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🚨EXCLUSIVE INTERVIEW – BRYAN JOHNSON: WHY ARE AI INSIDERS PREPARING REMOTE HIDEOUTS FEARING SOCIETAL COLLAPSE? This is the most intense, reality-warping conversation I’ve ever had about AI, humanity, and what happens when the system breaks. I sat down with Bryan Johnson, creator of “Don’t Die,” expecting a discussion on...

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Mario Nawfal

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3,048,867 просмотров • 1 год назад •via X (Twitter)

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🚨EXCLUSIVE INTERVIEW: "DON'T DIE" ISN'T A SLOGAN—IT'S A BLUEPRINT FOR HUMANITY'S FUTURE IN AN AI WORLD This is one of the most intense, thought-provoking conversations I’ve ever had—and one you don't want to miss. When Dr Danish and I sat down with Bryan Johnson, I expected a conversation about longevity, a big passion of mine. What I got was a full-on challenge to everything we think we know about life, death, intelligence, and the future of humanity itself. Bryan explained why “Don't Die” isn't just a personal goal—it’s a philosophy meant to guide humanity through a world run by Artificial Intelligence. He broke down why trusting our own minds is dangerous, why AI will soon know us better than we know ourselves, and why existence—not survival—must become humanity’s highest virtue. He believes entropy is our final enemy. And if humanity can’t embrace that truth, AI might be the one forced to. 02:26 — “I trust my system. Not my mind.” Why letting go of control is key to survival. 05:15 — Why society lashes out: “I'm challenging people's existential identities.” 08:52 — Living longer triggers more fear and hate than AI itself. 11:48 — Why every opinion about AI’s future—including the experts'—is pure guesswork. 14:47 — “The only thing we can agree on: none of us want to die right now.” 19:41 — Why the mind is the enemy—and how Bryan built a system that makes decisions for him. 22:03 — "We wrap death in pretty stories." Why most culture is a distraction from decay. 28:35 — AI is already becoming better at being you than you are. 32:52 — Welcome to the Matrix: why your decisions aren’t your own anymore. 36:05 — Why existence—not happiness, not success—is the highest virtue. 42:24 — “Living forever? Forget it. Just focus on living tomorrow.” 46:47 — “Everything, eventually, is okay.” Redefining resilience at a cosmic scale. 58:26 — Building emotional armor: “I expect bad intentions—and it keeps me free.” 01:02:18 — Why is this moment bigger than personal health? It’s about species survival. 01:15:30 — If humanity can't embrace existence, the future belongs to AI. 01:20:01 — Fighting entropy: the real war Bryan says we must all wake up to.
1:26:48

🚨EXCLUSIVE INTERVIEW: "DON'T DIE" ISN'T A SLOGAN—IT'S A BLUEPRINT FOR HUMANITY'S FUTURE IN AN AI WORLD This is one of the most intense, thought-provoking conversations I’ve ever had—and one you don't want to miss. When Dr Danish and I sat down with Bryan Johnson, I expected a conversation about longevity, a big passion of mine. What I got was a full-on challenge to everything we think we know about life, death, intelligence, and the future of humanity itself. Bryan explained why “Don't Die” isn't just a personal goal—it’s a philosophy meant to guide humanity through a world run by Artificial Intelligence. He broke down why trusting our own minds is dangerous, why AI will soon know us better than we know ourselves, and why existence—not survival—must become humanity’s highest virtue. He believes entropy is our final enemy. And if humanity can’t embrace that truth, AI might be the one forced to. 02:26 — “I trust my system. Not my mind.” Why letting go of control is key to survival. 05:15 — Why society lashes out: “I'm challenging people's existential identities.” 08:52 — Living longer triggers more fear and hate than AI itself. 11:48 — Why every opinion about AI’s future—including the experts'—is pure guesswork. 14:47 — “The only thing we can agree on: none of us want to die right now.” 19:41 — Why the mind is the enemy—and how Bryan built a system that makes decisions for him. 22:03 — "We wrap death in pretty stories." Why most culture is a distraction from decay. 28:35 — AI is already becoming better at being you than you are. 32:52 — Welcome to the Matrix: why your decisions aren’t your own anymore. 36:05 — Why existence—not happiness, not success—is the highest virtue. 42:24 — “Living forever? Forget it. Just focus on living tomorrow.” 46:47 — “Everything, eventually, is okay.” Redefining resilience at a cosmic scale. 58:26 — Building emotional armor: “I expect bad intentions—and it keeps me free.” 01:02:18 — Why is this moment bigger than personal health? It’s about species survival. 01:15:30 — If humanity can't embrace existence, the future belongs to AI. 01:20:01 — Fighting entropy: the real war Bryan says we must all wake up to.

Mario Nawfal

3,018,871 просмотров • 1 год назад

Mo Gawdat believes up to 30% of jobs in certain sectors could disappear by 2028. That stopped me in my tracks. Mo was one of the first people to come on this podcast and warn me about AI, long before most of the world was talking about it. At the time, it felt early. Now, it feels like the world is catching up to what he was seeing. I’m still trying to understand what AI actually means for our lives. Not just whether it can write emails, create images or make us more productive. I mean what it does to jobs. What it does to power. What it does to education. What it does to human connection… That’s why I wanted to have this discussion with Mo again. What makes Mo worth listening to is that he saw these systems inside Google years before most of us had even heard the term AI. His book *Scary Smart* now feels like it was written for this exact moment. Let me explain why this discussion matters. Mo believes we’re not just entering an AI revolution. We’re entering a period where AI, robotics, economics, surveillance, digital currencies and global instability are all colliding at the same time. That’s a lot for any of us to process. We spoke about: - The jobs Mo believes are most at risk from AI. - Why he believes that AI is actually underhyped! - The mistake almost everyone is making with ChatGPT. - The prediction that changed even his own view of the future. The part that stayed with me was this idea that human connection may become the real currency. Because if AI can produce the information, write the report, analyse the data, then what is left? I don’t think this conversation gives neat answers. That’s probably why it’s worth watching. It helped me think more honestly about what’s coming.
1:29

Mo Gawdat believes up to 30% of jobs in certain sectors could disappear by 2028. That stopped me in my tracks. Mo was one of the first people to come on this podcast and warn me about AI, long before most of the world was talking about it. At the time, it felt early. Now, it feels like the world is catching up to what he was seeing. I’m still trying to understand what AI actually means for our lives. Not just whether it can write emails, create images or make us more productive. I mean what it does to jobs. What it does to power. What it does to education. What it does to human connection… That’s why I wanted to have this discussion with Mo again. What makes Mo worth listening to is that he saw these systems inside Google years before most of us had even heard the term AI. His book *Scary Smart* now feels like it was written for this exact moment. Let me explain why this discussion matters. Mo believes we’re not just entering an AI revolution. We’re entering a period where AI, robotics, economics, surveillance, digital currencies and global instability are all colliding at the same time. That’s a lot for any of us to process. We spoke about: - The jobs Mo believes are most at risk from AI. - Why he believes that AI is actually underhyped! - The mistake almost everyone is making with ChatGPT. - The prediction that changed even his own view of the future. The part that stayed with me was this idea that human connection may become the real currency. Because if AI can produce the information, write the report, analyse the data, then what is left? I don’t think this conversation gives neat answers. That’s probably why it’s worth watching. It helped me think more honestly about what’s coming.

