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AI Expert’s Chilling Warning About Super-intelligence - 99.9999% Chance Human Extinction | Dr. Roman Yampolskiy (0:00) Will AI Destroy Humanity in 10 Years? (10:16) Does Iran Have Nuclear Weapons? (21:20) Social Engineering & Propaganda (28:36) AI-Driven Unemployment (54:37) Do AI Models Have Governors? (1:02:34) The Rise of Superintelligence (1:28:10)...

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PBD Podcast

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16,464 просмотров • 9 дней назад •via X (Twitter)

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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
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We interviewed Nick Bostrom, The author of NYT’s Bestseller “Superintelligence,” and one of the most influential experts on AI Risks. Timestamps: 2:11 - Will AI be used for Extreme Bad? What are the odds? 4:44 - What are the biggest concerns with AI? 6:16 - People are greatly underestimate what Super-intelligence will be. 7:19 - Can we trust anyone with creating a Super-Intelligent AI? 8:49 - Are the big AI companies taking AI safety serious enough? 10:39 - Are multiple AI systems undergoing the transition to super-intelligence at the same time a good or bad thing? 13:10 - How do we prevent AI from becoming biased like we saw with Google Gemini? 16:17 - Is there a danger of AI being too truthful or too opinionated? 18:10 - When do AI’s gain a moral status? How do we know? 19:40 - What is Truth for an AI? 22:37 - What has surprised Bostrom the most regarding AI in the past 10 years? 26:13 - Is AI moving faster or slower than Bostrom imagined 10 years ago? 26:38 - Do we see another AI Winter or AGI first? 28:21 - Is energy a limiting factor in AI? 30:00 - What is Deep Utopia? 33:18 - When will we reach Super-intelligence and Deep Utopia? 36:00 - Can a Deep Utopia be a problem for humanity? 39:29 - Could a Utopian society lead to the creation of a simulated reality as a way to escape? 42:28 - If we are in a simulation, is our consciousness simulated? 47:48 - Elon Musk or Sam Altman? 48:17 - Artificial Super-Intelligence before or after 2035? 49:40 - How can you get Nick Bostrom’s book “Deep Utopia?”

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1,779,641 просмотров • 7 месяцев назад

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Can AI truly understand concepts, or is it just processing data? 🤖 Join Hannah Fry as she discusses this and more with our Principal Scientist Murray Shanahan. They break down the meaning of consciousness and explore how it might – or might not – apply to AI, as well as exploring the anthropomorphism of multimodal models. Watch our podcast now ↓ Timestamps: 00:00 Introduction 02:00 Ex Machina 03:28 John McCarthy & Coining "AI" 05:45 Symbolic AI 09:43 AI Reasoning 14:42 Turing Test 18:10 Alternative Tests 21:58 Anthropomorphism 26:42 Embodied AI 28:17 AI Consciousness 34:00 Octopus Analogy 37:48 Prompt Engineering 39:40 Exotic Mind-Like Entities 40:44 Conclusion

Google DeepMind

292,685 просмотров • 1 год назад

Here's my conversation with the founding team of Cursor, a popular code editor (based on VSCode) that specializes in AI-assisted programming. This is a super technical conversation that is bigger than just about one code editor. It's about the future of programming and, in general, the future of human-AI collaboration. It's here on X in full, and is up on everywhere else. Timestamps: 0:00 - Introduction 0:59 - Code editor basics 3:09 - GitHub Copilot 10:27 - Cursor 16:54 - Cursor Tab 23:08 - Code diff 31:20 - ML details 36:54 - GPT vs Claude 43:28 - Prompt engineering 50:54 - AI agents 1:04:51 - Running code in background 1:09:31 - Debugging 1:14:58 - Dangerous code 1:26:09 - Branching file systems 1:29:20 - Scaling challenges 1:43:32 - Context 1:48:39 - OpenAI o1 2:00:01 - Synthetic data 2:03:48 - RLHF vs RLAIF 2:05:34 - Fields Medal for AI 2:08:17 - Scaling laws 2:17:06 - The future of programming
2:28:55

