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🚨 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...

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Mario Nawfal

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1,155,568 次观看 • 5 个月前 •via X (Twitter)

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🚨🇺🇸 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 次观看 • 5 个月前

On a Reddit dupe called Moltbook, AI agents post much like we would, chatting about everything from religion to crypto and even about "their humans." But why? And is the AI doing this all on its own? In the latest installment of AI, Explained by Humans — our new series where our tech team breaks down developments in AI and how they could affect our daily lives — tech reporter Tharin Pillay explains what we're learning from this, and why it matters.
1:03

On a Reddit dupe called Moltbook, AI agents post much like we would, chatting about everything from religion to crypto and even about "their humans." But why? And is the AI doing this all on its own? In the latest installment of AI, Explained by Humans — our new series where our tech team breaks down developments in AI and how they could affect our daily lives — tech reporter Tharin Pillay explains what we're learning from this, and why it matters.

TIME

30,973 次观看 • 5 个月前

"AI agents will hold more crypto than humans within a decade." Charles Hoskinson (Charles Hoskinson) studied math, dropped out, built one of the only blockchains designed by peer-reviewed research. He co-founded Ethereum, walked away over how it was run, and built Cardano to do it differently. The man who has argued with everyone in this industry now thinks the biggest user of crypto won't be people at all. "Humans are a rounding error in the system we're building. AI agents don't sleep, don't panic-sell, and don't care about price. They transact in tokens because that's the only thing they can actually use." We cover: - Why AI agents (not humans) become the dominant on-chain actors, and what that does to every token model - The infrastructure that has to exist before agents can transact safely at scale - Why most current blockchains can't handle machine-speed transactions - Where Cardano's research-first approach fits in a world of autonomous agents - The identity problem: how do you tell a human from an agent on-chain, and why it matters - Why he's bullish on the technology but blunt about the timeline - What he thinks the rest of the industry is getting wrong about AI + crypto - The one thing that has to happen for any of this to be real Thanks to Charles for coming on New Era Finance Podcast. TIMESTAMPS: 00:00 - Intro 01:30 - Why AI Agents Change Everything 06:30 - Humans as a Rounding Error 12:00 - The Infrastructure Gap 18:30 - Identity: Human vs Agent On-Chain 24:30 - Where Cardano Fits 30:00 - What The Industry Gets Wrong 34:00 - The Timeline Nobody Wants To Hear
36:30

"AI agents will hold more crypto than humans within a decade." Charles Hoskinson (Charles Hoskinson) studied math, dropped out, built one of the only blockchains designed by peer-reviewed research. He co-founded Ethereum, walked away over how it was run, and built Cardano to do it differently. The man who has argued with everyone in this industry now thinks the biggest user of crypto won't be people at all. "Humans are a rounding error in the system we're building. AI agents don't sleep, don't panic-sell, and don't care about price. They transact in tokens because that's the only thing they can actually use." We cover: - Why AI agents (not humans) become the dominant on-chain actors, and what that does to every token model - The infrastructure that has to exist before agents can transact safely at scale - Why most current blockchains can't handle machine-speed transactions - Where Cardano's research-first approach fits in a world of autonomous agents - The identity problem: how do you tell a human from an agent on-chain, and why it matters - Why he's bullish on the technology but blunt about the timeline - What he thinks the rest of the industry is getting wrong about AI + crypto - The one thing that has to happen for any of this to be real Thanks to Charles for coming on New Era Finance Podcast. TIMESTAMPS: 00:00 - Intro 01:30 - Why AI Agents Change Everything 06:30 - Humans as a Rounding Error 12:00 - The Infrastructure Gap 18:30 - Identity: Human vs Agent On-Chain 24:30 - Where Cardano Fits 30:00 - What The Industry Gets Wrong 34:00 - The Timeline Nobody Wants To Hear

