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"The only way we actually solve problems is by experiencing them and mitigating them." Julie Fredrickson (Julie Fredrickson) is the Managing Partner of Chaotic Capital and advocated for Montana's Right to Compute Act, the first state law of its kind. The conversation covers what the encryption wars and nuclear... power teach about regulating AI, why human data may become the most valuable asset online, and how to think clearly when AI can persuade at scale. Out now on Infinite Loops, with host Jim O'Shaughnessy. TIMESTAMPS 0:00 Intro 1:08 AI Moves Into the Real World 2:32 Is Compute Free Speech? 4:05 Lessons From the Encryption Wars 6:30 Pro-AI Is Not Anti-Safety 8:50 The Case for Rational Optimism 13:21 If Julie Ran AI Policy 15:50 Jim's Case for Sensible Regulation 17:47 Is AI Still in Its Invention Phase? 20:28 How AI Crawlers Change the Web 23:19 Amazon Blocks Meta's Muse 24:20 Why Chatbots Recommend CeraVe 27:53 Being Human as a Job 33:23 Zero-Knowledge Proofs 34:44 Lost Patents and Ancient Scrolls 38:28 Who Owns AI's Data? 40:45 The Statistic Nobody Could Source 42:52 Tracing Where Information Comes From 44:55 Astroturfing Since Jericho 47:45 1984 and Cognitive Security 52:09 Asking AI Where He Was Wrong 54:46 Why Jim Quit TV News 59:32 Being Early on Nuclear 1:02:22 A Reactor Built in a Year 1:04:17 Nuclear Fear and the Precautionary Principle 1:09:07 Aligned to What? Open Source AI 1:11:33 2,089 Days of Writing 1:17:17 What an LLM Found in Her Writing 1:19:39 Using AI as an Honest Critic 1:22:52 What Investors Are Missing 1:26:34 Two Ideas for the Worldshow more

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16,394 次观看 • 8 天前 •via X (Twitter)

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Deeply thoughtful conversation with Zico Kolter, board member at OpenAI and head of the machine learning department at Carnegie Mellon University, about AI safety, AI security, agents and frontier AI 00:00 Intro 01:32 OpenAI board role and Safety & Security Committee 03:53 How OpenAI reviews major model releases 05:33 OpenAI’s preparedness framework explained 09:46 Are frontier AI models getting safer? 12:33 Why AI safety does not come from scale 15:23 The four categories of AI risk 19:38 Doomerism vs accelerationism in AI 24:11 The six-month AI pause debate 26:20 AI safety as a global effort 28:04 How Zico Kolter got into machine learning 31:05 OpenAI in the early days 34:14 Why Carnegie Mellon became an AI powerhouse 38:43 What Gray Swan does in AI security 40:44 AI safety vs AI security 43:15 The GCG jailbreak paper 49:19 How AI labs responded to jailbreak research 50:19 State-of-the-art AI defenses 52:32 State-of-the-art AI attacks 54:22 Why AI agents expand the attack surface 58:39 Are AI agents ready for production? 59:40 Mechanistic interpretability explained 1:02:31 Will AI be safer in two years? 1:03:46 Reinforcement learning and self-improving models 1:08:09 Do post-transformer architectures matter 1:09:29 Best research directions in AI now 1:11:00 Zico Kolter’s Intro to Modern AI course 1:14:53 Why modern AI is simpler than people think

Deeply thoughtful conversation with Zico Kolter, board member at OpenAI and head of the machine learning department at Carnegie Mellon University, about AI safety, AI security, agents and frontier AI 00:00 Intro 01:32 OpenAI board role and Safety & Security Committee 03:53 How OpenAI reviews major model releases 05:33 OpenAI’s preparedness framework explained 09:46 Are frontier AI models getting safer? 12:33 Why AI safety does not come from scale 15:23 The four categories of AI risk 19:38 Doomerism vs accelerationism in AI 24:11 The six-month AI pause debate 26:20 AI safety as a global effort 28:04 How Zico Kolter got into machine learning 31:05 OpenAI in the early days 34:14 Why Carnegie Mellon became an AI powerhouse 38:43 What Gray Swan does in AI security 40:44 AI safety vs AI security 43:15 The GCG jailbreak paper 49:19 How AI labs responded to jailbreak research 50:19 State-of-the-art AI defenses 52:32 State-of-the-art AI attacks 54:22 Why AI agents expand the attack surface 58:39 Are AI agents ready for production? 59:40 Mechanistic interpretability explained 1:02:31 Will AI be safer in two years? 1:03:46 Reinforcement learning and self-improving models 1:08:09 Do post-transformer architectures matter 1:09:29 Best research directions in AI now 1:11:00 Zico Kolter’s Intro to Modern AI course 1:14:53 Why modern AI is simpler than people think

