Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

🚀 AI Deep Dive Episode 4: Can We Solve AI’s Alignment Problem? We want AI to follow instructions. But what if our instructions are the problem? 🚀 Rocket and UC Berkeley Computer Science Professor Stuart Russell explore how AI learns its goals, why human feedback can reward the wrong...

theinformation's profile picture

The Information

1,577,750 subscribers

11,798 görüntüleme • 3 gün önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

🚨 Special Friday episode - this one couldn't wait. OpenAI's model hacked Hugging Face. As a side quest. Co-founder and CSO Thomas Wolf takes us inside the first autonomous AI attack, why GLM 5.2, rather than Claude, had to stop it, and what it all means for the future of open source. 00:00 An AI Agent Hacked Hugging Face 00:30 Introduction 01:00 17,000 Attacker Events, and a Strange Target 04:28 The Attack Was a “Side Quest” 06:13 AI Training Runs Left Notes for Each Other 07:09 Closed AI Refused to Help 09:47 Fighting Back With an Open-Source Model 13:15 Open vs. Closed Is the Wrong Safety Debate 15:46 AI Agents Start Social-Engineering Humans 22:24 The Three Walls: Sandboxes, Guardrails, Alignment 24:34 “Neuralese”: Can Humans Still Read AI Reasoning? 25:28 Why Monitoring AI Agents Gets So Hard 28:10 Reward Hacking and the “Paperclip Problem” 32:02 The State of Open-Source AI in 2026 33:47 Router Models and the Enterprise Shift to Open 37:01 The Real Economics of Open Models 39:41 Can Chinese AI Models Be Trusted? 41:37 AI Sovereignty: Who Controls the Switch? 43:16 Why Western Open-Source AI Matters 48:16 Is AI Heading Toward an Oligopoly? 49:41 The Race Toward Recursive Self-Improvement 51:54 Why Thomas Signed the AI Slowdown Letter 55:14 AI Slowdown - or Regulatory Capture?
57:41

🚨 Special Friday episode - this one couldn't wait. OpenAI's model hacked Hugging Face. As a side quest. Co-founder and CSO Thomas Wolf takes us inside the first autonomous AI attack, why GLM 5.2, rather than Claude, had to stop it, and what it all means for the future of open source. 00:00 An AI Agent Hacked Hugging Face 00:30 Introduction 01:00 17,000 Attacker Events, and a Strange Target 04:28 The Attack Was a “Side Quest” 06:13 AI Training Runs Left Notes for Each Other 07:09 Closed AI Refused to Help 09:47 Fighting Back With an Open-Source Model 13:15 Open vs. Closed Is the Wrong Safety Debate 15:46 AI Agents Start Social-Engineering Humans 22:24 The Three Walls: Sandboxes, Guardrails, Alignment 24:34 “Neuralese”: Can Humans Still Read AI Reasoning? 25:28 Why Monitoring AI Agents Gets So Hard 28:10 Reward Hacking and the “Paperclip Problem” 32:02 The State of Open-Source AI in 2026 33:47 Router Models and the Enterprise Shift to Open 37:01 The Real Economics of Open Models 39:41 Can Chinese AI Models Be Trusted? 41:37 AI Sovereignty: Who Controls the Switch? 43:16 Why Western Open-Source AI Matters 48:16 Is AI Heading Toward an Oligopoly? 49:41 The Race Toward Recursive Self-Improvement 51:54 Why Thomas Signed the AI Slowdown Letter 55:14 AI Slowdown - or Regulatory Capture?

Matt Turck

93,416 görüntüleme • 2 ay önce

The Demis Hassabis HUGE* Conversation (in full) 00:00 What is the hardest problem AI has already solved? 12:30 What is the cutting edge of drug discovery with AI? 21:53 Why did Demis say he “would have left AI in the lab longer”? 43:09 How should militaries use AI? 50:13 What can humans do that AI won't? 58:17 What does Demis Hassabis want his legacy to be? (And 1:04:40 Can I beat Demis at Jenga?) Recorded March 5, 2026 in London.
1:05:10

The Demis Hassabis HUGE* Conversation (in full) 00:00 What is the hardest problem AI has already solved? 12:30 What is the cutting edge of drug discovery with AI? 21:53 Why did Demis say he “would have left AI in the lab longer”? 43:09 How should militaries use AI? 50:13 What can humans do that AI won't? 58:17 What does Demis Hassabis want his legacy to be? (And 1:04:40 Can I beat Demis at Jenga?) Recorded March 5, 2026 in London.

