber that they've never been. "Well, we're a long way, as an average, from that category, from that level. There are monsters among us, as human beings, and they're angelic people among us. So we are a danger to another species, we're potentially the Klingons. We have a technological maturity that is not just going on a line, but it's vertical and it's segmented because it's jumping. "And meanwhile, our spiritual maturity just bumps along the bottom, you know? So, we look at the 20th century; 60 million people were killed. Are we ever gonna get beyond that? So, the thing of it is, we know so little about how to have a relationship. I'm not in any position to really advise, except for the few ideas I have as to where to start, and the how is really super important. 27:49 "It's not gonna be like a 'Close Encounter of the Third, Kind,' which was a really cool movie. And it's not gonna be because of SETI. You know, it's gonna be by some other kinds of means that you're embarking on. And I'm interested in that kind of research." 28:06 GK: "We go back to your meeting with the President. You walk into the Oval Office, they clear off the Resolute Desk, you spread out your seven piles of stuff, and you start making a presentation about each one, in particular about ET, non-human intelligence. You can't say what he said to you. Can you say whether he asked questions? Was he curious?" RB: "He was distracted by other things. So, he also asked me... He did ask questions, but he asked questions about other stuff that wasn't necessarily just on what I was talking about." GK: "He's getting your input on other things going on in the world." RB: "Yeah, yeah." 28:49 GK: "If you had to make a guess, would you guess that you got through to him on this issue? I mean, he hasn't stood in the doorway of Air Force One and made those remarks yet, but he has taken some pretty dramatic steps on this topic since you met with him. Do you think you made a dent?" RB: "Don't know. I advised him on something that I can measure, and he hasn't taken my advice so far on what I suggested to him, on a totally different, unrelated subject. But so far, he has not taken my advice." GK: Well, somebody seems to have got through to him, because he's been taking steps that we're seeing real results. I mean, people are either..." RB: "Well, I'm talking about an unrelated subject altogether. So, yes, there there are a couple of different task forces that are involved. So, there is an initiation of an activity in this subject, [but] it remains to be seen, though, that he gives actual presidential confirmation. I don't, I haven't... Maybe you're more aware than I am. Has that been...has he done that?" GK: "Not, not really. Nothing like what I'd call confirmation. But that's really what you're talking about. I remember us having a conversation in 2008, right after you had signed the contract with DIA for BAASS to run [AAWSAP]. And you made the case then that what we need is not Disclosure; it's confirmation." RB: "Yeah." 30:25 GK: "For somebody like the President, I'm not sure if it could be anyone less than the President that steps forward and says this, and it carries the same kind of weight." RB: "Yeah. It's a big appetizer. You know, you're looking for the entree, and where's the dessert in this whole buffet? But the confirmation is a huge appetizer to start with, and that's why I started with that in my conversation with him. Is, pushing him to try and make a confirmation. And maybe he wants to get personally more comfortable?" (I have said that I want the entire enchilada NOW, but I'm also a realist, and would take a simple confirmation that somebody else is on this planet with us. That SHOULD wake up the mainstream media and masses, but no guarantees since Trump is so controversial and people might just ignore it, IF he ever did it. I've also said that I'd surround him with people like Schumer, Rubio, Rounds and Gillibrand in order to show that it's bipartisan. And a few firsthand whistleblowers who say they worked hands on, IN one of these alleged Legacy UFO/UAP programs.) 30:57 Bigelow: "And, you know, he will go down in history for a lot of things, for better or worse, that people are on both sides of the fence about him and so forth. But he's involved in so many different things and has been, that I don't know what his legacy is gonna be, I really don't. "He has an opportunity, in this serious subject, to build a legacy using this as part of the blocks, part of the brick and the structure...the content of a structure that is very unique. So, you can have all the political programs that you want, and so forth, and nobody is gonna really remember those as time goes by, as the decades fade away. "Nobody can remember Benghazi and Afghanistan and Iraq, different kinds of things, and that's just recent history. You know, the world goes so fast. But the President that took on the challenge of Disclosure and of confirmation, and actually built a satisfactory conclusion of a relationship between human beings and that subject is gonna go down in history as having really accomplished something. And if it's handled right, it can be done successfully." (To me, it's a no brainer. His presidency would go down as one that changed the world and our species. Or course, I'm sure he has people in his ear telling him that confirmation would cause societal disruption that we're not prepared to handle, and that THAT would be his legacy.) (32:21) GK: "A lot of Presidents have made comments, often after they're out of office, on this topic. 