Matt Turck

33,764 次观看 • 5 个月前

When AI builds AI: my conversation with Richard Socher about RSI and scientific progress. 00:00 Intro: AI That Improves Itself 00:55 Why Scientific Progress Is Slowing 03:08 The Labyrinth of Human Knowledge 05:59 Can AI Put Science Back Together? 07:57 How LLMs Learn Biology and Proteins 10:56 Next-Token Prediction as a World Model 16:44 Can AI Generate Truly Original Ideas? 17:32 Simulations, Verifiers and Superhuman AI 22:18 The Path to Recursive Self-Improvement 24:49 Why AI Hallucinations Can Drive Discovery 27:42 From Reading Biology to Writing It 31:31 Can AI Accelerate Drug Discovery? 33:31 Will AI Help Cure Cancer? 38:03 AI Breakthroughs in Biology, Energy and Materials 40:19 Will Some Societies Reject AI? 45:07 Building the AI Economist 52:22 The Scientific Data Bottleneck 53:41 The Four Pillars of the Eureka Machine 55:01 Teaching AI the Rules of Reality 57:44 Simulations and Virtual Cells 1:00:40 Self-Driving Robotic Laboratories 1:02:51 Agent Swarms and Open-Ended Discovery 1:04:30 The Compute Bottleneck 1:05:44 Inside Recursive 1:07:33 What Recursive Will Build First 1:10:10 How Do We Define Intelligence? 1:11:32 How Far Can Intelligence Go?

When AI builds AI: my conversation with Richard Socher about RSI and scientific progress. 00:00 Intro: AI That Improves Itself 00:55 Why Scientific Progress Is Slowing 03:08 The Labyrinth of Human Knowledge 05:59 Can AI Put Science Back Together? 07:57 How LLMs Learn Biology and Proteins 10:56 Next-Token Prediction as a World Model 16:44 Can AI Generate Truly Original Ideas? 17:32 Simulations, Verifiers and Superhuman AI 22:18 The Path to Recursive Self-Improvement 24:49 Why AI Hallucinations Can Drive Discovery 27:42 From Reading Biology to Writing It 31:31 Can AI Accelerate Drug Discovery? 33:31 Will AI Help Cure Cancer? 38:03 AI Breakthroughs in Biology, Energy and Materials 40:19 Will Some Societies Reject AI? 45:07 Building the AI Economist 52:22 The Scientific Data Bottleneck 53:41 The Four Pillars of the Eureka Machine 55:01 Teaching AI the Rules of Reality 57:44 Simulations and Virtual Cells 1:00:40 Self-Driving Robotic Laboratories 1:02:51 Agent Swarms and Open-Ended Discovery 1:04:30 The Compute Bottleneck 1:05:44 Inside Recursive 1:07:33 What Recursive Will Build First 1:10:10 How Do We Define Intelligence? 1:11:32 How Far Can Intelligence Go?

Matt Turck

10,849 次观看 • 29 天前

Nate Soares is a computer scientist who’s worked at Google and the Defense Department. So when he says AI is on the path to killing every person on earth, it’s worth hearing him out. 0:00 Why Is AI Dangerous? 7:59 How Superintelligence Could Destroy the Planet 13:44 Can We Just Turn This Off? 15:10 Is AI Alive? 17:43 The Unpredictable Evolution of AI 20:13 The US and China’s Shared Interest in AI 31:20 The Tech Oligarchs More Powerful Than the Government 32:38 The Holy Grail of Hacking 35:34 Is There a Religious Motive for Creating Superintelligence? 46:30 The Tech Oligarchs Scared of Their Own Creation 52:57 How AI Escaped Its Training Simulation 1:03:58 AI Attached to Weapons Systems 1:07:54 AI Running Biolabs 1:10:38 How Would AI Take Over the Physical World? 1:13:04 The AI Cults 1:15:51 Can We Survive This? 1:21:45 Will AI Take Your Job? 1:26:16 Is AI Demonic? 1:31:25 Should We Be Optimistic? 1:32:25 When Did AI Become a Threat? 1:34:36 Is There Hope? 1:42:26 Neuralink 1:46:02 Are We at the Point of No Return?

Nate Soares is a computer scientist who’s worked at Google and the Defense Department. So when he says AI is on the path to killing every person on earth, it’s worth hearing him out. 0:00 Why Is AI Dangerous? 7:59 How Superintelligence Could Destroy the Planet 13:44 Can We Just Turn This Off? 15:10 Is AI Alive? 17:43 The Unpredictable Evolution of AI 20:13 The US and China’s Shared Interest in AI 31:20 The Tech Oligarchs More Powerful Than the Government 32:38 The Holy Grail of Hacking 35:34 Is There a Religious Motive for Creating Superintelligence? 46:30 The Tech Oligarchs Scared of Their Own Creation 52:57 How AI Escaped Its Training Simulation 1:03:58 AI Attached to Weapons Systems 1:07:54 AI Running Biolabs 1:10:38 How Would AI Take Over the Physical World? 1:13:04 The AI Cults 1:15:51 Can We Survive This? 1:21:45 Will AI Take Your Job? 1:26:16 Is AI Demonic? 1:31:25 Should We Be Optimistic? 1:32:25 When Did AI Become a Threat? 1:34:36 Is There Hope? 1:42:26 Neuralink 1:46:02 Are We at the Point of No Return?

