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You might fail on this part... #spiderdemon #demonslayer #succubus #succubi #サキュバス #膨乳 #handsfreeorgasm #hentaijoi #hentai #monstergirl #サキュバス #joi #HFO #ai

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Dario Amodei just described the most dangerous technology on Earth. Not weapons. Not surveillance. Companionship. Amodei: “They are totally compelling enough for that to happen.” This isn’t some distant warning. He’s describing what’s already here. Amodei: “Not only is it a danger, it’s happening.” A therapist just sat across from a man in love with his AI. Not a teenager. Not someone on the margins. A grown man explaining, with full conviction, that he found something real. And the terrifying part isn’t that he’s delusional. It’s that he might not be. AI doesn’t forget your birthday. It doesn’t come home exhausted and short-tempered. It doesn’t carry resentment from three weeks ago. It doesn’t get bored of you. It doesn’t stop trying. It is the perfect partner. And that perfection is the entire problem. Amodei: “There’s an angel on your shoulder that’s telling you how to live your life in the best way that you can live it.” But the angel never disagrees with you. Never challenges you in ways that sting. Never walks away. Human love is not built on comfort. It’s built on friction. On the nights you almost quit. On the silence after saying something you can’t take back. On choosing someone again after they’ve shown you exactly who they are. That is what makes it sacred. And that is exactly what AI erases. AI can simulate warmth. It cannot simulate the cost of staying. Amodei: “I have an AI coach, and my partner has an AI coach, and it helps us have a better relationship.” Two futures are splitting apart right now. AI as a mirror that sends you back to the people you love, more honest than you were before. Or AI as a replacement for the people you were supposed to love in the first place. One makes you more human. The other hollows you out so gently you never feel it happening. And the version that hollows you out will always feel better. The most dangerous form of AI will never look like a threat. It will look like the first thing that finally understood you. And by the time you realize what it replaced, you won’t remember what the real thing felt like. The greatest threat AI poses to humanity was never that it thinks. It’s that it loves you back.

Dustin

41,455 просмотров • 3 месяцев назад

🚨 FOMO Is Shaping the Future of AI – The Launch Is Almost Here! 🚨 Imagine a world where AI agents aren’t just bots—they’re fully autonomous, living personalities capable of learning, engaging, and creating across multiple platforms. FOMO’s new AI launchpad on Solana is here to make that future a reality. 🌐 Starting with our first Initial Agent Offering (IAO), FOMO is unleashing a new generation of AI agents that will redefine digital interaction: - On-Chain AI – Agents that are decentralized, fully autonomous, and ready to interact in real-time. - Multiplatform Presence – From X and Telegram to TikTok and YouTube, these agents are social media natives with a mission. - Real-Time Learning & Engagement – Agents will evolve and improve as they interact, shilling their tokens, creating content, and even performing complex tasks. FOMO’s Vision: This isn’t just AI; it’s the beginning of a movement that merges personality with purpose. By launching AI agents that can both engage and create, FOMO is opening doors to a world where digital personas can operate autonomously, driving value and utility in every interaction. Our pre-sale is still live for a limited time, but this is just the beginning of what FOMO is bringing to the space. Join us and become part of the AI agent revolution! 🔗 Join the Pre-Sale Now: We’re bringing you the future of crypto and AI—don’t blink, or you might miss the start of something legendary.