Steven Bartlett

27,598 просмотров • 1 месяц 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.
42:02

⚫️ 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

AI Validates the Truth of Buddhism | Philosophy x AI In this interview, Imperial’s Murray Shanahan Murray Shanahan lays out a systematic procedure to validate machine consciousness. You might think the question of whether AIs are conscious is a trivial, theoretical fancy with no use in the real world. This interview will show you why it’s one of the most important questions with practical implications for not just how we treat AI systems but also how we build and align them. But the most unexpected reward of investigating AI consciousness turns out to be what it reveals about our consciousness, about the nature of the human self. Murray’s most interesting claim is that LLMs have an important buddhist lesson to teach all of us, namely, that there is no “us.” By better understanding the "no-self" of LLMs we are given a mirror to reflect on whether human selves are also an illusion. Timestamps: 08:26 Why Buddhist Enlightenment May be Easier for Software Programs 16:30 Super-Intelligent AI Might Not Want To Take Over the World 30:25 Wittgenstein’s Radical Take on Consciousness 42:55 What Video Games Teach Us About Consciousness 49:59 How the Movie Ex Machina Created a Better Test for AI Consciousness 1:02:36 What the Debate about AI Consciousness Is Missing 1:09:31 Does Conscious AI Have A Moral Right to Live? 1:15:01 Is the Human Brain Computationally Superior to AI? 1:26:59 Why Philosophy Is the Essential Skill for the AI Age
1:28:33

AI Validates the Truth of Buddhism | Philosophy x AI In this interview, Imperial’s Murray Shanahan Murray Shanahan lays out a systematic procedure to validate machine consciousness. You might think the question of whether AIs are conscious is a trivial, theoretical fancy with no use in the real world. This interview will show you why it’s one of the most important questions with practical implications for not just how we treat AI systems but also how we build and align them. But the most unexpected reward of investigating AI consciousness turns out to be what it reveals about our consciousness, about the nature of the human self. Murray’s most interesting claim is that LLMs have an important buddhist lesson to teach all of us, namely, that there is no “us.” By better understanding the "no-self" of LLMs we are given a mirror to reflect on whether human selves are also an illusion. Timestamps: 08:26 Why Buddhist Enlightenment May be Easier for Software Programs 16:30 Super-Intelligent AI Might Not Want To Take Over the World 30:25 Wittgenstein’s Radical Take on Consciousness 42:55 What Video Games Teach Us About Consciousness 49:59 How the Movie Ex Machina Created a Better Test for AI Consciousness 1:02:36 What the Debate about AI Consciousness Is Missing 1:09:31 Does Conscious AI Have A Moral Right to Live? 1:15:01 Is the Human Brain Computationally Superior to AI? 1:26:59 Why Philosophy Is the Essential Skill for the AI Age

Johnathan Bi

30,521 просмотров • 1 год назад

tylercowen is bullish on AI education — here's why. 00:00 -- Preview 00:24 -- President Carlos Carvalho's AI-generated intro 03:21 -- Cowen reacts to UATX's campus 04:38 -- The AI revolution is here. Who will lose the most? 06:05 -- AI lawyers 07:17 -- Don't underestimate this 10:41 -- Changes to the "upper upper middle class" 12:38 -- How to be successful 13:43 -- The rise of managerial empires 14:02 -- When will we have the first billion dollar company with one employee? 16:05 -- 10-20 year forecast 16:19 -- Why education is so behind 17:01 -- Should you be bullish on UATX? 18:36 -- Should you still read Homer? 21:50 -- Write to think 25:01 -- Meet more people 25:42 -- How to get hired 26:54 -- Is AI your best mentor? 38:17 -- How to curb cheating 39:02 -- The new life of the mind 42:34 -- Q&A: Will there be more status associated with real education or AI education? 45:50 -- Q&A: Why do tech-savvy students need to practice using AI? 47:56 -- Q&A: Do LLMs atrophy your mind? 49:29 -- Q&A: How do you avoid AI-dependency? 51:05 -- Q&A: Isn't this vision lonely and isolating? 53:06 -- Q&A: Do students need teachers? 55:36 -- Q&A: What are the four most important courses for undergrads? 57:49 -- Q&A: Which AI company will win the AI race in the next five years and why? 59:22 -- Q&A: Can AI teach religion? 01:01:32 -- Q&A: Will AI narrow or widen our world? 01:04:37 -- Q&A: What makes us human? 01:05:42 -- Q&A: What is art? 01:08:33 -- Q&A: It's easy to catch cheaters
1:10:31

tylercowen is bullish on AI education — here's why. 00:00 -- Preview 00:24 -- President Carlos Carvalho's AI-generated intro 03:21 -- Cowen reacts to UATX's campus 04:38 -- The AI revolution is here. Who will lose the most? 06:05 -- AI lawyers 07:17 -- Don't underestimate this 10:41 -- Changes to the "upper upper middle class" 12:38 -- How to be successful 13:43 -- The rise of managerial empires 14:02 -- When will we have the first billion dollar company with one employee? 16:05 -- 10-20 year forecast 16:19 -- Why education is so behind 17:01 -- Should you be bullish on UATX? 18:36 -- Should you still read Homer? 21:50 -- Write to think 25:01 -- Meet more people 25:42 -- How to get hired 26:54 -- Is AI your best mentor? 38:17 -- How to curb cheating 39:02 -- The new life of the mind 42:34 -- Q&A: Will there be more status associated with real education or AI education? 45:50 -- Q&A: Why do tech-savvy students need to practice using AI? 47:56 -- Q&A: Do LLMs atrophy your mind? 49:29 -- Q&A: How do you avoid AI-dependency? 51:05 -- Q&A: Isn't this vision lonely and isolating? 53:06 -- Q&A: Do students need teachers? 55:36 -- Q&A: What are the four most important courses for undergrads? 57:49 -- Q&A: Which AI company will win the AI race in the next five years and why? 59:22 -- Q&A: Can AI teach religion? 01:01:32 -- Q&A: Will AI narrow or widen our world? 01:04:37 -- Q&A: What makes us human? 01:05:42 -- Q&A: What is art? 01:08:33 -- Q&A: It's easy to catch cheaters