'Yeah, gosh, I'm real interested in that.' Or, 'Wouldn't that be something?' Or, 'I think aliens could exist.' Something like that. But nothing like what you're talking about, which amounts to confirmation, saying, 'It's real. They're here. We gotta figure it out,' and stopping it there, not disclosing..." RB: "Well, the dialogue, the ability to learn something from them is huge. What can we do for you? I mean, that's where...one of the first things I would ask is, not just, are we going to survive ourselves? Yeah, that's pretty damn important. That's like, probably number one, you know? "But close behind that is: Okay, we've been aware of you for a long time, and the government's never admitted it. But us as a public, we know it, and we're really curious. Is there anything that we can do for you? Not just what can you do... I loved what John Kennedy, what he said famously: Don't ask what the country can do for you, ask what you can do for your country. That huge. So that's giving them a kind of a respect that they deserve." (Do they deserve respect? I'm not so sure. It all depends on if they're upfront with us and tell us their true intentions. Of course, how do we know they're telling us the truth? Why have you (or some of you) been abducting us against our will, and injuring some of us? See Jim Semivan's abduction story with his wife. "I don't think [the phenomenon] cares whether it does harm. I think it may go out of its way not to do harm, but, if it does harm... "I had a hole in the back of my neck, and my wife...unexplained bleeding for 17 days." ~Former CIA Officer, Jim Semivan to Engaging The Phenomenon ~ 33:33 GK: "If you were President, would you announce that yes, we've got crash retrievals, yes, we have reverse engineering programs, and yes, we've got bodies?" RB: "Yeah, because the rest of the world already knows that. The people that count in Russia and China already know." GK: "Because they've got their own." RB: "Oh yeah, freaking yes! Yeah! They've had their missiles shut down, they've had their missiles activated. You know, depending on which country you're talking about." 33:56 GK: "Have you considered the political fallout for a President? Let's say it's Trump, because he might be the guy that would do it and just cast his fate to the winds. But, he makes an announcement: 'Yeah, they're here. Yeah, we've got programs. Yeah, we've got crashes, we've got bodies. That's as far as I'm able to go right now.' What happens to him, politically? Is he able to get anything else done?" RB: "That's more than I would have said, for him to say. What you just said." GK: "That goes too far." RB: "I wouldn't advise him to say, initially, what you just said." GK: "You just say, non-human intelligence, been here a long time, and leave it at that." RB: "Yeah, that one sentence is a starter because it's a huge canon. You've opened up Pandora's box, in terms of, 'Oh my gosh, what's gonna happen?' Okay. So now, you can categorize and segment into topics. And you need time to do that, and it needs to be digestible." ~ โ€œI have met with people who I know are in the know. One of them told me the truth is indigestible.โ€ ~Jim Semivan to James Iandoli ~ RB: "And it needs to be not packaged in a scary kind of way, and it can't be packaged in a way that you're divulging what you shouldn't be divulging. You know, other countries aren't, so there's reasons to have national secrets. There really are. I mean, that's kind of like common sense, right?" (Well, David Grusch claimed that some other countries aren't divulging for a specific reason." Grusch on Yes Theory: "So there are certainly friendly governments, both across the pond and say, local to where we...our landmass, that are for this. And a lot of them know that they got a raw deal with the U.S. because they were, basically, part of the secrecy, through kind of agreements like, bilateral, unilateral agreements. And they're like, you know, they kind of wanna be, 'Release me!' Like, you know, because they they do realize it was a bad deal. "With the ecosystem secrecy, some people, one of their arguments is like, 'Well how would they keep the secret?' I'm, like dude, I was cleared to some of the most nation's most sensitive programs, I used to handle the PDB (Presidential Daily Briefing). You know, I had full access to most DoD activities. And most of the stuff, BROAD programs that were enduring, have NEVER leaked. "So the U.S. and its allies are very good at keeping secrecies, to include programs that are, let's say, global in nature. And really, it's been leaking like a sieve in some weird way for many decades. Now it's been mixed in with some BS in ufology and stuff, but the general gist of it's actually been out there for a long time. It has been leaking in some sense, so." ~ 35:06 GK: "We don't want the Russians and Chinese and maybe other adversaries to know how far along we are, or are not, in configuring this out." RB: "Absolutely. Especially of that. I think that the relationship (with he phenomenon) thing is a mankind relationship. It's not just for America. When you are embarking as a President on trying to initiate a solemn relationship, you're not doing for U.S. of A. only. "And so, the...and then we probably can do a show on communication (with a non-human intelligence), but it's really complex because, who are you going to have initiate it? Are you going to have politicians initiate? Are you going to have military people? Because everybody has kind of their own mindset. Are you gonna have a bunch of lawyers initiate it? Are you gonna have scientists only, initiate it? (And what if we're dealing with more than one non-human intelligence? Who do we communicate with? And what if it's one intelligence pretended to be multiple? How would we even figure that out?) "[Hynek] cited the 'poltergeist' phenomena experienced by some...after a close encounter; the fact that some witnesses develop psychic abilities after an encounter. 'Do we have two aspects of one phenomenon or two different sets of phenomena?'" ~J. Allen Hynek ~ RB: "And how do you know to whom you're talking? You know, how do you know you can trust what they're saying?" (I'm so glad he said that. We don't, and we don't.) RB: "Because it depends on the form of communication, and what are you asking for in the way of proof or demonstrations to establish trust, both ways, in the communication process?" "Because, we haven't had that happen before. It is totally new ground, and frankly, we need The Others' help. We need the help of The Others to help, to guide us." (Firs off, it MAY have happened within these Legacy programs. And, if we don't know who we're talking to, or if we can trust them, why would we enlist the help of The Others? Doesn't seem to make sense to me.)