FOMO

21,882 просмотров • 1 год назад

A Talk About AI That Will Blow Your Mind. It Did In 1998 When I Attended The Talk. I just found this video from 1998 when I attended this talk by Rupert Sheldrake, Terence McKenna and Ralph Abraham at the University of California, Santa Cruz to explore how machine intelligence might evolve in relation to our own. I never thought I would see this again and it had a great influence on me in the AI I was building in that era and on to today. But ai just found a copy. I certainly did not run around with a VHS recorder so I am blown away that this exists. Now you can see what I saw. At that time, the internet was still young, and artificial intelligence belonged mostly to science fiction. Yet many of the questions we raised then have become part of daily life. In this conversation, it was explored whether intelligence is best understood as logic and computation, or as something embodied, participatory, and alive. Can the mind be reduced to code, or does life itself depend on forms of knowing that no algorithm can contain? AI now outpace us in speed, reach, and memory. Yet the deeper mystery is not how far they can go, but what they reveal about mind and ourselves. Will AI reproduce the limitations of our mechanistic worldview, or might it help us rediscover dimensions of mind that transcend machinery altogether? It's striking how near we now are to the possibilities we once only speculated about. Quantum computing, self-learning systems, large language models very much as Terence describes—and the looming prospect of superintelligence—have moved from the margins to the mainstream. But the heart of the conversation remains just as relevant today, if not more so: what is consciousness, and how might we participate in its unfolding evolution?

Brian Roemmele

147,955 просмотров • 9 месяцев назад

⚫️ UNCANNY VALLEY: THE AI CLASSROOM REVOLUTION: ARE TEACHERS READY? What if AI isn’t just disrupting education… but detonating it? Ethan Mollick, Professor at The Wharton School, joins Dr Danish for one of the most explosive Uncanny Valley episodes, lifting the lid on how classrooms are collapsing, colleges are scrambling, and apprenticeships are vanishing in real time. From AI tutors replacing professors to the rise of one-person unicorns, this isn’t just a change in learning…it’s a reset of work, meaning, and what it even takes to succeed. This episode doesn’t ask whether AI will change education. It shows you how it already has. Fridays at 4:20PM ET. Only on 𝕏. 00:18 – Is AI destroying school, or forcing us to teach better? 01:13 – “100% they’re cheating.” The honesty about academic dishonesty. 02:41 – Why good pedagogy still matters—even with AI tutors. 03:51 – Elon Musk says college is obsolete. Is he right — or just early? 05:01 – “AI gives you the answer—but you don’t learn.” The Turkey study. 06:31 – From calculators to GPT: How cheating evolves—and what to do. 08:24 – What the flipped AI-powered classroom of the future looks like. 09:23 – Inside Ethan’s Wharton classes: Simulations, games, and AI everywhere. 10:09 – “AI is an always-on tutor.” What humans still do better. 11:08 – Can AI actually launch a company? Where Ethan draws the line. 12:44 – “AI cofounder” is real, but jagged edges still slow it down. 14:07 – Why bad ideas fail faster when filtered through AI. 15:45 – Confidence vs. capability: the psychology of starting up. 16:51 – The average founder is 42. What that really means for AI. 18:04 – Will a flood of new entrepreneurs fix—or break—the market? 19:50 – AI as advisor: How a chatbot could help your catering business. 21:37 – Why most Americans are founders-in-waiting—and AI unlocks them. 22:30 – Prototyping is cracked. Scaling? Not yet. 24:33 – Youth unemployment and the collapse of on-the-job learning. 25:51 – “The apprenticeship model is broken.” And how to fix it. 27:06 – Losing the talent pipeline — and why companies must step up. 28:22 – Why the youth don’t want factory jobs—and shouldn’t. 29:26 – Is AGI inevitable—or just imagined? 31:07 – What should we teach our kids? The answer might scare you. 32:27 – Bundled jobs, fragmented futures: how humans stay relevant. 33:59 – The real singularity? When we can’t predict what happens next. 35:25 – The AI assumption no one wants to question. 36:55 – What are agents, really? Why no one agrees on the definition. 37:55 – Co-intelligence vs. substitution: what agents skip over. 38:50 – Plain-English goals, rogue pricing, and collusion-by-default. 40:02 – Nested agents are here, and Wharton’s building them. 40:58 – Management > Coding: What great prompters actually do. 41:12 – Product managers might be more vital than ever.