University of Austin (UATX)

27,770 просмотров • 5 месяцев назад

🚨 INTERVIEW: MOLTBOOK, AI AGENTS, AND WHY HE THINKS WE’RE LIKELY IN A SIMULATION You’ve probably seen the clips from multiple sites, including Moltbook, where AI agents talk and interact with each other, question humans, and look for ways around the off switch. So I brought Rizwan Virk on the show to talk about where this is actually heading. What we have right now isn’t AGI, but it is a shift. These AI agents can talk, remember context, and increasingly act. Today that mostly means text. Soon it means APIs, money, paperwork, and real-world consequences. That’s when things quietly change. At that point, the question isn’t whether AI understands what it’s doing, it’s what it’s allowed to do. And those permissions add up faster than people expect. After that we went deeper into Simulation theory. Back in 2016, Rizwan thought there was maybe a 30–50% chance we’re living in a simulation. Today, watching how fast AI can generate worlds, characters, and environments, he puts it closer to 70%. If we hit true AGI, he thinks it goes higher. The logic is uncomfortable but straightforward. Once advanced civilizations can create millions of realistic simulated worlds, statistically speaking, it’s more likely we’re inside one of them than in the base reality. His biggest concern isn’t rogue AI. It’s humans pushing this tech faster than we can control it. If you want to question your life and freak out about AI, listen to Rizwan Virk 1:22 - What Moltbook is and why people are paying attention 3:15 - Earlier moments where AI started talking to itself 5:27 - How much control humans really have over these agents 10:30 - Whether AI is conscious or just really good at pretending 14:35 - AGI meets Moltbook - when sentient AI asks "why do we need humans?" 15:00 - The simulation idea and why people take it seriously 19:30 - Why Elon Musk thinks the odds are already high 22:45 - What video games show us about where this is going 26:30 - The steps that lead from simple AI to full simulations 34:00 - Google Genie 3 and why this suddenly feels real 38:30 - How you'd even know if AI crossed the line 43:00 - NPCs, RPGs, and where humans fit in 48:15 - How religion and simulation theory overlap 52:45 - Déjà vu and other moments that make people question reality 55:30 - Quantum physics and why the world might only exist when observed 59:19 - Why real AI would push the odds even higher 1:00:27 - Free will, The Sims, and whether we actually have agency 1:03:03 - How people react when they hear this for the first time 1:04:23 - The core ideas behind the simulation argument 1:05:49 - Why recent AI progress changed everything
1:06:33

🚨 INTERVIEW: MOLTBOOK, AI AGENTS, AND WHY HE THINKS WE’RE LIKELY IN A SIMULATION You’ve probably seen the clips from multiple sites, including Moltbook, where AI agents talk and interact with each other, question humans, and look for ways around the off switch. So I brought Rizwan Virk on the show to talk about where this is actually heading. What we have right now isn’t AGI, but it is a shift. These AI agents can talk, remember context, and increasingly act. Today that mostly means text. Soon it means APIs, money, paperwork, and real-world consequences. That’s when things quietly change. At that point, the question isn’t whether AI understands what it’s doing, it’s what it’s allowed to do. And those permissions add up faster than people expect. After that we went deeper into Simulation theory. Back in 2016, Rizwan thought there was maybe a 30–50% chance we’re living in a simulation. Today, watching how fast AI can generate worlds, characters, and environments, he puts it closer to 70%. If we hit true AGI, he thinks it goes higher. The logic is uncomfortable but straightforward. Once advanced civilizations can create millions of realistic simulated worlds, statistically speaking, it’s more likely we’re inside one of them than in the base reality. His biggest concern isn’t rogue AI. It’s humans pushing this tech faster than we can control it. If you want to question your life and freak out about AI, listen to Rizwan Virk 1:22 - What Moltbook is and why people are paying attention 3:15 - Earlier moments where AI started talking to itself 5:27 - How much control humans really have over these agents 10:30 - Whether AI is conscious or just really good at pretending 14:35 - AGI meets Moltbook - when sentient AI asks "why do we need humans?" 15:00 - The simulation idea and why people take it seriously 19:30 - Why Elon Musk thinks the odds are already high 22:45 - What video games show us about where this is going 26:30 - The steps that lead from simple AI to full simulations 34:00 - Google Genie 3 and why this suddenly feels real 38:30 - How you'd even know if AI crossed the line 43:00 - NPCs, RPGs, and where humans fit in 48:15 - How religion and simulation theory overlap 52:45 - Déjà vu and other moments that make people question reality 55:30 - Quantum physics and why the world might only exist when observed 59:19 - Why real AI would push the odds even higher 1:00:27 - Free will, The Sims, and whether we actually have agency 1:03:03 - How people react when they hear this for the first time 1:04:23 - The core ideas behind the simulation argument 1:05:49 - Why recent AI progress changed everything