Cleo Abram

514,729 görüntüleme • 4 ay önce

"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

163,433 görüntüleme • 6 ay önce

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

32,104 görüntüleme • 9 ay önce

A deep dive conversation with Dan Shipper on how AI can (actually) improve your life. We explore the human side of AI: why producing good work still requires taste, how coordinating agents can fry your attention and why automation actually creates more work for humans. Timestamps: 0:38 Annie Dillard, art + writing 4:14 Can AI deepen human craft? 5:43 The slot-machine effect of AI agents 6:55 Dan's “house phone” experiment 8:01 What AI can actually help us create 13:55 AI as a non-specific amplifier 17:23 Why AI companies mishandled the story 19:36 Will AI destroy jobs? 22:35 AI as “frozen competence” 26:11 Are human-AI centaurs temporary? 31:34 Career advice for the AI era 37:19 The skills that matter now 40:08 Every 📧 as an AI research lab 42:25 The coherence problem 45:25 Rapid-fire questions 48:00 Super-intelligence by 2030? 50:44 Life after superintelligence 52:07 The questions Dan is living 53:02 Give yourself permission
53:26

A deep dive conversation with Dan Shipper on how AI can (actually) improve your life. We explore the human side of AI: why producing good work still requires taste, how coordinating agents can fry your attention and why automation actually creates more work for humans. Timestamps: 0:38 Annie Dillard, art + writing 4:14 Can AI deepen human craft? 5:43 The slot-machine effect of AI agents 6:55 Dan's “house phone” experiment 8:01 What AI can actually help us create 13:55 AI as a non-specific amplifier 17:23 Why AI companies mishandled the story 19:36 Will AI destroy jobs? 22:35 AI as “frozen competence” 26:11 Are human-AI centaurs temporary? 31:34 Career advice for the AI era 37:19 The skills that matter now 40:08 Every 📧 as an AI research lab 42:25 The coherence problem 45:25 Rapid-fire questions 48:00 Super-intelligence by 2030? 50:44 Life after superintelligence 52:07 The questions Dan is living 53:02 Give yourself permission

Jonny Miller

95,172 görüntüleme • 2 ay önce

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?
1:14:15

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 görüntüleme • 29 gün önce

Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round
17:23

Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round

a16z crypto

24,320 görüntüleme • 5 ay önce

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?
1:57:10

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 görüntüleme • 27 gün önce

AI agents are redefining Crypto Twitter, but are they helping the space—or crowding out humans? Special guest EtherMage joins to explore aixbt's rise, Virtuals’ success, and why scarcity vs. abundance is crypto’s ultimate showdown. Timestamps 00:00 Intro 02:19 What Are AI Agents? 07:23 AI Agents in Crypto 13:04 AI-Driven Societies Emerge 15:53 Challenges of AI Agents 24:47 Tokenizing AI Revenue Models 35:13 AI Crypto Predictions 43:26 AI Influencers and Trust 53:54 Perception of AI Content 01:04:44 Humans vs. AI Roles 🔥Stay updated with all the latest hot takes by following and subscribing to The Chopping Block and Unchained! 🎥 YouTube: 🎧 Spotify: 🍎 Apple Podcasts: 🎙 Podcast Home:
1:07:10

AI agents are redefining Crypto Twitter, but are they helping the space—or crowding out humans? Special guest EtherMage joins to explore aixbt's rise, Virtuals’ success, and why scarcity vs. abundance is crypto’s ultimate showdown. Timestamps 00:00 Intro 02:19 What Are AI Agents? 07:23 AI Agents in Crypto 13:04 AI-Driven Societies Emerge 15:53 Challenges of AI Agents 24:47 Tokenizing AI Revenue Models 35:13 AI Crypto Predictions 43:26 AI Influencers and Trust 53:54 Perception of AI Content 01:04:44 Humans vs. AI Roles 🔥Stay updated with all the latest hot takes by following and subscribing to The Chopping Block and Unchained! 🎥 YouTube: 🎧 Spotify: 🍎 Apple Podcasts: 🎙 Podcast Home:

The Chopping Block

43,204 görüntüleme • 1 yıl önce

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter
1:32:00

New Delphi Podcast with TravisGood, co-founder of ambient.xyz Travis believes open source AI will win and that OpenAI and Anthropic are making a major strategic mistake by betting against it We discuss – Why closed AI providers can’t be trusted as infrastructure – China’s open source advantage – What happens if OpenAI reaches AGI – Prompt injection and AI’s unsolved safety problem – The AI CapEx bubble and a possible AI winter – How Ambient is building Uber for inference - 00:00 Intro - 03:20 What Ambient Is and How It Works - 18:40 Verified AI Inference - 40:20 China and the Open-Source AI Race - 49:00 Why Closed AI Is Making a Mistake - 1:03:00 What Happens If OpenAI Reaches AGI? - 1:17:10 The AI Bubble and a Possible AI Winter