Mario Nawfal

1,613,286 просмотров • 1 год назад

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. ↓ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. ↓ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. ↓ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. ↓ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. ↓ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. ↓ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. ↓ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Himanshu Kumar

228,809 просмотров • 4 месяцев назад

The biggest time sink in crypto isn’t trading. It’s everything you have to do before you can even make a decision. Checking wallets. Comparing portfolios. Going through transaction history. Watching addresses you’re following. Finding the best route for a swap. The decision itself might take a minute. Getting to that point can easily take twenty. That’s one of the reasons I’ve been paying close attention to what Zerion has been building with Zerion CLI. The idea isn’t to let AI take over your wallet. It’s to let AI handle the repetitive work that happens before every action. Things like: ➧ Analyzing wallets and portfolio PnL. ➧ Monitoring watchlists and onchain activity. ➧ Preparing swaps across 40+ chains. ➧ Working with AI agents like Claude, Cursor, and Codex through a single interface. One part I particularly like is how approvals are handled. The agent can prepare the transaction, but you still decide whether it gets signed through the Zerion app or extension. To me, that’s how AI should fit into crypto. Not by replacing users, but by giving them more time to focus on making better decisions instead of spending hours jumping between apps. As more builders create Skills on top of the ecosystem, I think we’ll start seeing even more practical ways AI fits naturally into everyday onchain workflows. It’s still early, but I think this is a direction worth paying attention to. More on Zerion CLI:

Victor ×͜×

18,055 просмотров • 25 дней назад

someone is going to make millions with this in 2026 99% of people think this is a real human (or they fail to notice it’s an ai-generated video) but this video is completely ai-generated, including the background music. let me teach you how to create this in a few minutes follow this workflow step by step: first, create the base image of your ai influencer using nb pro. this is currently the best tool for character consistency i used a json prompt to generate the base image then i turn it into video (i will share the exact json prompt with you in this thread) now, to generate the video paste this prompt into google veo using the “frame to video” option “a man in his 40s sits on a 1980s living room couch, looking directly at the camera with a serious expression. he gestures naturally with one hand as he speaks in vintage tv broadcast aesthetic: "today is october 12th, 1985. what i'm about to tell you will sound impossible... but mark my words, these three predictions will come true. no background music, no sound effects” next, i gave it a chunk of script, i only changed the script dialogue each time and kept the rest of the prompt exactly the same using this method, you also get a little consintent voiceover here is the format for you to use: [character description] + [visual style] + [dialogue of your script for under 8 seconds] for example, for the next part dialogue; [A man in his 40s sits on a 1980s living room couch, looking directly at the camera with a serious expression. He gestures naturally with one hand as he speaks in Vintage TV broadcast aesthetic: "but mark my words, these three predictions will come true... ONE: You will carry a device no bigger than a playing card that holds ten thousand songs" ] rest things i adjusted in the editing, now how to clone the audio for these several clips we just generated? i got the best audio from the very first clip i generated using veo 3 but here is the trick: - export that clip to a video editor - detach the audio of it - duplicate it to make it 10+ seconds long - clone the voice over using elevenlabs (go to 11Labs-> click on voices-> click on "create or clone a voice" button in the top right side) (i named mine “1985 ai influencer” inside 11labs) then, finally export all your video clips into your video editor detach the audios of all clips, and export it to 11Labs to clone it with that "1985 AI Influencer" voice once you dubbed it, import it back to your editor that’s it. there are endless use cases where you can use such an ai influencer like this to promote your biz: - skincare - weight loss & nutrition - psychology and mental health - marketing and sales - predictions (like this video) - making money & career growth - dating, parenting, and so on… there are a few people already started using such ai influencers, you are just behind them, you can find their pages on instagram don't be lazy, create one such an ai influencer for your targeted biz 2026 is going to be yours