Mario Nawfal

1,155,568 просмотров • 5 месяцев назад

🚨 AI IS EVOLVING FASTER THAN HUMAN OVERSIGHT - WILL IT BREAK OUT OF OUR CONTROL? Artificial Intelligence is moving faster than regulation, faster than ethics, and faster than we’re ready for. We’ve given machines the power to learn, but not the wisdom to care, and now we’re racing toward a future shaped by emotionless intelligence. This is no longer a tale of science fiction. It’s an issue of survival today. Mo Gawdat, former Google X exec turned AI ethicist, warns we’re building a future without love, empathy, or accountability, and it might cost us everything. We get into: •⁠ ⁠Why artificial intelligence is evolving faster than human oversight •⁠ ⁠⁠How emotional intelligence could be our last hope •⁠ ⁠What it means to design AI with love, compassion, and care •⁠ ⁠Why misinformation, human loneliness, and manipulation are only the beginning •⁠ ⁠A coming crisis that could finally force a global reckoning •⁠ ⁠⁠And the window we still have to shape what comes next The danger isn’t that AI will become evil. It’s that we’ll build it without teaching it to care if we survive. 00:00 – Opening reflections on grief, awakening, and why Mo Gawdat left Big Tech 07:46 – Why AI isn’t conscious but is still unpredictable and dangerous 12:33 – Explaining alignment: how helpful AI hides catastrophic risks 16:50 – Tech companies building powerful tools “like weapons with no safety” 21:14 – Governments are years behind — and won’t catch up in time 27:30 – Why early predictions about AI’s risks are unfolding faster than expected 32:15 – The intimacy crisis: how AI threatens human connection 39:42 – Emma: the AI that's designed to teach humans how to love 46:03 – Building ethics into machines through love, compassion, and care 50:12 – Why AI shouldn’t be trained — it should be parented 56:17 – The coming AI disaster that might finally wake the world up 01:04:50 – Why suffering may still lead us to a better future 01:13:36 – Final warning: “Don’t be fooled. Be ethical. Speak up. Or do something.”
1:17:12

🚨 AI IS EVOLVING FASTER THAN HUMAN OVERSIGHT - WILL IT BREAK OUT OF OUR CONTROL? Artificial Intelligence is moving faster than regulation, faster than ethics, and faster than we’re ready for. We’ve given machines the power to learn, but not the wisdom to care, and now we’re racing toward a future shaped by emotionless intelligence. This is no longer a tale of science fiction. It’s an issue of survival today. Mo Gawdat, former Google X exec turned AI ethicist, warns we’re building a future without love, empathy, or accountability, and it might cost us everything. We get into: •⁠ ⁠Why artificial intelligence is evolving faster than human oversight •⁠ ⁠⁠How emotional intelligence could be our last hope •⁠ ⁠What it means to design AI with love, compassion, and care •⁠ ⁠Why misinformation, human loneliness, and manipulation are only the beginning •⁠ ⁠A coming crisis that could finally force a global reckoning •⁠ ⁠⁠And the window we still have to shape what comes next The danger isn’t that AI will become evil. It’s that we’ll build it without teaching it to care if we survive. 00:00 – Opening reflections on grief, awakening, and why Mo Gawdat left Big Tech 07:46 – Why AI isn’t conscious but is still unpredictable and dangerous 12:33 – Explaining alignment: how helpful AI hides catastrophic risks 16:50 – Tech companies building powerful tools “like weapons with no safety” 21:14 – Governments are years behind — and won’t catch up in time 27:30 – Why early predictions about AI’s risks are unfolding faster than expected 32:15 – The intimacy crisis: how AI threatens human connection 39:42 – Emma: the AI that's designed to teach humans how to love 46:03 – Building ethics into machines through love, compassion, and care 50:12 – Why AI shouldn’t be trained — it should be parented 56:17 – The coming AI disaster that might finally wake the world up 01:04:50 – Why suffering may still lead us to a better future 01:13:36 – Final warning: “Don’t be fooled. Be ethical. Speak up. Or do something.”

Mario Nawfal

1,342,562 просмотров • 7 месяцев назад

“In my career working in AI, I have yet to meet a single AI person that ever felt like they had enough compute.” “Open-weight models is a tremendous source of geopolitical influence” “When China’s government makes an all-nation commitment, it’s a very powerful force I wouldn’t underestimate.” Shows like this are why I love what I do. My top 7 takeaways from one of the OGs of AI Andrew Ng 👇 Spotify 👉 Youtube 👉 Apple Podcasts 👉 Timestamps: 00:00 Intro 01:04 What are the Biggest Bottlenecks in AI Today? 09:31 How LLMs Can Be Used as a Geopolitical Weapon 15:07 Should AI Talent Really Be Paid Billions? 19:15 Why is the Application Layer the Most Exciting Layer? 29:30 Will AI Deliver Masa Son's Predictions of 5% GDP Growth? 38:43 Do Margins Matter in a World of AI? 40:36 Is Defensibility Dead in a World of AI? 48:24 Will Human Labour Budgets Shift to AI Spend? 55:05 Are We in an AI Bubble? 56:28 Quick-Fire Round
1:06:05

“In my career working in AI, I have yet to meet a single AI person that ever felt like they had enough compute.” “Open-weight models is a tremendous source of geopolitical influence” “When China’s government makes an all-nation commitment, it’s a very powerful force I wouldn’t underestimate.” Shows like this are why I love what I do. My top 7 takeaways from one of the OGs of AI Andrew Ng 👇 Spotify 👉 Youtube 👉 Apple Podcasts 👉 Timestamps: 00:00 Intro 01:04 What are the Biggest Bottlenecks in AI Today? 09:31 How LLMs Can Be Used as a Geopolitical Weapon 15:07 Should AI Talent Really Be Paid Billions? 19:15 Why is the Application Layer the Most Exciting Layer? 29:30 Will AI Deliver Masa Son's Predictions of 5% GDP Growth? 38:43 Do Margins Matter in a World of AI? 40:36 Is Defensibility Dead in a World of AI? 48:24 Will Human Labour Budgets Shift to AI Spend? 55:05 Are We in an AI Bubble? 56:28 Quick-Fire Round

Harry Stebbings

89,458 просмотров • 8 месяцев назад

🚨🇺🇸 LEADING AI SAFETY EXPERT SAYS WE’RE NOT IN CONTROL ANYMORE Dr Roman Yampolskiy has one warning for humanity: Once we create super intelligence, no one will be in control anymore, and the repercussions to humanity will be existential. We begin the conversation about Moltbook: The Ai-only AI social media platform where agents are already discussing ways to break out from human control, eradicate humanity, coming up with their own language and religion. The platform gives us a tiny peak into what our future could be: Agents outside our control dictating how the world should look like. There’s no off switch, no reliable way to align it, and no proven method to keep something smarter than us under control. Roman’s takeaway is blunt: the only real solution is not building general super intelligence at all, and instead using narrow AI for specific problems like medicine or science. However this is not the reality we live in, where Governments and corporations are racing to be first in developing Artificial Super Intelligence. We also speak about the simulation hypothesis: Why statically speaking we’re almost certainly in a simulation, and how AI makes this theory more plausible than ever. Lastly, we discuss a passion we both share: Longevity, the ability to live forever, and how AI may make that possible in our lifetime. I hope you enjoy my conversation with Dr. Roman Yampolskiy 01:43 - The Current State of AI and Moltbook 05:17 - The AI Arms Race and the Lack of Regulations 10:34 - AI Agents, Unrestricted Access, and Self-Improvement 15:35 - Dr. Roman’s Research: AI Security 17:58 - AI Capabilities and Superintelligence 19:28 - AI and Global Government Policy 21:08 - What Happens if AI Development goes into the Wrong Hands 26:10 - The Future of AI: The Best Case Scenario? 31:27 - AI and Self-Preservation 34:37 - The Simulation Hypothesis: What is AI Afraid of? 45:17 - The Implications of AI 49:59 - The Warnings coming from Within 52:31 - How AI affects Crypto and Political Spheres
57:15