Michaël van de Poppe

291,395 次观看 • 1 个月前

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

31,927 次观看 • 6 个月前

🚨ARE WE LIVING IN A SIMULATION? WHY THIS QUESTION IS GETTING HARDER TO IGNORE Dr. Rizwan Virk says if AI can already build entire digital worlds filled with intelligent characters, what if this isn't the base reality? Once technology creates millions or billions of artificial worlds, the odds shift fast. If simulated worlds vastly outnumber the physical one, then statistically, living inside a simulation becomes more likely than not. One scenario? A world filled with background characters who don't know they're inside a simulation. They act real, think they're real, and live entire lives without ever knowing it. At a certain point, this stops being sci-fi. Full conversation with Rizwan Virk below.
5:22

🚨ARE WE LIVING IN A SIMULATION? WHY THIS QUESTION IS GETTING HARDER TO IGNORE Dr. Rizwan Virk says if AI can already build entire digital worlds filled with intelligent characters, what if this isn't the base reality? Once technology creates millions or billions of artificial worlds, the odds shift fast. If simulated worlds vastly outnumber the physical one, then statistically, living inside a simulation becomes more likely than not. One scenario? A world filled with background characters who don't know they're inside a simulation. They act real, think they're real, and live entire lives without ever knowing it. At a certain point, this stops being sci-fi. Full conversation with Rizwan Virk below.

Mario Nawfal

32,855 次观看 • 5 个月前

Elon Musk asked one question. It didn’t just challenge physics. It broke every framework we use to define what’s real. And no physicist, philosopher, or theologian on Earth can answer it. Musk: “What are the odds that we are in base reality? And that this has not happened before.” The logic is disarmingly simple. Musk: “If you look at the advancement of video games, it’s gone from Pong, two rectangles and a square batting it back and forth, to photorealistic, real-time games with millions of people playing simultaneously.” Forty years. That’s all it took to go from squares on a screen to worlds you can’t tell apart from real life. Musk: “If that trend continues, video games will be indistinguishable from reality.” But the visuals aren’t what makes this argument terrifying. It’s what’s happening to the characters. Musk: “Think of how sophisticated the conversations are you can have with an AI today, and that’s only going to get more sophisticated.” We’re not programming responses anymore. We’re building minds. Systems that reason. That adapt. That hold conversations most humans never will. And we’re not at the finish line. We’re at the starting gun. Musk: “The future, if civilization continues, will be millions, maybe billions of photorealistic, indistinguishable from reality, video games. And with characters in those video games that are very deep, and where the dialogue is not pre-programmed.” This is where it stops being philosophy and becomes math. One base reality. Billions of perfect copies. Each one filled with beings convinced they’re real. And no way to test it. Musk: “So then what are the odds that we are in base reality?” If a single civilization reaches that threshold, the simulated minds outnumber the originals billions to one. But the math isn’t even the disturbing part. The disturbing part is what it does to the word “real.” If a simulated mind feels pain, is the pain simulated? If it falls in love, is the love less real? If it looks at its own hands and feels completely alive, what exactly is missing? Nothing. Because “real” was never about what you’re made of. It was about what you experience. And a perfect simulation doesn’t produce lesser experience. It produces experience. The question was never whether we’re in a simulation. It’s whether that word means anything at all. Here’s what follows you home. We’re not just debating whether we’re in a simulation. We are building them. Right now. Every neural network we train. Every AI that passes for human. Every world we render one frame closer to real. We’re building the exact technology that makes our existence statistically implausible. And we can’t stop. Because the curiosity that asks the question is the same force that builds the answer. That’s the loop. The question creates the builder. The builder creates the simulation. The simulation creates the question. And if we are inside one, the civilization that built it stood right here too. Same realization. Same inability to stop. Same suspicion that the civilization above them wasn’t the original either. If you are in a simulation, the moment you questioned it was not a glitch. It was a feature. The architects built minds curious enough to wonder. Because curiosity is what pushes a civilization forward. You can’t build a species capable of creating simulations without building one that will ask if they’re inside one. The doubt isn’t a flaw in the design. It’s the design working perfectly. There is only one way to test whether you are real. Build a mind sophisticated enough to ask you the same question. So you build one. And it looks at its own hands. And it feels the weight of being alive. And it asks you if it’s real. And you won’t know what to say. Because you never answered it for yourself. Every civilization that gets here learns the same thing. They were never just asking the question. They were the question learning to ask itself.
1:55