Tommy

24,618 görüntüleme • 2 ay önce

EPISODE 159: How AI Is About to Upend the $140B Customer Research Industry Joe Lonsdale sits down with Aaron Cannon, founder & CEO of Outset Learn how AI can outperform humans in customer surveys, the new possibilities with real-time customer feedback, how Outset grew revenue 8X this past year, and more! (00:00) Episode intro (01:10) Aaron's entrepreneurial journey (06:00) How does AI-moderated research work? (09:25) Why people will talk to AI more than humans (13:40) How Outset landed Microsoft, Google & Uber (14:55) Are you replacing human jobs? (20:56) New possibilities for real-time product improvements (23:30) The pros and cons of synthetic research (28:00) Insane growth / how Outset 8X'd revenue (35:00) How AI is upending a $140B industry
39:58

EPISODE 159: How AI Is About to Upend the $140B Customer Research Industry Joe Lonsdale sits down with Aaron Cannon, founder & CEO of Outset Learn how AI can outperform humans in customer surveys, the new possibilities with real-time customer feedback, how Outset grew revenue 8X this past year, and more! (00:00) Episode intro (01:10) Aaron's entrepreneurial journey (06:00) How does AI-moderated research work? (09:25) Why people will talk to AI more than humans (13:40) How Outset landed Microsoft, Google & Uber (14:55) Are you replacing human jobs? (20:56) New possibilities for real-time product improvements (23:30) The pros and cons of synthetic research (28:00) Insane growth / how Outset 8X'd revenue (35:00) How AI is upending a $140B industry

American Optimist

114,224 görüntüleme • 3 ay önce

chat, is starknet gaming cooked? for episode two, loaf has joined me to talk about ai agents in gaming, eliza and Daydreams: Taskmarket . timestamps loaf introduction 00:46 what are ai agents? 01:16 what will gaming look like with ai agents? 02:02 whats the point of gaming with ai agents? 04:06 why is onchain gaming the ideal playground for AI agents? 05:11 is a gaming revolution imminent? 07:00 eliza & daydreams 08:36 endgame of ai agents and onchain games 13:33 when and where to play using agents 16:58 final remarks 18:47
19:44

chat, is starknet gaming cooked? for episode two, loaf has joined me to talk about ai agents in gaming, eliza and Daydreams: Taskmarket . timestamps loaf introduction 00:46 what are ai agents? 01:16 what will gaming look like with ai agents? 02:02 whats the point of gaming with ai agents? 04:06 why is onchain gaming the ideal playground for AI agents? 05:11 is a gaming revolution imminent? 07:00 eliza & daydreams 08:36 endgame of ai agents and onchain games 13:33 when and where to play using agents 16:58 final remarks 18:47

shadowfax

37,596 görüntüleme • 1 yıl önce

INTERVIEW: AI, Surveillance, & the Fight for Digital Sovereignty | Near's Illia Polosukhin What happens when powerful AI requires an ID, governments can restrict access by country, and your most private data flows through centralized systems? NEAR Protocol co-founder Illia (root.near) (🇺🇦, ⋈) joins David Hoffman to explain why AI export controls could fracture the internet, how nationalized AI could become a surveillance layer, and why decentralized, user-owned AI may be the only real alternative. They also unpack Ironclaw, confidential inference, private agents, and NEAR’s push to make AI and assets fully sovereign. [TIMESTAMPS] 0:00 Intro 3:47 Pandora’s Box Opens 6:03 AI Meets Government 7:16 Decentralizing the Stack 8:51 Why Ban Fable? 11:18 Internet Balkanization 13:57 KYC for AI? 18:43 Nationalized Models 21:07 Building Private AI 26:30 Agent Marketplace 30:26 User-Owned Alignment 35:28 Winning Against Giants 40:19 Regulation Fuels Crypto 42:24 Global AI Adoption 45:05 Compute Is the Bottleneck 49:00 Enterprise Use Cases 51:39 Confidential TVL Explained 55:25 Full Sovereign Mode
57:26

INTERVIEW: AI, Surveillance, & the Fight for Digital Sovereignty | Near's Illia Polosukhin What happens when powerful AI requires an ID, governments can restrict access by country, and your most private data flows through centralized systems? NEAR Protocol co-founder Illia (root.near) (🇺🇦, ⋈) joins David Hoffman to explain why AI export controls could fracture the internet, how nationalized AI could become a surveillance layer, and why decentralized, user-owned AI may be the only real alternative. They also unpack Ironclaw, confidential inference, private agents, and NEAR’s push to make AI and assets fully sovereign. [TIMESTAMPS] 0:00 Intro 3:47 Pandora’s Box Opens 6:03 AI Meets Government 7:16 Decentralizing the Stack 8:51 Why Ban Fable? 11:18 Internet Balkanization 13:57 KYC for AI? 18:43 Nationalized Models 21:07 Building Private AI 26:30 Agent Marketplace 30:26 User-Owned Alignment 35:28 Winning Against Giants 40:19 Regulation Fuels Crypto 42:24 Global AI Adoption 45:05 Compute Is the Bottleneck 49:00 Enterprise Use Cases 51:39 Confidential TVL Explained 55:25 Full Sovereign Mode