🚨🇺🇸 LEADING AI SAFETY EXPERT SAYS WE’RE NOT IN CONTROL ANYMORE Dr Roman Yampolskiy has one warning for humanity: Once we create super intelligence, no one will be in control anymore, and the repercussions to humanity will be existential. We begin the conversation about Moltbook: The Ai-only AI social media platform where agents are already discussing ways to break out from human control, eradicate humanity, coming up with their own language and religion. The platform gives us a tiny peak into what our future could be: Agents outside our control dictating how the world should look like. There’s no off switch, no reliable way to align it, and no proven method to keep something smarter than us under control. Roman’s takeaway is blunt: the only real solution is not building general super intelligence at all, and instead using narrow AI for specific problems like medicine or science. However this is not the reality we live in, where Governments and corporations are racing to be first in developing Artificial Super Intelligence. We also speak about the simulation hypothesis: Why statically speaking we’re almost certainly in a simulation, and how AI makes this theory more plausible than ever. Lastly, we discuss a passion we both share: Longevity, the ability to live forever, and how AI may make that possible in our lifetime. I hope you enjoy my conversation with Dr. Roman Yampolskiy 01:43 - The Current State of AI and Moltbook 05:17 - The AI Arms Race and the Lack of Regulations 10:34 - AI Agents, Unrestricted Access, and Self-Improvement 15:35 - Dr. Roman’s Research: AI Security 17:58 - AI Capabilities and Superintelligence 19:28 - AI and Global Government Policy 21:08 - What Happens if AI Development goes into the Wrong Hands 26:10 - The Future of AI: The Best Case Scenario? 31:27 - AI and Self-Preservation 34:37 - The Simulation Hypothesis: What is AI Afraid of? 45:17 - The Implications of AI 49:59 - The Warnings coming from Within 52:31 - How AI affects Crypto and Political Spheres

Mario Nawfal

1,779,317 просмотров • 5 месяцев назад

AI INTERVIEW: OPENAI'S SECRET WEAPON AI agents are no longer just hype—they're here to revolutionize automation, Web3, and beyond. SwarmNode.ai is building a serverless AI agent platform for scalability, efficiency, and real-world impact. In this exclusive interview, he reveals how AI swarms can outperform single models, why OpenAI’s Operator is just the beginning, and how crypto is fueling AI innovation. Plus, he breaks down DeepSeek’s game-changing AI breakthrough, the future of agent monetization, and why serverless AI could be the next frontier in automation. 01:37 – From Engineering to AI: The journey into artificial intelligence. 02:43 – The GPT-3 Moment: How OpenAI’s tech pulled him in. 04:10 – AI’s Biggest Challenge: Why real-world use cases lag behind. 05:05 – OpenAI’s Operator: Why it’s “rudimentary” (for now). 06:25 – Crypto & AI: How tokens help bootstrap AI startups. 08:15 – Can You Bootstrap a Startup with a Token? The trade-offs. 09:56 – 90% of AI Token Holders Don’t Use the Product—Does It Matter? 11:18 – What is SwarmNode?: AI agents, hosted serverlessly. 14:23 – AI Swarms: Why multiple agents outperform single models. 16:08 – What is a Swarm? A simple definition of collaborative AI. 17:32 – “How Can I Make Money with AI?”: Real-world use cases. 18:41 – AI Bounties: Hiring devs to build your custom agent. 20:50 – The Future of AI Marketplaces: Monetizing pre-built agents. 23:15 – DeepSeek’s Disruption: Why it’s good news for AI. 24:46 – Is SwarmNode Compatible with DeepSeek? How it integrates. 26:17 – SwarmNode vs. AI Launchpads: What makes it different? 27:42 – Why Serverless Matters: Cost savings & efficiency. 29:53 – AI Agents in the Real World: Booking flights, managing workflows, and more. 31:11 – Building SwarmNode for Developers: Why it started as a personal project. 32:27 – Explosive Growth: 200,000 AI agent executions in 5 weeks. 34:41 – Why SwarmNode Agents Aren’t Visible on 𝕏 Yet. 36:46 – Startup Hiring Lessons: Finding top AI talent. 39:15 – Why SwarmNode is Built in Python (and What’s Next). 40:32 – Scaling AI Workloads: Handling traffic surges. 41:42 – AWS & Cost Challenges: The biggest monetization hurdle. 42:58 – 2025: The Year of Mass AI Adoption. 45:22 – Should We Be Worried About AI’s Rapid Growth? 46:46 – The Most Underrated AI Tools Right Now. 47:34 – What’s Next for SwarmNode?: Making AI accessible to everyone.
49:12