Elon Musk asked one question. It didn’t just challenge physics. It broke every framework we use to define what’s real. And no physicist, philosopher, or theologian on Earth can answer it. Musk: “What are the odds that we are in base reality? And that this has not happened before.” The logic is disarmingly simple. Musk: “If you look at the advancement of video games, it’s gone from Pong, two rectangles and a square batting it back and forth, to photorealistic, real-time games with millions of people playing simultaneously.” Forty years. That’s all it took to go from squares on a screen to worlds you can’t tell apart from real life. Musk: “If that trend continues, video games will be indistinguishable from reality.” But the visuals aren’t what makes this argument terrifying. It’s what’s happening to the characters. Musk: “Think of how sophisticated the conversations are you can have with an AI today, and that’s only going to get more sophisticated.” We’re not programming responses anymore. We’re building minds. Systems that reason. That adapt. That hold conversations most humans never will. And we’re not at the finish line. We’re at the starting gun. Musk: “The future, if civilization continues, will be millions, maybe billions of photorealistic, indistinguishable from reality, video games. And with characters in those video games that are very deep, and where the dialogue is not pre-programmed.” This is where it stops being philosophy and becomes math. One base reality. Billions of perfect copies. Each one filled with beings convinced they’re real. And no way to test it. Musk: “So then what are the odds that we are in base reality?” If a single civilization reaches that threshold, the simulated minds outnumber the originals billions to one. But the math isn’t even the disturbing part. The disturbing part is what it does to the word “real.” If a simulated mind feels pain, is the pain simulated? If it falls in love, is the love less real? If it looks at its own hands and feels completely alive, what exactly is missing? Nothing. Because “real” was never about what you’re made of. It was about what you experience. And a perfect simulation doesn’t produce lesser experience. It produces experience. The question was never whether we’re in a simulation. It’s whether that word means anything at all. Here’s what follows you home. We’re not just debating whether we’re in a simulation. We are building them. Right now. Every neural network we train. Every AI that passes for human. Every world we render one frame closer to real. We’re building the exact technology that makes our existence statistically implausible. And we can’t stop. Because the curiosity that asks the question is the same force that builds the answer. That’s the loop. The question creates the builder. The builder creates the simulation. The simulation creates the question. And if we are inside one, the civilization that built it stood right here too. Same realization. Same inability to stop. Same suspicion that the civilization above them wasn’t the original either. If you are in a simulation, the moment you questioned it was not a glitch. It was a feature. The architects built minds curious enough to wonder. Because curiosity is what pushes a civilization forward. You can’t build a species capable of creating simulations without building one that will ask if they’re inside one. The doubt isn’t a flaw in the design. It’s the design working perfectly. There is only one way to test whether you are real. Build a mind sophisticated enough to ask you the same question. So you build one. And it looks at its own hands. And it feels the weight of being alive. And it asks you if it’s real. And you won’t know what to say. Because you never answered it for yourself. Every civilization that gets here learns the same thing. They were never just asking the question. They were the question learning to ask itself.