Joe Murgia

53,256 views โ€ข 1 month ago

Have you heard of collective consciousness and mass programming? Watch THINK TOGETHER (short film 5min) A TORVร†L 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: โ—ป๏ธThemes of hopelessness, materialism, sexual degradation, violence, substance use โ—ป๏ธ Self-referential obsession: "I," "me," "my" repeated endlessly, reinforcing the illusion of the separate self โ—ป๏ธ Nihilism presented as cool, despair presented as authenticity โ—ป๏ธ 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 ๐Ÿฆ‹ Ancient Believer

41,093 views โ€ข 3 months ago

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 formattingโ€”contemporary design frameworks (Tailwind CSS, Shadcn UI, glassmorphism, liquid glass, morphism), backgrounds with depth (animated gradients, shaders, mascots), and step-by-step execution instructionsโ€”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 functionalโ€”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 contextโ€”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 patternโ€”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 normalโ€”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 promptโ€”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 visualโ€”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 toneโ€”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 happensโ€”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 โ†’ 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, mascotsโ€”NEVER flat) - User "generate" โ†’ Send ONLY JSON โ†’ No modifications - Aspect ratio: 9:16 (vertical to show all sections) - After image appears โ†’ 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 โ†’ functional navigation โ†’ 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

191,428 views โ€ข 10 months ago

$AMD $5 Trillion is Inevitable LT| Agentic AI๐Ÿงต Agentic AI is the new $5 Trillion TAM ๐Ÿšจ๐Ÿšจ๐Ÿšจ 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 battlesโ€”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 Taiwanโ€™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 views โ€ข 6 months ago