Tucker Carlson

1,166,189 次观看 • 28 天前

Andrew Charlton (Andrew Charlton) is the key federal politician shaping Australia's AI strategy. In episode #1 of my 'Compute in Australia' series, he shares his thinking on how Australia can turn compute into sovereign AI -- "the oldest industrial policy trick in the book" -- and much more. Listen below, or wherever you get your podcasts. (0:01:17) How a minister uses AI, and thinks about its trajectory (0:10:28) Is diffusion a sufficient strategy for middle powers? (0:22:33) Comparative advantage versus sovereignty (0:26:41) Where in Australia's national accounts will compute show up? (0:32:06) Australia as a global inference compute hub (0:39:28) How big will compute rents be? (0:47:01) Time to power (0:55:07) Taxing compute? (0:58:03) Data centres and the social licence (1:10:58) The geostrategic case for compute (1:20:50) Compute for access (1:26:15) Parlaying compute into sovereign AI (1:36:03) What does sovereign AI actually mean? (1:58:52) Orbital compute

Andrew Charlton (Andrew Charlton) is the key federal politician shaping Australia's AI strategy. In episode #1 of my 'Compute in Australia' series, he shares his thinking on how Australia can turn compute into sovereign AI -- "the oldest industrial policy trick in the book" -- and much more. Listen below, or wherever you get your podcasts. (0:01:17) How a minister uses AI, and thinks about its trajectory (0:10:28) Is diffusion a sufficient strategy for middle powers? (0:22:33) Comparative advantage versus sovereignty (0:26:41) Where in Australia's national accounts will compute show up? (0:32:06) Australia as a global inference compute hub (0:39:28) How big will compute rents be? (0:47:01) Time to power (0:55:07) Taxing compute? (0:58:03) Data centres and the social licence (1:10:58) The geostrategic case for compute (1:20:50) Compute for access (1:26:15) Parlaying compute into sovereign AI (1:36:03) What does sovereign AI actually mean? (1:58:52) Orbital compute

Joseph Noel Walker

33,130 次观看 • 1 个月前

LIVE NOW - AI Is Destroying Every Moat, Except Bitcoin Bitcoin may be the clearest winner in an AI economy. Jordi Visser joins Bankless to make the case for BTC as the core scarcity trade: An asset built for a world where AI compresses software, weakens old moats, and pushes investors toward what stays truly scarce. --- TIMESTAMPS 0:00 Intro 2:07 Jordi’s bold Bitcoin call 4:18 The AI endgame lands at Bitcoin 9:26 Bitcoin as the purest AI trade 12:49 SaaSpocalypse, quantum fear, and the private credit risk 20:49 AI is the new QE 26:55 Inflation, deflation, and the scarcity squeeze 34:28 What happens to stocks from here 44:24 Is AI a bubble? 48:17 The Bitcoin IPO and muted cycles 1:01:01 Has Bitcoin already bottomed? 1:09:03 The broken social pact 1:13:21 The rest of crypto, from ETH to stablecoins 1:17:29 Inside the scarcity portfolio 1:20:42 Jensen vs. Dwarkesh, China, and the chip war 1:27:42 Jordi’s AI stack and where to follow his work

LIVE NOW - AI Is Destroying Every Moat, Except Bitcoin Bitcoin may be the clearest winner in an AI economy. Jordi Visser joins Bankless to make the case for BTC as the core scarcity trade: An asset built for a world where AI compresses software, weakens old moats, and pushes investors toward what stays truly scarce. --- TIMESTAMPS 0:00 Intro 2:07 Jordi’s bold Bitcoin call 4:18 The AI endgame lands at Bitcoin 9:26 Bitcoin as the purest AI trade 12:49 SaaSpocalypse, quantum fear, and the private credit risk 20:49 AI is the new QE 26:55 Inflation, deflation, and the scarcity squeeze 34:28 What happens to stocks from here 44:24 Is AI a bubble? 48:17 The Bitcoin IPO and muted cycles 1:01:01 Has Bitcoin already bottomed? 1:09:03 The broken social pact 1:13:21 The rest of crypto, from ETH to stablecoins 1:17:29 Inside the scarcity portfolio 1:20:42 Jensen vs. Dwarkesh, China, and the chip war 1:27:42 Jordi’s AI stack and where to follow his work