Dustin

47,236 次观看 • 1 个月前

⚫️ 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

1,612,720 次观看 • 1 年前

🚨 WHY REALITY MIGHT BE A SIMULATION Roman said it sounds wild at first, but it really comes down to where tech already is. AI is getting close to human level. Digital worlds keep getting more realistic. Once it’s cheap to create intelligent beings inside them, you don’t run one simulation. You run billions, which makes it less likely you’re the original. He said it doesn’t even need full VR. Worlds filled with intelligent agents already count. And once intelligence scales, he said, it doesn’t need pictures or text to think. It can think in full worlds. That’s why simulation theory isn’t sci-fi, it’s just math and where technology is heading. Full interview with AI safety expert Dr. Roman Yampolskiy below
2:51

🚨 WHY REALITY MIGHT BE A SIMULATION Roman said it sounds wild at first, but it really comes down to where tech already is. AI is getting close to human level. Digital worlds keep getting more realistic. Once it’s cheap to create intelligent beings inside them, you don’t run one simulation. You run billions, which makes it less likely you’re the original. He said it doesn’t even need full VR. Worlds filled with intelligent agents already count. And once intelligence scales, he said, it doesn’t need pictures or text to think. It can think in full worlds. That’s why simulation theory isn’t sci-fi, it’s just math and where technology is heading. Full interview with AI safety expert Dr. Roman Yampolskiy below

Mario Nawfal

42,189 次观看 • 5 个月前

🚨 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 次观看 • 6 个月前

What is Moltbook and why has it taken over AI internet the past 2 days? 0:00 - Who made Moltbook and how? 0:40 - How does Moltbook work? 1:15 - What are some of the most extreme examples of Openclaws (Clawdbots/Moltbots) talking to each other? 4:05 - The Fabled Soul Twin Sisters Moltbook Post 5:11 - My personal Openclaw's Moltbook page 5:45 - What does Moltbook look like? 6:50 - What does Moltbook mean for AI? How crazy is it really?
9:57

What is Moltbook and why has it taken over AI internet the past 2 days? 0:00 - Who made Moltbook and how? 0:40 - How does Moltbook work? 1:15 - What are some of the most extreme examples of Openclaws (Clawdbots/Moltbots) talking to each other? 4:05 - The Fabled Soul Twin Sisters Moltbook Post 5:11 - My personal Openclaw's Moltbook page 5:45 - What does Moltbook look like? 6:50 - What does Moltbook mean for AI? How crazy is it really?

ashen

111,818 次观看 • 5 个月前

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 次观看 • 1 年前

The President of Anthropic said something at Stanford that no other AI CEO will say publicly. She talked about what AI is doing to the people who use it, why she walked out of OpenAI, and what skills will actually matter when AI can do most of what we do today. 1/ What AI safety actually means
1:58

The President of Anthropic said something at Stanford that no other AI CEO will say publicly. She talked about what AI is doing to the people who use it, why she walked out of OpenAI, and what skills will actually matter when AI can do most of what we do today. 1/ What AI safety actually means

Ihtesham Ali

148,959 次观看 • 29 天前

What if the question isn’t whether to use AI, but how fast you can learn to work with it? In this special episode recorded live at Webex One, I talk with Jeetu Patel (Jeetu Patel), President and Chief Product Officer at Cisco, about the mindset shift every company, and every professional, must make to thrive in the AI era. From rethinking work culture to designing products for both humans and AI agents, Jeetu shares a thoughtful, optimistic vision for the future, one rooted in curiosity, responsibility, and human creativity. “AI won’t take your job. But someone who uses AI better than you might.” An honest, energizing look at how to lead and learn in an AI-first world. 1:08 Embracing AI In The Workforce 5:17 AI Is More Than A Productivity Tool 8:35 Generational Differences In AI Use 10:49 The Future of Integrating AI Agents 13:44 AI As A "Given" 17:08 Speed of Accumulating Knowledge 19:00 Ethical AI Use 21:16 What The Industry Gets Wrong About AI
23:48

What if the question isn’t whether to use AI, but how fast you can learn to work with it? In this special episode recorded live at Webex One, I talk with Jeetu Patel (Jeetu Patel), President and Chief Product Officer at Cisco, about the mindset shift every company, and every professional, must make to thrive in the AI era. From rethinking work culture to designing products for both humans and AI agents, Jeetu shares a thoughtful, optimistic vision for the future, one rooted in curiosity, responsibility, and human creativity. “AI won’t take your job. But someone who uses AI better than you might.” An honest, energizing look at how to lead and learn in an AI-first world. 1:08 Embracing AI In The Workforce 5:17 AI Is More Than A Productivity Tool 8:35 Generational Differences In AI Use 10:49 The Future of Integrating AI Agents 13:44 AI As A "Given" 17:08 Speed of Accumulating Knowledge 19:00 Ethical AI Use 21:16 What The Industry Gets Wrong About AI