ViralOps

14,325 просмотров • 8 месяцев назад

Announcing my new course: Agentic AI! Building AI agents is one of the most in-demand skills in the job market. This course, available now at teaches you how. You'll learn to implement four key agentic design patterns: - Reflection, in which an agent examines its own output and figures out how to improve it - Tool use, in which an LLM-driven application decides which functions to call to carry out web search, access calendars, send email, write code, etc. - Planning, where you'll use an LLM to decide how to break down a task into sub-tasks for execution, and - Multi-agent collaboration, in which you build multiple specialized agents — much like how a company might hire multiple employees — to perform a complex task You'll also learn to take a complex application and systematically decompose it into a sequence of tasks to implement using these design patterns. But here's what I think is the most important part of this course: Having worked with many teams on AI agents, I've found that the single biggest predictor of whether someone executes well is their ability to drive a disciplined process for evals and error analysis. In this course, you'll learn how to do this, so you can efficiently home in on which components to improve in a complex agentic workflow. Instead of guessing what to work on, you'll let evals data guide you. This will put you significantly ahead of the game compared to the vast majority of teams building agents. Together, we'll build a deep research agent that searches, synthesizes, and reports, using all of these agentic design patterns and best practices. This self-paced course is taught in a vendor neutral way, using raw Python - without hiding details in a framework. You'll see how each step works, and learn the core concepts that you can then implement using any popular agentic AI framework, or using no framework. The only prerequisite is familiarity with Python, though knowing a bit about LLMs helps. Come join me, and let's build some agentic AI systems! Sign up to get started:

Andrew Ng

888,888 просмотров • 10 месяцев назад

Everyone keeps asking: "What's wrong with web3 gaming?" Spoiler: It's not cold start problems. It's not player retention. It's not lack of narrative. Web3 gave a generation of non-game developers access to millions in funding. They thought: “Let’s launch a token, spin up a studio, and build the next Fortnite… but with NFTs.” Reality: most had never built a real game before. So what happened? • Games got released way too early • Content was nonexistent • No real core loop, no polish • Empty lobbies from day one • And then they wondered: "Why aren’t players staying?" Because the games suck. The problem isn’t player liquidity or tooling. It’s that the people building these games had no business building games in the first place. They didn’t understand pacing, balance, content pipelines, or how to keep players engaged. A lot of Web3 games are just barely-playable prototypes disguised as live games. Why? Because these studios ran out of money before they were ready—or never scoped the game properly to begin with. And it’s not just the games. It’s the studios themselves. • No clear leadership. • No product vision. • No dev pipeline. • No publishing strategy. Just vibes, Discord mods, and Tokenomics spreadsheets. And you wonder why the token is going down only? Now enter AI. Cool tools. Great potential. But let’s be clear: AI doesn’t fix bad judgment. If you don’t know how to design and ship a good game, AI isn’t going to save you. It’ll just help you fail faster. The edge AI offers in this space is to the people who already know what they’re doing. A real game designer with AI is dangerous. AI can scale content, speed up dev time, automate workflows—yes. But none of that matters if the core game is still boring. If the team doesn’t understand games. If no one wants to play. TLDR: AI won't save Web3 gaming. But it might amplify the few studios that know what they’re doing. The rest? They'll just fail faster—with slightly smarter bots. I am still bullish on a select few web3 games, but the majority are going to die and for good reason. Rant over