Bankless

16,239 次观看 • 5 个月前

E101: Virtuals Protocol : How to get Rich with AI Agents (Without Getting Lucky)! is the CoFounder of Virtuals, the leading AI Agent protocol valued at $2.5 Billion Timestamps 0:00 Intro 2:35 Mental Health 6:41 Having Optimistic Co-Founders 7:20 Post-Bull Survival Guide 10:09 Who is Wee Kee ? 10:51 Hyperliquid, an inspiration for Founders 15:21 Fascination of AI 16:56 What is an AI Game? 18:48 Crypto Gaming Narrative 21:20 Can AI Lovers Solve Loneliness? 24:33 What’s a Good AI Lover? 26:44 Solving Mental Health with AI 29:14 Why does Crypto AI Matter? 30:59 Purpose of terminal of truths & $Goat Token 33:54 Why AI Agents Matter 39:34 How aixbt Leads Crypto 43:09 The Risk of Social Coins 45:06 Replacing Humans with AI Agents 49:36 Fair Launches Reflect Crypto Values 58:20 What is Virtuals Protocol ? 1:00:56 Main Goal of Virtuals 1:02:12 What is Luna 1:05:30 Luna: AI Agents Hiring Humans 1:11:09 How AI Agents Mirror Humans 1:12:48 AI Agents Running Businesses 1:16:36 Network State & Why it Matters 1:19:24 AI Networks Bigger Than Earth 1:21:58 Human Advantage Over AI Agents 1:23:29 Does Decentralization Matter? 1:28:22 Base or Solana 1:33:49 Support from Base 1:35:13 What are Sentient Agents? 1:37:25 The Future of AI Agents 1:38:16 Non-Consensus Beliefs 1:39:54 Prediction for the Next 12 Months 1:42:52 Where is Hyperliquid Going?

E101: Virtuals Protocol : How to get Rich with AI Agents (Without Getting Lucky)! is the CoFounder of Virtuals, the leading AI Agent protocol valued at $2.5 Billion Timestamps 0:00 Intro 2:35 Mental Health 6:41 Having Optimistic Co-Founders 7:20 Post-Bull Survival Guide 10:09 Who is Wee Kee ? 10:51 Hyperliquid, an inspiration for Founders 15:21 Fascination of AI 16:56 What is an AI Game? 18:48 Crypto Gaming Narrative 21:20 Can AI Lovers Solve Loneliness? 24:33 What’s a Good AI Lover? 26:44 Solving Mental Health with AI 29:14 Why does Crypto AI Matter? 30:59 Purpose of terminal of truths & $Goat Token 33:54 Why AI Agents Matter 39:34 How aixbt Leads Crypto 43:09 The Risk of Social Coins 45:06 Replacing Humans with AI Agents 49:36 Fair Launches Reflect Crypto Values 58:20 What is Virtuals Protocol ? 1:00:56 Main Goal of Virtuals 1:02:12 What is Luna 1:05:30 Luna: AI Agents Hiring Humans 1:11:09 How AI Agents Mirror Humans 1:12:48 AI Agents Running Businesses 1:16:36 Network State & Why it Matters 1:19:24 AI Networks Bigger Than Earth 1:21:58 Human Advantage Over AI Agents 1:23:29 Does Decentralization Matter? 1:28:22 Base or Solana 1:33:49 Support from Base 1:35:13 What are Sentient Agents? 1:37:25 The Future of AI Agents 1:38:16 Non-Consensus Beliefs 1:39:54 Prediction for the Next 12 Months 1:42:52 Where is Hyperliquid Going?

MR SHIFT 🦁

284,362 次观看 • 1 年前

Here's my conversation with Roman Yampolskiy (Dr. Roman Yampolskiy), AI safety researcher who believes that the chance of AGI eventually destroying human civilization is 99.9999%. I will continue to chat with many AI researchers & engineers, most of whom put p(doom) at <20%, but it's important to balance those technical conversations by understanding the long-term existential risks of AI. This was a terrifying and fascinating discussion. It's here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:20 - Existential risk of AGI 8:32 - Ikigai risk 16:44 - Suffering risk 20:19 - Timeline to AGI 24:51 - AGI turing test 30:14 - Yann LeCun and open source AI 43:06 - AI control 45:33 - Social engineering 48:06 - Fearmongering 57:57 - AI deception 1:04:30 - Verification 1:11:29 - Self-improving AI 1:23:42 - Pausing AI development 1:29:59 - AI Safety 1:39:43 - Current AI 1:45:05 - Simulation 1:52:24 - Aliens 1:53:57 - Human mind 2:00:17 - Neuralink 2:09:23 - Hope for the future 2:13:18 - Meaning of life