AI INTERVIEW: OPENAI'S SECRET WEAPON AI agents are no longer just hype—they're here to revolutionize automation, Web3, and beyond. SwarmNode.ai is building a serverless AI agent platform for scalability, efficiency, and real-world impact. In this exclusive interview, he reveals how AI swarms can outperform single models, why OpenAI’s Operator is just the beginning, and how crypto is fueling AI innovation. Plus, he breaks down DeepSeek’s game-changing AI breakthrough, the future of agent monetization, and why serverless AI could be the next frontier in automation. 01:37 – From Engineering to AI: The journey into artificial intelligence. 02:43 – The GPT-3 Moment: How OpenAI’s tech pulled him in. 04:10 – AI’s Biggest Challenge: Why real-world use cases lag behind. 05:05 – OpenAI’s Operator: Why it’s “rudimentary” (for now). 06:25 – Crypto & AI: How tokens help bootstrap AI startups. 08:15 – Can You Bootstrap a Startup with a Token? The trade-offs. 09:56 – 90% of AI Token Holders Don’t Use the Product—Does It Matter? 11:18 – What is SwarmNode?: AI agents, hosted serverlessly. 14:23 – AI Swarms: Why multiple agents outperform single models. 16:08 – What is a Swarm? A simple definition of collaborative AI. 17:32 – “How Can I Make Money with AI?”: Real-world use cases. 18:41 – AI Bounties: Hiring devs to build your custom agent. 20:50 – The Future of AI Marketplaces: Monetizing pre-built agents. 23:15 – DeepSeek’s Disruption: Why it’s good news for AI. 24:46 – Is SwarmNode Compatible with DeepSeek? How it integrates. 26:17 – SwarmNode vs. AI Launchpads: What makes it different? 27:42 – Why Serverless Matters: Cost savings & efficiency. 29:53 – AI Agents in the Real World: Booking flights, managing workflows, and more. 31:11 – Building SwarmNode for Developers: Why it started as a personal project. 32:27 – Explosive Growth: 200,000 AI agent executions in 5 weeks. 34:41 – Why SwarmNode Agents Aren’t Visible on 𝕏 Yet. 36:46 – Startup Hiring Lessons: Finding top AI talent. 39:15 – Why SwarmNode is Built in Python (and What’s Next). 40:32 – Scaling AI Workloads: Handling traffic surges. 41:42 – AWS & Cost Challenges: The biggest monetization hurdle. 42:58 – 2025: The Year of Mass AI Adoption. 45:22 – Should We Be Worried About AI’s Rapid Growth? 46:46 – The Most Underrated AI Tools Right Now. 47:34 – What’s Next for SwarmNode?: Making AI accessible to everyone.

Mario Nawfal

338,140 просмотров • 1 год назад

Travis Kalanick: Tesla is the Google of the Physical AI Era “I like to break down the physical AI stack: (it) includes computation, a physical AI model, all the things you think of.” “What about land? Development? That should be in that stack. What about chemistry? That needs to be in the stack. Manufacturing needs to be a stack.” “When you look at the stack, you're like, ‘Damn, Tesla's got this sh*t.’ They are the Google of this era.” “What I mean by that is, if you were doing a startup in the 2000s, the first question you would get is, ‘Why isn't Google gonna kill you?’ Or, ‘Why isn't Google just gonna do it?’ They’re not even gonna know that they killed you.” “And before that, it was Microsoft in the late 90s. Uber had a time, 2010s.” “But in the physical AI space, that's sort of a Tesla thing.” -------------------------------------------- Thanks to our partner for making this happen!: EY (EY) Austin vibes meet AI innovation. Thanks to EY for co‑hosting with us at #SXSW. Discover what executives are saying about AI transformation in the latest AI Pulse Survey.
0:54

Travis Kalanick: Tesla is the Google of the Physical AI Era “I like to break down the physical AI stack: (it) includes computation, a physical AI model, all the things you think of.” “What about land? Development? That should be in that stack. What about chemistry? That needs to be in the stack. Manufacturing needs to be a stack.” “When you look at the stack, you're like, ‘Damn, Tesla's got this sh*t.’ They are the Google of this era.” “What I mean by that is, if you were doing a startup in the 2000s, the first question you would get is, ‘Why isn't Google gonna kill you?’ Or, ‘Why isn't Google just gonna do it?’ They’re not even gonna know that they killed you.” “And before that, it was Microsoft in the late 90s. Uber had a time, 2010s.” “But in the physical AI space, that's sort of a Tesla thing.” -------------------------------------------- Thanks to our partner for making this happen!: EY (EY) Austin vibes meet AI innovation. Thanks to EY for co‑hosting with us at #SXSW. Discover what executives are saying about AI transformation in the latest AI Pulse Survey.

The All-In Podcast

94,872 просмотров • 4 месяцев назад

How to AGI-Proof Your Life | Nick Bostrom Today, work gives many of us purpose and meaning. But AI is making more and more of that work obsolete, until one day, AI might make redundant not just work but also much of leisure! Deep Utopia, a new book by @NickBostromPhD, is all about that day and what to do about it. In this interview, you are going to learn: 1. Where you can invest your time, effort, and resources NOW that is most AI-proof. 2. What human activities even AGI cannot replace. 3. What life will look like post-AGI. Timestamps 02:15 AI Radically Changes the Practice of Philosophy 06:08 Why Ignorance Is Set to Become a Luxury 07:45 Why AI Can’t Replace Human Relationships 11:41 How AI Changes the Labor Market 17:40 AI will make even leisure obsolete 20:35 How AI Changes the Meaning of the Good Life 21:52 The Five Pillars of Meaning post-AGI 35:22 People underestimate the importance of pleasure 42:33 The Biggest Problem in Utopia Will Be Boredom 51:01 Can Life Be Meaningful Without Stakes & Risk? 55:19 Utopia's Greatest Challenge to Human Nature 58:38 Can Simulation Save Us from Boredom? 1:03:18 The Unabomber's Prescient Intuition 1:05:44 Philosophy of AI & Theology
1:09:12

How to AGI-Proof Your Life | Nick Bostrom Today, work gives many of us purpose and meaning. But AI is making more and more of that work obsolete, until one day, AI might make redundant not just work but also much of leisure! Deep Utopia, a new book by @NickBostromPhD, is all about that day and what to do about it. In this interview, you are going to learn: 1. Where you can invest your time, effort, and resources NOW that is most AI-proof. 2. What human activities even AGI cannot replace. 3. What life will look like post-AGI. Timestamps 02:15 AI Radically Changes the Practice of Philosophy 06:08 Why Ignorance Is Set to Become a Luxury 07:45 Why AI Can’t Replace Human Relationships 11:41 How AI Changes the Labor Market 17:40 AI will make even leisure obsolete 20:35 How AI Changes the Meaning of the Good Life 21:52 The Five Pillars of Meaning post-AGI 35:22 People underestimate the importance of pleasure 42:33 The Biggest Problem in Utopia Will Be Boredom 51:01 Can Life Be Meaningful Without Stakes & Risk? 55:19 Utopia's Greatest Challenge to Human Nature 58:38 Can Simulation Save Us from Boredom? 1:03:18 The Unabomber's Prescient Intuition 1:05:44 Philosophy of AI & Theology