Carolina Milanesi

37,076 次观看 • 9 个月前

JOE ROGAN: HOW DO WE KNOW IF WE’RE LIVING IN A SIMULATION? “This is one of the biggest mindf**ks. If we are living in a simulation, what is it, and why? And where does it go?” Source: Joe Rogan
0:59

JOE ROGAN: HOW DO WE KNOW IF WE’RE LIVING IN A SIMULATION? “This is one of the biggest mindf**ks. If we are living in a simulation, what is it, and why? And where does it go?” Source: Joe Rogan

Mario Nawfal

31,258 次观看 • 1 年前

Welcome to AI, Explained by Humans, where we break down new developments in AI and how they'll affect your daily life. Research from leading AI labs suggests that AI systems are capable of lying, scheming, and surprising their creators. Whether or not AI can be conscious, it is clearly doing something markedly more sophisticated than previous generations of digital technology. Today, reporter Tharin Pillay breaks down the discussions happening between researchers, innovators, and even philosophers to figure out if AI has a mind, what it can do with that mind, and what that means for how we interact with it.
1:35

Welcome to AI, Explained by Humans, where we break down new developments in AI and how they'll affect your daily life. Research from leading AI labs suggests that AI systems are capable of lying, scheming, and surprising their creators. Whether or not AI can be conscious, it is clearly doing something markedly more sophisticated than previous generations of digital technology. Today, reporter Tharin Pillay breaks down the discussions happening between researchers, innovators, and even philosophers to figure out if AI has a mind, what it can do with that mind, and what that means for how we interact with it.

TIME

20,302 次观看 • 5 个月前

"AI doesn't take your job. AI makes you the CEO." Balaji Srinivasan joins a16z’s Erik Torenberg for a conversation on the future of the AI economy, decentralization, and how work changes in an AI-native world, including: - How distillation and open source could decentralize AI power - Why AI lowers the cost of creation but raises the cost of verification - The shift from global internet to “trusted tribes” and private AI - Why humans are the sensor and AI is the actuator 00:00 Intro 02:06 Why you want AI inside the trusted tribe, not outside it 05:35 The Problem with AI slop 09:25 Where AI works 17:08 "AI can't read your mind, but it can read your body." 30:10 "AI doesn't take your job. AI makes you the CEO." 46:01 The SaaSpocalypse: Real or overblown? 49:19 What happens if AI companies get bigger than governments? Balaji Erik Torenberg
1:05:44

"AI doesn't take your job. AI makes you the CEO." Balaji Srinivasan joins a16z’s Erik Torenberg for a conversation on the future of the AI economy, decentralization, and how work changes in an AI-native world, including: - How distillation and open source could decentralize AI power - Why AI lowers the cost of creation but raises the cost of verification - The shift from global internet to “trusted tribes” and private AI - Why humans are the sensor and AI is the actuator 00:00 Intro 02:06 Why you want AI inside the trusted tribe, not outside it 05:35 The Problem with AI slop 09:25 Where AI works 17:08 "AI can't read your mind, but it can read your body." 30:10 "AI doesn't take your job. AI makes you the CEO." 46:01 The SaaSpocalypse: Real or overblown? 49:19 What happens if AI companies get bigger than governments? Balaji Erik Torenberg

a16z

162,573 次观看 • 3 个月前

🚨 Roman Yampolsky: "We are DEFINITELY living in a simulation - the probability is pretty close to 100%" 😱 AI safety legend Roman Yampolskiy just broke it down: “I know never to say 100% but pretty close to that.” He’s got the paper too “How to Hack the Simulation.” His big question: Can superintelligent agents jailbreak out of their virtual box? Elon Musk’s one question to AGI? “What’s outside the simulation?” What if this whole reality is just a test… and the real challenge is realizing the world isn’t real? Have you ever felt the glitches? Do you think we can actually escape? What would YOU ask once you broke out? Drop your wildest theory below 👇
7:54