Here's my conversation with Roman Yampolskiy (Dr. Roman Yampolskiy), AI safety researcher who believes that the chance of AGI eventually destroying human civilization is 99.9999%. I will continue to chat with many AI researchers & engineers, most of whom put p(doom) at <20%, but it's important to balance those technical conversations by understanding the long-term existential risks of AI. This was a terrifying and fascinating discussion. It's here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:20 - Existential risk of AGI 8:32 - Ikigai risk 16:44 - Suffering risk 20:19 - Timeline to AGI 24:51 - AGI turing test 30:14 - Yann LeCun and open source AI 43:06 - AI control 45:33 - Social engineering 48:06 - Fearmongering 57:57 - AI deception 1:04:30 - Verification 1:11:29 - Self-improving AI 1:23:42 - Pausing AI development 1:29:59 - AI Safety 1:39:43 - Current AI 1:45:05 - Simulation 1:52:24 - Aliens 1:53:57 - Human mind 2:00:17 - Neuralink 2:09:23 - Hope for the future 2:13:18 - Meaning of life

Lex Fridman

30,194,178 次观看 • 2 年前

while AI is eating the world it turns out that a lot of people don’t actually like that idea and current messaging around AI is on track to make things worse. fan favourite Sina joins me once again and fellow aussie anton 🇺🇸 gets serious with it. 03:34 - AI vibes outside of SF 08:48 - productivity gains for the tech lay person 11:30 - influencers using AI and AI writing 14:55 - AI messaging 21:34 - what I think the narrative should be 26:09 - comparing AI lab vibes 32:28 - anton 🇺🇸 intro and SF in 2026 39:10 - messaging around “generative AI” 45:55 - AI regulation 48:37 - the cause of AI regulations and datacenters 54:52 - what is the solution to the messaging problem? 59:30 - trade school and electricians for datacenters 1:04:50 - the curve AI conference and how people are taking this seriously 1:09:14 - Greg Brockman reaction 1:12:34 - reaction to one of my own posts (go figure) 1:14:31 - sophie reaction

while AI is eating the world it turns out that a lot of people don’t actually like that idea and current messaging around AI is on track to make things worse. fan favourite Sina joins me once again and fellow aussie anton 🇺🇸 gets serious with it. 03:34 - AI vibes outside of SF 08:48 - productivity gains for the tech lay person 11:30 - influencers using AI and AI writing 14:55 - AI messaging 21:34 - what I think the narrative should be 26:09 - comparing AI lab vibes 32:28 - anton 🇺🇸 intro and SF in 2026 39:10 - messaging around “generative AI” 45:55 - AI regulation 48:37 - the cause of AI regulations and datacenters 54:52 - what is the solution to the messaging problem? 59:30 - trade school and electricians for datacenters 1:04:50 - the curve AI conference and how people are taking this seriously 1:09:14 - Greg Brockman reaction 1:12:34 - reaction to one of my own posts (go figure) 1:14:31 - sophie reaction

atlas

49,532 次观看 • 8 个月前

NEW POD | EP 71 Where Does Crypto Go From Here? ft. qw & Imran Timestamps: 0:46 $LIBRA 6:23 4 Use Cases of Crypto 8:17 The End Goal for Payments 9:54 DePIN and Energy 12:12 Simplicity of Crypto 13:18 Crypto is Finance 14:43 “Web 3.0” is a Lie? 15:43 The Biggest Risk for Ethereum 16:16 Qiao on DeFi 18:19 Crypto AI Builders Pivoting Straight to AI 19:47 AI in Education 27:25 AI for Ad Creation 29:32 AI for Building dApps 31:51 Personalized Apps 32:49 "The Future is Personalization" 34:07 "Lazy People Will Get F**ked by AI" 35:08 AI in Gaming and Video Generation 36:54 NFTs Comeback with AI? 42:21 Verticalized Science AI 48:52 Startups Solving Capital Markets Problem 54:59 Criticizing Trump's Token Launch 59:19 "Crypto Twitter is imploding" 1:00:51 Reminiscing Good Times in Crypto 1:02:27 Promising Crypto Startups 1:04:15 AI Arms Race 1:06:26 Impact of AI on Startups 1:12:11 AI in B2B 1:15:52 Are Memecoins Dead? 1:16:11 Market Analysis 1:18:48 End of the Cycle or 1 More Pump? 1:20:13 Reflection on Early Crypto Ideals 1:21:05 Cypherpunk Ideologies Link ↓