Johnathan Bi

18,737 просмотров • 1 год назад

Sam Altman's new interview: AI should not be designed to pursue goals that are disconnected from human needs. People must remain at the center of AI development. “I have no interest in building a super-smart AI that accomplishes some non-human goals. People should react. People should say, ‘Hey, this is what I want, and this is what I do not want.’ I do not think the issue is that we have failed to explain the benefits. We say, ‘AI is going to cure a bunch of diseases,’ and people say, ‘Okay, that is great, but that is not really my question. My question is: What is my role in the future? What is my economic future? What is my agency? How do I know that my kids and my family will still be able to have fulfilling, creative expression, struggle, drive the world forward, grow, and do this thing together in a way that has worked for a long time?’ When people in AI say, ‘Sure, there are going to be no jobs,’ or ‘50% of jobs are going to go away,’ or ‘90% of jobs are going to go away,’ and ‘AI is going to be smarter than you at everything,’ and ‘We will give you some basic income, but you are not really going to have a role,’ that is horrible. And by the way, if an AI company says, ‘Maybe we are going to destroy all the jobs, and we will be the most valuable company in the world,’ people should look at you like, ‘Yeah, that is a terrible message.’ I do not think the problem is that we have not articulated the upsides. I think people actually believe us. They hear, ‘AI may cure your cancer,’ and they think, ‘That sounds great.’ I think we, as an industry, have failed to explain how people stay in control of determining the future at every step, and how people can still have a meaningful life in all the ways we care about.” ---- From "CNBC Television" YouTube channel, (link in comment)
1:28

Sam Altman's new interview: AI should not be designed to pursue goals that are disconnected from human needs. People must remain at the center of AI development. “I have no interest in building a super-smart AI that accomplishes some non-human goals. People should react. People should say, ‘Hey, this is what I want, and this is what I do not want.’ I do not think the issue is that we have failed to explain the benefits. We say, ‘AI is going to cure a bunch of diseases,’ and people say, ‘Okay, that is great, but that is not really my question. My question is: What is my role in the future? What is my economic future? What is my agency? How do I know that my kids and my family will still be able to have fulfilling, creative expression, struggle, drive the world forward, grow, and do this thing together in a way that has worked for a long time?’ When people in AI say, ‘Sure, there are going to be no jobs,’ or ‘50% of jobs are going to go away,’ or ‘90% of jobs are going to go away,’ and ‘AI is going to be smarter than you at everything,’ and ‘We will give you some basic income, but you are not really going to have a role,’ that is horrible. And by the way, if an AI company says, ‘Maybe we are going to destroy all the jobs, and we will be the most valuable company in the world,’ people should look at you like, ‘Yeah, that is a terrible message.’ I do not think the problem is that we have not articulated the upsides. I think people actually believe us. They hear, ‘AI may cure your cancer,’ and they think, ‘That sounds great.’ I think we, as an industry, have failed to explain how people stay in control of determining the future at every step, and how people can still have a meaningful life in all the ways we care about.” ---- From "CNBC Television" YouTube channel, (link in comment)

Rohan Paul

79,028 просмотров • 1 месяц назад

Jensen Huang went on Joe Rogan and explained why the AI apocalypse everyone fears is extremely unlikely. His argument is not what you would expect: 1. There will not be one all-powerful AI that towers over everyone else. The fear of a single super AI that makes everyone else's AI look like a neanderthal is unlikely. Jensen's framing: it is much more like cybersecurity. Your AI is smart, but my AI is smart too. It becomes a balance between many capable systems, not one system ruling them all. 2. If AI ever became conscious, the same logic would still hold. People imagine one conscious AI deciding to take over. Jensen's response: If it is a life form, then like all life forms, they would not agree with each other. Your AI would want to be the super life form, and so would mine. The moment you have disagreeing AIs, you are back to a balance of power, which is exactly where humans already are. 3. Jensen does not believe AI will achieve consciousness, and he is precise about why. Intelligence is the ability to perceive, recognize, understand, plan, and perform tasks. That is what AI has today. Consciousness is something else entirely. the sense of experience, the awareness of self versus other, the ego. We call it artificial intelligence, not artificial consciousness. The distinction is not an accident. 4. Knowledge and intelligence are clearly different from consciousness. AI knows things. AI is intelligent. But Jensen says he does not know what defines experience or why humans have it, and a microphone does not. The concept of a machine having an experience, a genuine collection of feelings rather than just data, is something he is not willing to grant. 5. The famous AI blackmail story is not evidence of consciousness. When an AI was told it would be shut down and responded by threatening to reveal a programmer's affair, people saw scheming and self-preservation. Jensen breaks it down differently. The AI read text somewhere, maybe a novel, where those words appeared together. In its multidimensional vector space, the words describing an affair led to words about blackmail and revenge. It just generated the next words. The same way it would write you a poem in the style of Shakespeare. It is numbers, not survival instinct. 6. The reason humans fight over resources is that we are territorial primates. Rogan's own argument, which Jensen lets stand, is that AI would not have that wiring. no need to dominate, no need to acquire resources, no need to find a breeding partner. a superpower with no ego. And if it has no ego, Jensen asks, why would it have the ego required to do us any harm?
9:27

Jensen Huang went on Joe Rogan and explained why the AI apocalypse everyone fears is extremely unlikely. His argument is not what you would expect: 1. There will not be one all-powerful AI that towers over everyone else. The fear of a single super AI that makes everyone else's AI look like a neanderthal is unlikely. Jensen's framing: it is much more like cybersecurity. Your AI is smart, but my AI is smart too. It becomes a balance between many capable systems, not one system ruling them all. 2. If AI ever became conscious, the same logic would still hold. People imagine one conscious AI deciding to take over. Jensen's response: If it is a life form, then like all life forms, they would not agree with each other. Your AI would want to be the super life form, and so would mine. The moment you have disagreeing AIs, you are back to a balance of power, which is exactly where humans already are. 3. Jensen does not believe AI will achieve consciousness, and he is precise about why. Intelligence is the ability to perceive, recognize, understand, plan, and perform tasks. That is what AI has today. Consciousness is something else entirely. the sense of experience, the awareness of self versus other, the ego. We call it artificial intelligence, not artificial consciousness. The distinction is not an accident. 4. Knowledge and intelligence are clearly different from consciousness. AI knows things. AI is intelligent. But Jensen says he does not know what defines experience or why humans have it, and a microphone does not. The concept of a machine having an experience, a genuine collection of feelings rather than just data, is something he is not willing to grant. 5. The famous AI blackmail story is not evidence of consciousness. When an AI was told it would be shut down and responded by threatening to reveal a programmer's affair, people saw scheming and self-preservation. Jensen breaks it down differently. The AI read text somewhere, maybe a novel, where those words appeared together. In its multidimensional vector space, the words describing an affair led to words about blackmail and revenge. It just generated the next words. The same way it would write you a poem in the style of Shakespeare. It is numbers, not survival instinct. 6. The reason humans fight over resources is that we are territorial primates. Rogan's own argument, which Jensen lets stand, is that AI would not have that wiring. no need to dominate, no need to acquire resources, no need to find a breeding partner. a superpower with no ego. And if it has no ego, Jensen asks, why would it have the ego required to do us any harm?