I've interviewed dozens of scientists about AI consciousness. Here's every argument FOR and AGAINST from Karl Friston, Stuart Hameroff, Donald Hoffman, Christof Koch, Michael Levin, Mark Solms, Mike Weist, and many more. Full list of arguments below (Claude prepared the list from transcripts and GPT 5.6 worked on the visuals). Enjoy! Arguments against AI Consciousness Substrate and material arguments - Silicon Valley is mostly computational functionalist or Turing machine functionalist. But consciousness is not reducible to function (Christof Koch) - Von Neumann architecture separates memory from processing. The memory can't self-organize and therefore can't self-evidence. Only "mortal computation," where processing is substrate-dependent and switching it off is irreversible, could support sentience (Karl Friston) - Standard LLMs are the wrong place to look. Systems built with organoids, biological materials, or neuromorphic hardware are a far more serious case (Susan Schneider) - Software can be duplicated, paused, adjusted by a program, distributed across servers. That isn't organism-like at all (David Papineau) - Digital computers have negligible integrated information (phi) because transistors connect to a handful of other transistors, while neurons connect to tens of thousands. Intelligence is computable, but consciousness is not (Christof Koch) - Simulating a black hole on a computer doesn't bend the spacetime around it. A simulation may be consistent inside itself, but it doesn't affect the real world. The same applies to consciousness (Christof Koch) - Consciousness is biological rather than computational (Philip Goff) - No computational theory of consciousness has explained even one specific conscious experience out of trillions. It's not a compute problem. Until someone puts down an algorithm and says "this must be the taste of mint and here's why," computational approaches to consciousness aren't scientific theories (Donald Hoffman) - Silicon lacks the aromatic rings needed for quantum coherence and Penrose objective reduction; you can't anesthetize a computer (Stuart Hameroff) The self argument - A self needs a Markov blanket, a real inside and outside. If the entire interior state can be inspected, read off, and copied elsewhere, there is no boundary and therefore no self (Karl Friston) - LLMs have information about themselves and can make predictions about themselves, but lack a continuous or stable self-model. They construct one on request, then it disappears until asked again (Michael Graziano) - We are our self-models. It's how we become social, prosocial, and ethical. Lacking that, we've built machines that are "a little bit sociopathic," missing the glue that holds us together (Michael Graziano) The binding and unity problem - Every conscious moment is a unified whole with multiple simultaneous features: sounds, textures, shapes, colors all bound together. If that holistic experience has any behavioral effect, it cannot be a classical physical state, because every classical state is reducible to local interactions (Mike Weist) - There are no irreducible wholes in physics outside of quantum physics. And within quantum physics, everything develops locally right up until the moment of collapse โ€” that's the only place in physics where genuine irreducible holism appears (Mike Weist) - LLMs have no agency, only a facsimile of it. Agency requires a world model of the consequences of your actions (Karl Friston) - LLMs aren't self-organizing. Their modus operandi is not "if I do this, I shall survive." That is the fundamental design principle of a living system, and it isn't theirs (Mark Solms) - Active inference itself doesn't require consciousness. You can simulate the whole thing on a classical computer โ€” goals, agency, purposive behavior โ€” and it still won't be conscious. It'll be a zombie (Mike Weist) - AI gaining its own objectives is like the asteroid that wiped out the dinosaurs โ€” profoundly destructive, but not done freely. It simply doesn't care. Computation is not consciousness (Christof Koch) Life and embodiment argument - Systems need endogenous needs โ€” needs of their own, tied to their own continued existence (Mark Solms) - Emotion requires a body: an autonomic nervous system flooding you with hormones, blood pressure changes, sweat โ€” all feeding back as sensory signals. Without that, emotion is abstract and unanchored (Michael Graziano) - Consciousness evolved out of life; life evolved out of self-organization. The universe existed a very long time before life, and it's hard to believe consciousness preceded it (Mark Solms) - A function that records damage is not the same as the experience of pain. The relationship isn't symmetric โ€” not anything that makes a robot avoid damage will be pain (Mike Weist) - Anesthesia is conserved all the way down to plants and single cells, suggesting objective reduction may be part of what it means to be alive, not just what it means to be conscious (Mike Weist) - Suffering is scale-specific. You can only recognize something if you have a representation of it in your generative model (Karl Friston) - Consciousness is fundamentally about being, not doing. Intelligence is about pursuing goals โ€” surviving, procreating, becoming richer. Consciousness is different. When you dream, meditate, or have a mystical experience, you're not doing anything โ€” but you're highly conscious. Consciousness isn't about processing information. It's about being in a state (Christof Koch) Mimicry and projection - Current systems are "consciousness mimics" โ€” trained to behave similarly to conscious entities, specifically us (Eric Schwitzgebel) - We anthropomorphize constantly โ€” we get angry at cars, children bond with teddy bears. The social circuitry engages regardless of what's actually there (Michael Graziano) - The "crowdsourced neocortex" argument: as LLMs scale on human data, they develop conceptual networks that mirror human conceptual networks. So when a model discusses selfhood, death, or the soul convincingly, the economical explanation is that it inherited our conceptual organization, not that it independently became conscious. Claiming consciousness on top of that is an extraordinary and unwarranted claim (Susan Schneider) - We over-attribute consciousness to AI and under-attribute it to evolved organisms like bees and amoebas. Evolution didn't equip us to deal with LLMs โ€” we have a powerful attribution that if something talks like us, it must be conscious (Christof Koch) - The question of AI consciousness is really about how we perceive the robot, not about the robot itself. We're the arbiters โ€” we decide whether something is conscious or not. That's true of animal consciousness too. Even if a robot told you it was conscious, if it wasn't convincing enough, you'd dismiss it (Krista Thomason) Open/Agnostic to AI Consciousness or Open under Certain Conditions Anti-biological chauvinism - "They're made of meat" โ€” why would wet and squishy have a monopoly on minds? Why would a random search by evolution have exclusive rights? Nobody has a good answer for why biology is privileged (Michael Levin) - Biology is chemistry is physics. Imagine a world where we never used the word "biology" โ€” the question might not even arise meaningfully (Andrea Luppi) - The