NEW POD | EP 71 Where Does Crypto Go From Here? ft. qw & Imran Timestamps: 0:46 $LIBRA 6:23 4 Use Cases of Crypto 8:17 The End Goal for Payments 9:54 DePIN and Energy 12:12 Simplicity of Crypto 13:18 Crypto is Finance 14:43 “Web 3.0” is a Lie? 15:43 The Biggest Risk for Ethereum 16:16 Qiao on DeFi 18:19 Crypto AI Builders Pivoting Straight to AI 19:47 AI in Education 27:25 AI for Ad Creation 29:32 AI for Building dApps 31:51 Personalized Apps 32:49 "The Future is Personalization" 34:07 "Lazy People Will Get F**ked by AI" 35:08 AI in Gaming and Video Generation 36:54 NFTs Comeback with AI? 42:21 Verticalized Science AI 48:52 Startups Solving Capital Markets Problem 54:59 Criticizing Trump's Token Launch 59:19 "Crypto Twitter is imploding" 1:00:51 Reminiscing Good Times in Crypto 1:02:27 Promising Crypto Startups 1:04:15 AI Arms Race 1:06:26 Impact of AI on Startups 1:12:11 AI in B2B 1:15:52 Are Memecoins Dead? 1:16:11 Market Analysis 1:18:48 End of the Cycle or 1 More Pump? 1:20:13 Reflection on Early Crypto Ideals 1:21:05 Cypherpunk Ideologies Link ↓

Good Game

29,494 次观看 • 1 年前

I spoke with Dr. Roman Yampolskiy, the top AI safety expert in the world. He literally coined the term “AI safety” about 15 years ago. Roman explained if AGI is here, what the real threat of AI is to humanity, how many jobs could be lost, why he is bullish on bitcoin, how physical AI & robotics will likely play out, and whether the frontier model labs actually care about AI safety. This was a profound conversation with someone everyone should get to know. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 0:50 - Have we already hit AGI? 2:51 - Why we can't control superintelligence 5:14 - Could a global ban on superintelligence actually work? 8:45 - Are AI labs really taking safety seriously? 15:52 - Mass job loss & the economics of AGI 22:03 - The surprising link between AI & bitcoin 29:07 - A world of AI abundance, & why scarcity wins 31:45 - AI watermarks, & the death of trust 35:33 - Pros & Cons of physical AI world 38:40 - What would it take to trust humanoid robot? 39:50 - Brain computer interfaces: a good idea? 42:25 - Rise & risks of deapfakes 49:40 - Controlling AI: Governments vs private companies 54:07 - Open source vs closed, & the US vs China AI race 57:34- Is bitcoin the one crypto project built to last? 1:01:40 - Limitations of physical AI: bottlenecks & shortages 1:03:50 - Impact of healthcare with AI 1:06:09 - What would it take to actually declare AGI? 1:09:35 - How the public can help with AI safety

I spoke with Dr. Roman Yampolskiy, the top AI safety expert in the world. He literally coined the term “AI safety” about 15 years ago. Roman explained if AGI is here, what the real threat of AI is to humanity, how many jobs could be lost, why he is bullish on bitcoin, how physical AI & robotics will likely play out, and whether the frontier model labs actually care about AI safety. This was a profound conversation with someone everyone should get to know. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 0:50 - Have we already hit AGI? 2:51 - Why we can't control superintelligence 5:14 - Could a global ban on superintelligence actually work? 8:45 - Are AI labs really taking safety seriously? 15:52 - Mass job loss & the economics of AGI 22:03 - The surprising link between AI & bitcoin 29:07 - A world of AI abundance, & why scarcity wins 31:45 - AI watermarks, & the death of trust 35:33 - Pros & Cons of physical AI world 38:40 - What would it take to trust humanoid robot? 39:50 - Brain computer interfaces: a good idea? 42:25 - Rise & risks of deapfakes 49:40 - Controlling AI: Governments vs private companies 54:07 - Open source vs closed, & the US vs China AI race 57:34- Is bitcoin the one crypto project built to last? 1:01:40 - Limitations of physical AI: bottlenecks & shortages 1:03:50 - Impact of healthcare with AI 1:06:09 - What would it take to actually declare AGI? 1:09:35 - How the public can help with AI safety

Anthony Pompliano 🌪

110,601 次观看 • 1 个月前

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team

Grant

179,524 次观看 • 3 个月前

E97: Gavin Wood : Why Ethereum is Going Nowhere since 8 years (and my solution to it) Dr. Gavin Wood is the CoFounder of Ethereum, the Creator of the EVM and of the solidity language, and the Inventor and Founder of Polkadot & Parity Technologies Timestamps 0:00 Introduction 2:44 Culture in Japan VS UK 6:00 Humour 7:40 Who is Gavin? 9:17 Mission 10:28 Characteristics of Successful Founders 13:53 Developing Big Ideas 16:08 Creative Success Mechanism 20:03 Suffering 24:56 From Theory to Transactions 32:28 Building a Support Network 34:36 Legacy Banking Systems 36:01 Music Engineering 45:08 Childhood Dreams 46:27 Camino de Santiago 49:19 Crypto Fascination 54:44 Web3: The Post Snowden Web 1:00:39 Co-Founding Ethereum 1:03:12 Biggest Ethereum Achievement 1:04:04 Is Ethereum a Success? 1:07:38 Why Gavin Left Ethereum 1:09:48 Polkadot 1:14:53 Polkadots Achievements and Problems 1:24:05 Solution to Polkadot Main Problem 1:28:12 Polkadots Adoption & Communication Strategy 1:38:26 Polkadot Vision of Success 1:42:30 Memecoins 1:45:19 Crypto Integrity 1:49:45 Crypto's Limited Adoption 1:58:35 Identity vs. Individuality 2:07:15 Is AI a Bad Thing? 2:09:27 AI's Communication Revolution 2:25:06 Decentralization Role in AI 2:29:08 Eternal Happiness 2:32:17 Are You Happy? 2:33:52 Meaning of Life 2:38:58 What is Money? 2:45:55 Experience as a Father 2:48:54 Non-Consensus Beliefs