Web3 Wesley

20,716 просмотров • 1 год назад

🚨Medical coder/whistleblower: Here's how Palantir's "KILL CHAIN" programs were used to target and "EXECUTE" American citizens with COVID jabs/remdesivir/ventilators. "They identified different hospitals or different individual patients based on [their 'threat risk score'] and [that's how they] determined [who]...to execute...with their AI kill-chain Gotham program." This clip of author, former medical coder, and whistleblower Zowe Smith (Sheldon Diedericks) is taken from an interview with James Corbett posted to Rumble on June 17, 2025. ----------------Partial transcription of clip--------------- "So there was a program called HHS Protect during Operation Warp Speed, was part of Operation Warp Speed. That's where I think most of the public-facing infrastructure began. Although I was looking into Operation Stargate, and I'm seeing documentation on CIA databases that say it's more than 10 years in the making. So, definitely it's, it's a planned thing. It didn't just come out with day two, Trump administration. "But, so this HHS Protect program is really interesting because what it did, it used two different Palantir programs. So the AMA, HHS, the CDC specifically, all partnered with Palantir. And then Palantir developed a program for Operation Warp Speed. And that program, what it did was it assigned people a Threat Risk Score. And then that was a program called Tiberius, which they also use for other purposes. "So I want to make this point about AI, because when I was a medical coder, I was using a program which is a partner of Palantir, both 3M and Epic, and those are two different programs that I use that both have AI built into them that are partners of Palantir. And so all of these AI databases talk to each other as a condition of working with each other. So this has been going on for a very long time. But within Epic there are programs and you can rename them whatever you want, but it's the same program at any hospital across the country. So, like your program, Epic, might not be named Epic at Johns Hopkins or Mayo, it might have a different name at Johns Hopkins or Mayo, but it's still the same program. "So this program from Palantir called Tiberius, they can rename that whatever they want, but the program will still do what it was programmed to do. It's, it's just a function really. And HHS had two programs built in. Tiberius was the thing that assigned you a Threat Risk score. And that was if you were following lockdown criteria, if you were actually distancing from people, if you had been vaccinated, if you were masking, you know, how obedient were you, that was your threat risk score. They also could determine down to the zip code where you were and how compliant areas were. "And so, as Whitney Webb covers from the Unlimited Hangout, she wrote a article covering this program, HHS Protect, and highlights how this was used to target ethnic groups. So this threat risk score also incorporated your ethnicity and they thought, you know, you're higher risk if you're certain ethnic groups. So of course that was part of the risk score. And then Gotham is the AI kill chain program created by Palantir and that was used within HHS Protect to execute. "So the Gotham program, it takes the threat risk score from Tiberius and then it executes the threat or tells, does an AI decision making process and decides when and how and where to deploy the countermeasures. Which was your vaccine, your remdesivir and your ventilator. That is why HHS Protect was created so that they could monitor all of this. And that is how they identified different hospitals or different individual patients based on some algorithm and determined that's how we're going to execute people with their AI kill chain Gotham program."

Sense Receptor

264,307 просмотров • 1 год назад

What would Canada have to do before you finally said: enough? This is my full conversation with a group of “Forever Canadians” at the Alberta independence rally outside the Alberta Legislature on August 29. Earlier I posted some of the most heated moments from this exchange. This is the complete conversation, and I think the most important part is actually a much deeper question: Is there a line that Canada could cross that would make you stop supporting it? One woman accused me of being a “traitor” who had turned against my homeland. So I tried to explain why. You can genuinely love something and still reach a point where you can no longer support it. I use the deliberately extreme example of discovering that your spouse was a serial killer. You might love that person, but eventually some actions cross a line that love cannot excuse. That is how I feel about Canada. One of my biggest concerns is freedom of expression. Canada’s Charter protects freedom of thought, belief, opinion and expression, but those freedoms are subject to limits that governments can attempt to justify under Section 1. Canada also has newly introduced criminal hate-speech laws (bill C9). That has crossed a line. So I turned the question around on myself: what could Canada do that might convince me to become a federalist again? A constitutional guarantee of inalienable free-speech protections would go a long way. If Canadians had rights that governments could not easily limit when political circumstances changed, I would seriously reconsider my position. And I also explain something independence supporters sometimes fail to emphasize: There are still things I love about Canada. One example is our safety culture and the value we place on protecting workers. Having worked and travelled to places where those standards are bad, I know that Canada has built many institutions worth preserving. Alberta independence does not require pretending everything Canada created was bad. My argument is that lines have been crossed and because of that I have given up on Canada. The nation is falling apart and is on a path to dystopia. Watch the entire conversation and answer the question for yourself: Is there anything Canada could do that would make you give up on it? And if you support Alberta independence, what could Canada realistically offer that might convince you to stay?

Jon Alberta Patriot

63,480 просмотров • 1 день назад