Here's my conversation with the founding team of Cursor, a popular code editor (based on VSCode) that specializes in AI-assisted programming. This is a super technical conversation that is bigger than just about one code editor. It's about the future of programming and, in general, the future of human-AI collaboration. It's here on X in full, and is up on everywhere else. Timestamps: 0:00 - Introduction 0:59 - Code editor basics 3:09 - GitHub Copilot 10:27 - Cursor 16:54 - Cursor Tab 23:08 - Code diff 31:20 - ML details 36:54 - GPT vs Claude 43:28 - Prompt engineering 50:54 - AI agents 1:04:51 - Running code in background 1:09:31 - Debugging 1:14:58 - Dangerous code 1:26:09 - Branching file systems 1:29:20 - Scaling challenges 1:43:32 - Context 1:48:39 - OpenAI o1 2:00:01 - Synthetic data 2:03:48 - RLHF vs RLAIF 2:05:34 - Fields Medal for AI 2:08:17 - Scaling laws 2:17:06 - The future of programming

Lex Fridman

1,262,904 просмотров • 1 год назад

Here's my conversation with DHH. He is back for round 2! It was an epic fun 5 hour conversation about the future of programming, AI, Linux, and human civilization. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:27 - Introduction 2:56 - Programming with AI agents 18:14 - How software will change 27:30 - AI impact on open source 37:21 - Building Omarchy Linux distro 47:05 - Vibe coding vs agentic engineering 1:00:06 - The end of manual programming 1:10:24 - Advice for programmers 1:22:30 - Surviving Internet Hate 1:31:46 - Programming setup for AI Agents 1:44:11 - Obsessing about speed 2:07:06 - Voice prompting vs typing 2:21:05 - Best AI coding models 2:37:55 - Best AI coding harnesses 2:50:57 - AI video generation and filmmaking 3:10:28 - Fatherhood 3:38:35 - Linux will win the desktop 3:49:51 - PewDiePie 3:59:24 - Future of programming 4:22:17 - Politics and immigration 4:53:54 - Longevity, over-optimization, and fear of death 5:05:38 - Eternal recurrence and future of human civization
5:15:50

Here's my conversation with DHH. He is back for round 2! It was an epic fun 5 hour conversation about the future of programming, AI, Linux, and human civilization. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:27 - Introduction 2:56 - Programming with AI agents 18:14 - How software will change 27:30 - AI impact on open source 37:21 - Building Omarchy Linux distro 47:05 - Vibe coding vs agentic engineering 1:00:06 - The end of manual programming 1:10:24 - Advice for programmers 1:22:30 - Surviving Internet Hate 1:31:46 - Programming setup for AI Agents 1:44:11 - Obsessing about speed 2:07:06 - Voice prompting vs typing 2:21:05 - Best AI coding models 2:37:55 - Best AI coding harnesses 2:50:57 - AI video generation and filmmaking 3:10:28 - Fatherhood 3:38:35 - Linux will win the desktop 3:49:51 - PewDiePie 3:59:24 - Future of programming 4:22:17 - Politics and immigration 4:53:54 - Longevity, over-optimization, and fear of death 5:05:38 - Eternal recurrence and future of human civization

Lex Fridman

810,326 просмотров • 9 дней назад

Superintelligence or bust. Dylan Patel (Dylan Patel) breaks down the AI arms race. Meta, OpenAI, Apple, NVIDIA, xAI, Microsoft...we cover it all. Full interview below 👇 0:00 - Intro 1:15 - Meta’s llama struggles 6:20 - ScaleAI acquisition and $100m offers 15:32 - OpenAI’s relationship with Microsoft 22:28 - GPT4.5, what went wrong? 28:43 - Apple’s AI blunders 31:07 - Apple vs. NVIDIA Beef 33:43 - On-device vs. Cloud AI 39:39 - NVIDIA vs. AMD 48:47 - Grok and xAI 52:49 - Grok 3.5 54:16 - AI and Job Loss 1:00:59 - Who wins Super Intelligence race?
1:02:16

Superintelligence or bust. Dylan Patel (Dylan Patel) breaks down the AI arms race. Meta, OpenAI, Apple, NVIDIA, xAI, Microsoft...we cover it all. Full interview below 👇 0:00 - Intro 1:15 - Meta’s llama struggles 6:20 - ScaleAI acquisition and $100m offers 15:32 - OpenAI’s relationship with Microsoft 22:28 - GPT4.5, what went wrong? 28:43 - Apple’s AI blunders 31:07 - Apple vs. NVIDIA Beef 33:43 - On-device vs. Cloud AI 39:39 - NVIDIA vs. AMD 48:47 - Grok and xAI 52:49 - Grok 3.5 54:16 - AI and Job Loss 1:00:59 - Who wins Super Intelligence race?