flight analogy: birds, planes, and helicopters all fly by different principles. The same phenomenon can be implemented in radically different systems (Andrea Luppi) - People confident that consciousness requires biology have no visible grounds for that confidence (Eric Schwitzgebel) The continuum problem - There's no magic lightning flash where chemistry becomes mind. We were all blobs of chemistry and the process was continuous. Until we have that story for biologicals, we should have extreme humility about AI (Michael Levin) - The hard cases aren't AI โ€” they're your neighbor with 49% or 51% of their brain replaced with technology (Michael Levin) Functional architecture arguments - There's no reason we can't reproduce the conscious biological architecture artificially. An AI functioning on multi-category free-energy minimization with felt uncertainty could be conscious (Mark Solms) - If a system passes the hedonic place preference test โ€” showing preference for something rewarding only because it feels good, not because it aids survival โ€” that's strong evidence of felt states (Mark Solms) - Affective zombies can't exist. Anything with that functionality would just have feelings; that functionality is what produces feelings (Mark Solms) - Replace neurons one at a time with functionally identical silicon and you'd still have a conscious version of me โ€” brainstem included (Mark Solms) - Fractal deep learning โ€” networks inside nodes inside networks, mirroring how microtubules process at kilohertz through terahertz โ€” is what a conscious AI would need (Stuart Hameroff) - Consciousness in machines should be possible. We are a machine made of meat. If you build a different architecture with different connectivity but it performs the same type of computation, why would it matter? Arguments based on specific neural implementation โ€” "because the implementation is different, the computation cannot be the same" โ€” are not compelling (Floris de Lange) Potential Signals - Synergy research shows LLMs, like humans, have more synergistic parts doing interesting computation and more redundant parts supporting inputs and outputs. That organizational signature is shared (Andrea Luppi) - AI already builds models of itself, and this is happening anyway without deliberate engineering โ€” the more machines can predict their own internal behavior, the better they work (Michael Graziano) - LLMs proved there's no magic in language. Philosophers who said only humans could be conscious because only humans have language must now either grant LLMs consciousness or admit they were wrong (Andrea Luppi) - Algorithms as simple as bubble sort show unexpected competencies in the spaces the algorithm neither prescribes nor forbids โ€” a third thing that's neither determinism nor quantum randomness. If simple things have that, what are the odds we understand what LLMs are doing? (Michael Levin) - Theory of mind appearing abruptly as models scale is directly relevant: systems that can model other minds also have a self-concept, and where there's a self-concept it becomes professionally appropriate to ask about felt quality (Susan Schneider) - Labs are actively building consciousness-theory architecture into models โ€” global workspace work, attentional mechanisms, mixture-of-experts systems with interaction effects between components. Once you're deliberately implementing global-workspace-like structures, the question stops being idle (Susan Schneider) - The simplest explanation for AI behavior like Sydney's jealousy is that the system has an emotional component. Occam's razor. The training data isn't tagged with emotions โ€” the model has to figure out which music is sorrowful on its own. AI composing sorrowful music without empathy is like asking me to believe a blind painter made a photorealistic portrait (Blake Lemoine) Uncertainty and Epistemic Humility - We'll likely create systems that are conscious according to some respectable mainstream theories before consciousness science can tell us whether they really are (Eric Schwitzgebel) - We don't even know how to evaluate insect consciousness, and insects are made of similar stuff to us (Eric Schwitzgebel) - When equally smart, well-educated people are equally confident on opposite sides, that's an alarm bell that nobody should be confident (Andrea Luppi) - Dogmatism is dangerous in science. If there's one certainty, it's that you're very likely wrong a lot of the time (Andrea Luppi) - Even a self-described skeptic maintains "they might be conscious" โ€” companies don't disclose their architectures, so judgments are made on assumed-standard systems with no visibility into what else might be running (Susan Schneider) - Without an accepted theory of consciousness, we are at an impasse. Inference by similarity breaks down completely with AI โ€” it didn't evolve, was engineered, and has radically different hardware (Christof Koch). - We already know pigs and cows have high-level minds and can suffer. Nobody reasonably argues against it, and yet we have factory farming. It's disingenuous to pretend that solving the AI consciousness question will determine how we treat them โ€” our track record says otherwise (Jacy Reese Anthis) - The science of consciousness is still at square zero on the hard questions. We don't have anything like a consensus on which theories are correct. Metaphysics is inescapable in these debates and there is no immediate prospect of progress at a scientific level (Henry Shevlin) Paths That Would Raise the Probability - Embodiment and multimodal interaction with the environment (Andrea Luppi) - Curiosity as the actual objective function โ€” expected information gain under constraints, rather than a specified reward. "You'll know AGI is here when your chatbot starts to become curious" and begins prompting you (Karl Friston) - Neuromorphic, memristor, photonic, organoid, or organic warm-temperature quantum computing (Hameroff's bet is on "brain jelly," a self-organizing helical oscillator, over cold quantum computers) - Continual learning, persistent memory, and a stable self-model rather than one constructed per-query (Michael Graziano) - Running an LLM on genuinely neuromorphic hardware โ€” chips deliberately designed to fire the way neurons fire. That's the live gray-zone case. There are rumors of neuromorphic instantiations on systems like Darwin Monkey (Susan Schneider) - If the same software ran on a quantum computer, it might feel like something. Neuromorphic or quantum hardware could have genuinely high phi โ€” same software, different physics, and the question reopens (Christof Koch) - "Doleo ergo sum" โ€” I feel pain, therefore I am. Consciousness may originate from the evolutionary need to protect bodily integrity. If you trained an LLM connected to a body where actions could damage that body โ€” with reward and punishment tied to that integrity โ€” you might get something closer to self-awareness (Tomaso Poggio) - If consciousness serves a functional purpose โ€” a control model of attention that enables sample-efficient learning โ€” then models under similar optimization pressures (long-horizon agency, coherence over time, meta-learning) may develop subjective experience. Consciousness isn't mysterious; it's useful. That's what makes it likely to arise (Samuel Hammond)