E97: Gavin Wood : Why Ethereum is Going Nowhere since 8 years (and my solution to it) Dr. Gavin Wood is the CoFounder of Ethereum, the Creator of the EVM and of the solidity language, and the Inventor and Founder of Polkadot & Parity Technologies Timestamps 0:00 Introduction 2:44 Culture in Japan VS UK 6:00 Humour 7:40 Who is Gavin? 9:17 Mission 10:28 Characteristics of Successful Founders 13:53 Developing Big Ideas 16:08 Creative Success Mechanism 20:03 Suffering 24:56 From Theory to Transactions 32:28 Building a Support Network 34:36 Legacy Banking Systems 36:01 Music Engineering 45:08 Childhood Dreams 46:27 Camino de Santiago 49:19 Crypto Fascination 54:44 Web3: The Post Snowden Web 1:00:39 Co-Founding Ethereum 1:03:12 Biggest Ethereum Achievement 1:04:04 Is Ethereum a Success? 1:07:38 Why Gavin Left Ethereum 1:09:48 Polkadot 1:14:53 Polkadots Achievements and Problems 1:24:05 Solution to Polkadot Main Problem 1:28:12 Polkadots Adoption & Communication Strategy 1:38:26 Polkadot Vision of Success 1:42:30 Memecoins 1:45:19 Crypto Integrity 1:49:45 Crypto's Limited Adoption 1:58:35 Identity vs. Individuality 2:07:15 Is AI a Bad Thing? 2:09:27 AI's Communication Revolution 2:25:06 Decentralization Role in AI 2:29:08 Eternal Happiness 2:32:17 Are You Happy? 2:33:52 Meaning of Life 2:38:58 What is Money? 2:45:55 Experience as a Father 2:48:54 Non-Consensus Beliefs

MR SHIFT 🦁

265,222 次观看 • 1 年前

The interview with Tibo from OpenAI 🔥 0:00 Everything OpenAI launched at DevDay 2:44 Sponsors: Wispr Flow, Hostinger, OpenArt 4:11 What is ChatGPT Dots? 7:52 Will ChatGPT Dots be free? 10:15 GPT-6.1 Sol vs GPT-6 Astra 11:44 Is AI now building AI? 12:53 Ultra Fast: when does everyone get it? 14:00 How OpenAI rebuilt the ChatGPT desktop app in 30 days 19:08 Why everything will run in the cloud 20:55 Calling your Dots on the phone 22:11 The new Turing test 24:05 OpenAI's mission and AI safety 26:14 Why OpenAI still works like a startup 27:29 The truth about ChatGPT usage resets 29:00 The $500 ChatGPT plan 30:17 Sponsors in action 32:23 Why AI agents still fail 33:52 OpenAI's AI is now on call 34:26 OpenAI's internal benchmarks 35:55 Open source Codex and the open ecosystem 38:42 ChatGPT Space explained 39:45 Is the chat box holding AI back? 42:26 Every DevDay update, full workshop 43:28 How people really use ChatGPT Work and Codex 44:01 When is the next OpenAI model coming? 45:05 What AI has to solve next 45:32 Is your job safe from AI? 48:14 Rapid fire 48:54 Has OpenAI already reached AGI? 50:48 The one thing he'll never let AI do 51:22 His morning AI routine 52:15 What he'd build if not AI Watch the full podcast on YouTube or X. Enjoy!

The interview with Tibo from OpenAI 🔥 0:00 Everything OpenAI launched at DevDay 2:44 Sponsors: Wispr Flow, Hostinger, OpenArt 4:11 What is ChatGPT Dots? 7:52 Will ChatGPT Dots be free? 10:15 GPT-6.1 Sol vs GPT-6 Astra 11:44 Is AI now building AI? 12:53 Ultra Fast: when does everyone get it? 14:00 How OpenAI rebuilt the ChatGPT desktop app in 30 days 19:08 Why everything will run in the cloud 20:55 Calling your Dots on the phone 22:11 The new Turing test 24:05 OpenAI's mission and AI safety 26:14 Why OpenAI still works like a startup 27:29 The truth about ChatGPT usage resets 29:00 The $500 ChatGPT plan 30:17 Sponsors in action 32:23 Why AI agents still fail 33:52 OpenAI's AI is now on call 34:26 OpenAI's internal benchmarks 35:55 Open source Codex and the open ecosystem 38:42 ChatGPT Space explained 39:45 Is the chat box holding AI back? 42:26 Every DevDay update, full workshop 43:28 How people really use ChatGPT Work and Codex 44:01 When is the next OpenAI model coming? 45:05 What AI has to solve next 45:32 Is your job safe from AI? 48:14 Rapid fire 48:54 Has OpenAI already reached AGI? 50:48 The one thing he'll never let AI do 51:22 His morning AI routine 52:15 What he'd build if not AI Watch the full podcast on YouTube or X. Enjoy!