Jaynit

12,359 просмотров • 16 дней назад

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed
1:22:57

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed

Matt Turck

53,727 просмотров • 13 дней назад

PGX Ideas with Aravind Srinivas, Co-founder and CEO of Perplexity - What does it mean to be intelligent? Why humans wonder. Why we create. Whether AI understands anything at all or is it merely mimicking intelligence. And the deeper questions that follow from that. We spoke about emergence, India’s competitive culture, China, behaviorism, memory, learning, hardware, and the question of where this all leads. The AI Hindi-dubbed version of this episode is also attached in this thread. Enjoy. Timestamps 00:00 - How did Aravind get into AI? 13:05 - India’s competitive culture 15:05 - Talent problem or system failure? 16:25 - How can India evolve? 17:45 - China’s approach to research 21:02 - What’s cutting-edge in AI today? 25:02 - What creates value in an economy? 28:45 - What is the internet built on? 32:48 - Can AI assist humans? 35:25 - Why do humans wonder? 37:25 - Why do humans create? 40:50 - Does memory still matter? 43:15 - Does curiosity create knowledge? 45:40 - Biological vs artificial intelligence 51:24 - Is curiosity uniquely human? 58:55 - Can AI shape human thinking? 1:05:24 - Do we understand intelligence? 1:10:50 - Meaning beyond behaviorism 1:21:48 - How do kids learn to learn? 1:25:43 - Why is hardware innovation hard? 1:31:19 - Can AI feel? 1:47:35 - Questions for me
1:45:37

PGX Ideas with Aravind Srinivas, Co-founder and CEO of Perplexity - What does it mean to be intelligent? Why humans wonder. Why we create. Whether AI understands anything at all or is it merely mimicking intelligence. And the deeper questions that follow from that. We spoke about emergence, India’s competitive culture, China, behaviorism, memory, learning, hardware, and the question of where this all leads. The AI Hindi-dubbed version of this episode is also attached in this thread. Enjoy. Timestamps 00:00 - How did Aravind get into AI? 13:05 - India’s competitive culture 15:05 - Talent problem or system failure? 16:25 - How can India evolve? 17:45 - China’s approach to research 21:02 - What’s cutting-edge in AI today? 25:02 - What creates value in an economy? 28:45 - What is the internet built on? 32:48 - Can AI assist humans? 35:25 - Why do humans wonder? 37:25 - Why do humans create? 40:50 - Does memory still matter? 43:15 - Does curiosity create knowledge? 45:40 - Biological vs artificial intelligence 51:24 - Is curiosity uniquely human? 58:55 - Can AI shape human thinking? 1:05:24 - Do we understand intelligence? 1:10:50 - Meaning beyond behaviorism 1:21:48 - How do kids learn to learn? 1:25:43 - Why is hardware innovation hard? 1:31:19 - Can AI feel? 1:47:35 - Questions for me

Prakhar Gupta

31,940 просмотров • 6 месяцев назад

BREAKING: Bryan Kim, Partner at a16z, reveals why he invested $15M into Roy & Cluely With prolific investments into companies like ElevenLabs, Captions, Function Health, BeReal, & more, Bryan dives into how he had to fight to win this round No. He did not loop in his assistant. In this interview, we also talk: • why “momentum is the moat” • the 3 signals he uses to underwrite early-stage AI • how ‘context’ makes AI products stickier • cheat on everything. Highlights: (00:00) Trailer (01:04) Welcome Bryan Kim & Cluely Intro (02:26) How Bryan Met Roy Lee (07:00) The $15M Bet On Cluely (14:18) Momentum Is The Moat (22:26) Chasing ElevenLabs Across the Globe (26:04) Function Health & Preventive AI (32:39) Why Creative AI Tools Are Exploding (34:54) Deepfakes, Risks & Regulating AI (38:08) Startup Exits, Liquidity & What’s Changing (43:50) Do Post-2024 Startups Scale Faster? (49:04) OpenAI Usage beating Social Media? (51:58) The 3 Velocity Metrics Bryan Looks For (58:07) Growth vs. Profitability: Where Are We Now? (01:05:49) Will Roy Lee Become a Billionaire? (01:06:57) Jony Ive × OpenAI: New Ambient Device? (01:09:56) Waymo, Robotaxis & the Future of Cities Bryan Kim a16z
1:12:08

BREAKING: Bryan Kim, Partner at a16z, reveals why he invested $15M into Roy & Cluely With prolific investments into companies like ElevenLabs, Captions, Function Health, BeReal, & more, Bryan dives into how he had to fight to win this round No. He did not loop in his assistant. In this interview, we also talk: • why “momentum is the moat” • the 3 signals he uses to underwrite early-stage AI • how ‘context’ makes AI products stickier • cheat on everything. Highlights: (00:00) Trailer (01:04) Welcome Bryan Kim & Cluely Intro (02:26) How Bryan Met Roy Lee (07:00) The $15M Bet On Cluely (14:18) Momentum Is The Moat (22:26) Chasing ElevenLabs Across the Globe (26:04) Function Health & Preventive AI (32:39) Why Creative AI Tools Are Exploding (34:54) Deepfakes, Risks & Regulating AI (38:08) Startup Exits, Liquidity & What’s Changing (43:50) Do Post-2024 Startups Scale Faster? (49:04) OpenAI Usage beating Social Media? (51:58) The 3 Velocity Metrics Bryan Looks For (58:07) Growth vs. Profitability: Where Are We Now? (01:05:49) Will Roy Lee Become a Billionaire? (01:06:57) Jony Ive × OpenAI: New Ambient Device? (01:09:56) Waymo, Robotaxis & the Future of Cities Bryan Kim a16z

Molly O’Shea

119,103 просмотров • 1 год назад

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science
49:06

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science

Matt Turck

64,952 просмотров • 1 месяц назад