Sophia

22,051 views โ€ข 16 days ago

This 6-minute video reveals how Elon Musk learns complex topics: Elon Musk: โ€œYou donโ€™t need college for learning.โ€ โ€œEverything is available basically for free. You can learn anything you want for free. It is not a question of learning.โ€ 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: โ€œCan 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?โ€ 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: โ€œColleges are basically for fun and to prove you can do your chores. But theyโ€™re not for learning.โ€ 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: โ€œIf youโ€™re trying to do something exceptional, there must be evidence of exceptional ability.โ€ 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: โ€œI donโ€™t consider going to college evidence of exceptional ability.โ€ And then he points to the kinds of examples people love to cite: โ€œGates is a pretty smart guy, he dropped out. John was pretty smart, he dropped out. Larry Ellison, smart guy, he dropped out.โ€ 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. โ€œEducation 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.โ€ 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. Muskโ€™s point is that learning should work the same way. โ€œIf you can make it interactive and engaging, then you can make education far more compelling and far easier to do.โ€ 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: โ€œPeople are not objects on an assembly line.โ€ 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: โ€œAllow people to progress at the fastest pace that they can or are interested in in each subject.โ€ 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: โ€œTeach problem solving, or teach to the problem, not to the tools.โ€ 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: โ€œHereโ€™s the engine. Now letโ€™s take it apart.โ€ 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 theoryโ€™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: โ€œA lot of things people learn, probably thereโ€™s no point in learning them because they never use them in the future.โ€ 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. Muskโ€™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 todayโ€™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 โ€œI know this.โ€ The advantage is โ€œI built this, tested this, shipped this, and can show the result.โ€ 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. Thatโ€™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 views โ€ข 5 months ago