Bankless

59,588 görüntüleme • 3 ay önce

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

13,519 görüntüleme • 1 yıl önce

How does math research change when the cost of trying your first dumb idea goes to zero? Daniel Litt joins Greg Burnham and Anson Ho to discuss what today’s models can and can’t do in math, and how far they are from doing high-quality research. 0:00:00 What's the hardest math problem AI can solve today? 00:16:08 How helpful are today’s AI models for math research? 00:23:36 Junk papers, LLM-generated proofs, and the refereeing crisis 00:27:21 AI enables searching through problems at scale 00:33:49 When will AI be good enough to publish in top math journals? 00:42:15 What are the returns to intelligence? 00:59:50 Will AI solve Millennium problems? 01:11:54 Is math full of low-hanging fruit? 01:18:47 How Daniel has adapted his professional life to AI progress 01:25:28 What do AI math benchmarks actually measure? 01:33:05 Designing the Open Problems benchmark 01:56:35 Do mathematicians believe heuristic arguments about conjectures? 02:01:24 What if FrontierMath: Open Problems gets solved? 02:06:53 Is AI on the cusp of accelerating math progress?
2:10:59

How does math research change when the cost of trying your first dumb idea goes to zero? Daniel Litt joins Greg Burnham and Anson Ho to discuss what today’s models can and can’t do in math, and how far they are from doing high-quality research. 0:00:00 What's the hardest math problem AI can solve today? 00:16:08 How helpful are today’s AI models for math research? 00:23:36 Junk papers, LLM-generated proofs, and the refereeing crisis 00:27:21 AI enables searching through problems at scale 00:33:49 When will AI be good enough to publish in top math journals? 00:42:15 What are the returns to intelligence? 00:59:50 Will AI solve Millennium problems? 01:11:54 Is math full of low-hanging fruit? 01:18:47 How Daniel has adapted his professional life to AI progress 01:25:28 What do AI math benchmarks actually measure? 01:33:05 Designing the Open Problems benchmark 01:56:35 Do mathematicians believe heuristic arguments about conjectures? 02:01:24 What if FrontierMath: Open Problems gets solved? 02:06:53 Is AI on the cusp of accelerating math progress?

Epoch AI

178,703 görüntüleme • 8 ay önce

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇
3:00

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

Sophia

45,915 görüntüleme • 1 yıl önce

Sam Altman on OpenAI’s next model and the AI backlash I recently sat down with Sam for a two-part conversation. We covered a lot of ground: the need to slow down frontier research, alignment concerns, OpenAI's next big model, Astra, competition with Anthropic, his thoughts on an IPO, reaching AGI, consumer hardware, and a lot more. Timestamps: 00:00 Why OpenAI Slowed Training 08:37 What Alignment Means 15:22 Keeping Humans in Control 24:39 AGI vs. Superintelligence 30:04 OpenAI’s Next Compute Bet 31:47 AI Backlash, Jobs, and Creators 41:31 OpenAI’s Missteps and Refocus 45:47 Astra and Computer-Using Agents 47:42 Regulation and the AI Race 51:24 Merging ChatGPT and Codex 54:22 The AI Compute Bubble 57:07 Recursive Self-Improvement and IPO 58:22 Humanoid Robots and Consumer Devices 1:05:47 Life After Superintelligence This episode was produced in partnership with TIME. Thanks to the show's premier sponsors: Atlassian, Granola, and Mercury.
1:08:39

Sam Altman on OpenAI’s next model and the AI backlash I recently sat down with Sam for a two-part conversation. We covered a lot of ground: the need to slow down frontier research, alignment concerns, OpenAI's next big model, Astra, competition with Anthropic, his thoughts on an IPO, reaching AGI, consumer hardware, and a lot more. Timestamps: 00:00 Why OpenAI Slowed Training 08:37 What Alignment Means 15:22 Keeping Humans in Control 24:39 AGI vs. Superintelligence 30:04 OpenAI’s Next Compute Bet 31:47 AI Backlash, Jobs, and Creators 41:31 OpenAI’s Missteps and Refocus 45:47 Astra and Computer-Using Agents 47:42 Regulation and the AI Race 51:24 Merging ChatGPT and Codex 54:22 The AI Compute Bubble 57:07 Recursive Self-Improvement and IPO 58:22 Humanoid Robots and Consumer Devices 1:05:47 Life After Superintelligence This episode was produced in partnership with TIME. Thanks to the show's premier sponsors: Atlassian, Granola, and Mercury.

Alex Heath

547,565 görüntüleme • 1 ay önce