Matthew Berman

152,595 просмотров • 1 год 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

32,033 просмотров • 8 месяцев назад

NEW EP: Why AGI Will Happen This Decade with Emad Mostaque The AI revolution is here, but *actually* who controls the intelligence we'll all rely on? In today's episode, & Wayne Sim sit down with Emad of Intelligent Internet to cover: > Who Controls AI? > The Ghibli Effect by ChatGPT-4o > Why Most AI Models Are Inefficient > Universal Basic Intelligence > AI Atlantis: Economic Disruption & Rebirth > Credibly Neutral AI Infrastructure Full episode links below. Timestamps: 00:00 Intro 00:56 Mantle Ad 01:37 Ghibli AI Use 04:50 Replacing Humans with AI? 05:21 Artificial Remote Intelligence 10:14 Emad’s Opinion on Better AI Models 12:25 Concentration of Power with AI? 16:34 Training AI Models 20:46 Compute Demand Collapse? 27:00 Abundance of Open Source AI 30:04 Shift Towards Specialized Models 34:05 RedStone Ad 34:18 Frax Ad 34:44 Approaching Biases in AI 45:16 End of Original Thoughts? 50:30 Intelligent Internet & Reinforced Learning 59:07 Coordinating Incentives
1:05:59

NEW EP: Why AGI Will Happen This Decade with Emad Mostaque The AI revolution is here, but *actually* who controls the intelligence we'll all rely on? In today's episode, & Wayne Sim sit down with Emad of Intelligent Internet to cover: > Who Controls AI? > The Ghibli Effect by ChatGPT-4o > Why Most AI Models Are Inefficient > Universal Basic Intelligence > AI Atlantis: Economic Disruption & Rebirth > Credibly Neutral AI Infrastructure Full episode links below. Timestamps: 00:00 Intro 00:56 Mantle Ad 01:37 Ghibli AI Use 04:50 Replacing Humans with AI? 05:21 Artificial Remote Intelligence 10:14 Emad’s Opinion on Better AI Models 12:25 Concentration of Power with AI? 16:34 Training AI Models 20:46 Compute Demand Collapse? 27:00 Abundance of Open Source AI 30:04 Shift Towards Specialized Models 34:05 RedStone Ad 34:18 Frax Ad 34:44 Approaching Biases in AI 45:16 End of Original Thoughts? 50:30 Intelligent Internet & Reinforced Learning 59:07 Coordinating Incentives

The Rollup

32,804 просмотров • 1 год назад

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 ↓
1:22:45

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 просмотров • 1 год назад

Here's my conversation with Yann LeCun (Yann LeCun) about AI, importance of open source, limits of LLMs, why AI doomers are wrong, and the path to AGI. This was a fun and fascinating technical conversation! It's here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:18 - Limits of LLMs 13:54 - Bilingualism and thinking 17:46 - Video prediction 25:07 - JEPA (Joint-Embedding Predictive Architecture) 28:15 - JEPA vs LLMs 37:31 - DINO and I-JEPA 38:51 - V-JEPA 44:22 - Hierarchical planning 50:40 - Autoregressive LLMs 1:06:06 - AI hallucination 1:11:30 - Reasoning in AI 1:29:02 - Reinforcement learning 1:34:10 - Woke AI 1:43:48 - Open source 1:47:26 - AI and ideology 1:49:58 - Marc Andreesen 1:57:56 - Llama 3 2:04:20 - AGI 2:08:48 - AI doomers 2:24:38 - Joscha Bach 2:28:51 - Humanoid robots 2:38:00 - Hope for the future
2:47:07

Here's my conversation with Yann LeCun (Yann LeCun) about AI, importance of open source, limits of LLMs, why AI doomers are wrong, and the path to AGI. This was a fun and fascinating technical conversation! It's here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:18 - Limits of LLMs 13:54 - Bilingualism and thinking 17:46 - Video prediction 25:07 - JEPA (Joint-Embedding Predictive Architecture) 28:15 - JEPA vs LLMs 37:31 - DINO and I-JEPA 38:51 - V-JEPA 44:22 - Hierarchical planning 50:40 - Autoregressive LLMs 1:06:06 - AI hallucination 1:11:30 - Reasoning in AI 1:29:02 - Reinforcement learning 1:34:10 - Woke AI 1:43:48 - Open source 1:47:26 - AI and ideology 1:49:58 - Marc Andreesen 1:57:56 - Llama 3 2:04:20 - AGI 2:08:48 - AI doomers 2:24:38 - Joscha Bach 2:28:51 - Humanoid robots 2:38:00 - Hope for the future

Lex Fridman

1,022,504 просмотров • 2 лет назад