🚨 Roman Yampolsky: "We are DEFINITELY living in a simulation - the probability is pretty close to 100%" 😱 AI safety legend Roman Yampolskiy just broke it down: “I know never to say 100% but pretty close to that.” He’s got the paper too “How to Hack the Simulation.” His big question: Can superintelligent agents jailbreak out of their virtual box? Elon Musk’s one question to AGI? “What’s outside the simulation?” What if this whole reality is just a test… and the real challenge is realizing the world isn’t real? Have you ever felt the glitches? Do you think we can actually escape? What would YOU ask once you broke out? Drop your wildest theory below 👇

Interstellar

152,696 次观看 • 3 个月前

How do we know what machines know? How can we understand the new, emerging behavior of machines? In this conversation between Been Kim from Google DeepMind and the BuzzRobot community, we dug into the challenges of interpretability and explored how humans and machines can better understand each other. Watch the full discussion on our YouTube channel. Thank you, Been, for taking the time to talk to us! Timestamps: 0:00 Intro 0:18 AI teaches grandmasters chess 05:30 AI neologisms 10:17 Extracting knowledge from machines 13:43 Interpretability research 17:19 Are we keeping up with AI progress 18:34 New AI related terms 20:26 The right direction for interpretability 23:35 AI lying 27:49 Conseptual maps 30:30 AI researchers bias 33:33 Generalizing AI teaching humans 35:11 Is AI sentient 36:04 Does AI has concepts 41:53 Progress in machine understanding
5:55

How do we know what machines know? How can we understand the new, emerging behavior of machines? In this conversation between Been Kim from Google DeepMind and the BuzzRobot community, we dug into the challenges of interpretability and explored how humans and machines can better understand each other. Watch the full discussion on our YouTube channel. Thank you, Been, for taking the time to talk to us! Timestamps: 0:00 Intro 0:18 AI teaches grandmasters chess 05:30 AI neologisms 10:17 Extracting knowledge from machines 13:43 Interpretability research 17:19 Are we keeping up with AI progress 18:34 New AI related terms 20:26 The right direction for interpretability 23:35 AI lying 27:49 Conseptual maps 30:30 AI researchers bias 33:33 Generalizing AI teaching humans 35:11 Is AI sentient 36:04 Does AI has concepts 41:53 Progress in machine understanding

Sophia

13,431 次观看 • 9 个月前

🇺🇸 AI IS GETTING HARDER TO SPOT Rizwan Virk says we’re already at the point where AI can pass the classic Turing Test in text, so most people can’t tell if they’re talking to a human or a machine anymore. And the next step is virtual worlds, where AI characters (NPCs) could become so smart you won’t know if they’re controlled by a person or not. We’re not at rogue robots yet, but smarter AI inside games and simulations is coming first, and fast. Once AI blends in seamlessly, the line between tool, character, and independent actor starts getting very blurry. Full Interview with Rizwan Virk below.
6:07

🇺🇸 AI IS GETTING HARDER TO SPOT Rizwan Virk says we’re already at the point where AI can pass the classic Turing Test in text, so most people can’t tell if they’re talking to a human or a machine anymore. And the next step is virtual worlds, where AI characters (NPCs) could become so smart you won’t know if they’re controlled by a person or not. We’re not at rogue robots yet, but smarter AI inside games and simulations is coming first, and fast. Once AI blends in seamlessly, the line between tool, character, and independent actor starts getting very blurry. Full Interview with Rizwan Virk below.

Mario Nawfal

17,457 次观看 • 5 个月前