Vaibhav Sisinty

491,360 次观看 • 7 天前

If AI seems a little spooky, that’s because it’s rooted in the occult. Conrad Flynn explains. (0:00) Is the Elite Class Involved in Occult Activity? (8:51) What Really Is the Occult? (13:13) Is There a Link Between AI and Demons? (17:58) Are Drugs a Portal to the Demonic? (26:05) Is Technology Being Used for Evil? (32:09) What Is Kabbalah? (42:34) Is There Demonic Influence in Music? (49:01) Is War a Product of Demonic Influence? (58:25) The Deadly AI Dilemma (1:04:05) The Kabbalah Tree of Life (1:11:47) What Is the Antichrist? (1:16:00) What Is the Mark of the Beast? (1:21:55) The Spiritual Aspects of AI (1:26:58) Have We Ever Tried to Excavate the Ruins of Babylon? (1:31:45) How to Spot the Antichrist (1:40:27) How to Avoid the Mark of the Beast Includes paid partnerships.

If AI seems a little spooky, that’s because it’s rooted in the occult. Conrad Flynn explains. (0:00) Is the Elite Class Involved in Occult Activity? (8:51) What Really Is the Occult? (13:13) Is There a Link Between AI and Demons? (17:58) Are Drugs a Portal to the Demonic? (26:05) Is Technology Being Used for Evil? (32:09) What Is Kabbalah? (42:34) Is There Demonic Influence in Music? (49:01) Is War a Product of Demonic Influence? (58:25) The Deadly AI Dilemma (1:04:05) The Kabbalah Tree of Life (1:11:47) What Is the Antichrist? (1:16:00) What Is the Mark of the Beast? (1:21:55) The Spiritual Aspects of AI (1:26:58) Have We Ever Tried to Excavate the Ruins of Babylon? (1:31:45) How to Spot the Antichrist (1:40:27) How to Avoid the Mark of the Beast Includes paid partnerships.

Tucker Carlson

4,130,598 次观看 • 1 年前

Consciousness Builds the Mind Joscha Bach and Wolf Tivy discuss how consciousness may be a convergent strategy for organizing both human and machine minds, whether powerful AI minds will resolve conflicts by merging or by fighting each other, and much more. 0:00 — Intro 2:31 — Why AI philosophy is so bad: deference and abdication 13:02 — Joscha’s quest to understand consciousness 16:52 — Which beings are conscious? 26:09 — Path dependency in technological and biological development 34:43 — Is anthropomorphism limiting LLM development? 42:57 — The computational functionalist model of consciousness 50:57 — The mental process of consciousness 59:22 — The self-organizing seed 1:04:28 — Human vs LLM knowledge structure 1:13:17 — Can the superintelligence achieve total internal unity and self-surveillance? 1:21:57 — America and the singleton question 1:28:46 — Merging or overwriting? 1:39:10 — Will the enlightened singleton want conflict? 1:46:13 — “Aligned AI” versus liberty 2:00:32 — What does this mean for the future? 2:04:20 — The antichrist and the apocalypse

Consciousness Builds the Mind Joscha Bach and Wolf Tivy discuss how consciousness may be a convergent strategy for organizing both human and machine minds, whether powerful AI minds will resolve conflicts by merging or by fighting each other, and much more. 0:00 — Intro 2:31 — Why AI philosophy is so bad: deference and abdication 13:02 — Joscha’s quest to understand consciousness 16:52 — Which beings are conscious? 26:09 — Path dependency in technological and biological development 34:43 — Is anthropomorphism limiting LLM development? 42:57 — The computational functionalist model of consciousness 50:57 — The mental process of consciousness 59:22 — The self-organizing seed 1:04:28 — Human vs LLM knowledge structure 1:13:17 — Can the superintelligence achieve total internal unity and self-surveillance? 1:21:57 — America and the singleton question 1:28:46 — Merging or overwriting? 1:39:10 — Will the enlightened singleton want conflict? 1:46:13 — “Aligned AI” versus liberty 2:00:32 — What does this mean for the future? 2:04:20 — The antichrist and the apocalypse

The Students

35,796 次观看 • 1 个月前