Loading video...

Video Failed to Load

Go Home

Played a quick game with Daniel Negreanu (Daniel Negreanu) before the podcast. Wild how fast someone at his level can read you. We spoke about how people behave when the stakes rise, what pressure does to decision-making, how influence works at a table, and physical cues. Also got into...

prvkhvr's profile picture

Prakhar Gupta

120,298 subscribers

114,188 views • 9 months ago •via X (Twitter)

GamingComedyEducation
LIVE

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

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 views • 7 months ago

You don’t know people as well as you think. Polina Pompliano studies the world’s highest performers—and what she’s found challenges how we think about success, creativity, and human behavior. From mental models to media bias to the hidden motivations driving people, this is a deep dive into how great thinkers actually see the world. TIMESTAMPS 00:00 – Intro 02:12 – How Polina Breaks Down High Performers 06:02 – Rationality vs Emotion 10:03 – Creativity and Logic 15:30 – The Power of Storytelling 19:00 – Building The Profile 22:29 – The Mask vs The Real Person 30:48 – Growing Up in Bulgaria 36:03 – What Freedom Actually Means 40:17 – Why We’re All in Ideological “Cults” 01:00:15 – What She Learned From Profiling People
1:07:07

You don’t know people as well as you think. Polina Pompliano studies the world’s highest performers—and what she’s found challenges how we think about success, creativity, and human behavior. From mental models to media bias to the hidden motivations driving people, this is a deep dive into how great thinkers actually see the world. TIMESTAMPS 00:00 – Intro 02:12 – How Polina Breaks Down High Performers 06:02 – Rationality vs Emotion 10:03 – Creativity and Logic 15:30 – The Power of Storytelling 19:00 – Building The Profile 22:29 – The Mask vs The Real Person 30:48 – Growing Up in Bulgaria 36:03 – What Freedom Actually Means 40:17 – Why We’re All in Ideological “Cults” 01:00:15 – What She Learned From Profiling People

Infinite Loops 🎙

50,994 views • 5 months ago

Bret Weinstein, Viva Frei and Jimmy Dore tangle over who shot Charlie Kirk, and how. 00:00:00 Three people, three positions, one killing 00:01:16 Sponsor: SaunaSpace 00:03:39 Sponsor: MUD\WTR 00:05:27 Where each of us has landed as of today 00:05:47 Viva Frei: it was a bullet from the Losee roof 00:08:41 Jimmy Dore: the case for a cover-up 00:16:41 When a Question Becomes an Accusation 00:18:15 Morality as a Substitute for Argument 00:21:27 Sponsor: Helix 00:22:42 A Biologist's Toolkit 00:25:35 George Zinn and the Reflex to Confess 00:29:42 Paving the Courtyard 00:38:11 The Exploding Microphone 00:45:09 Joe Kent Says He Was Stopped 00:46:50 The Mic That Should Have Recorded It 00:52:58 O'Neill, the Hamptons, and 39 Minutes 00:57:28 "You Don't Have an FBI" 00:59:26 Butler and the Roof Nobody Covered 01:06:27 Harpole, Shawn Ryan, and the Drones 01:11:48 The Prosecutor's Fallacy 01:15:29 Drones and a Plane at 200 Feet 01:22:06 Foreign Nexus, or Domestic 01:29:07 Retroactive Continuity 01:33:21 What Ballistics Can and Cannot Show 01:38:10 A Potemkin Explanation 01:44:14 TPUSA After Charlie 01:49:20 Iran, Motive, and What Charlie Opposed 01:51:26 "Who I Fear Is the People..." 01:56:31 A Nation, or Whatever Controls It 02:00:43 The Phone, the Necklace, the Car 02:04:39 The Emergency Cleanup Order 02:07:20 When No Answer Will Be Believed 02:09:34 Conspiracy Psychosis 02:10:47 Closing Thoughts
2:11:24

Bret Weinstein, Viva Frei and Jimmy Dore tangle over who shot Charlie Kirk, and how. 00:00:00 Three people, three positions, one killing 00:01:16 Sponsor: SaunaSpace 00:03:39 Sponsor: MUD\WTR 00:05:27 Where each of us has landed as of today 00:05:47 Viva Frei: it was a bullet from the Losee roof 00:08:41 Jimmy Dore: the case for a cover-up 00:16:41 When a Question Becomes an Accusation 00:18:15 Morality as a Substitute for Argument 00:21:27 Sponsor: Helix 00:22:42 A Biologist's Toolkit 00:25:35 George Zinn and the Reflex to Confess 00:29:42 Paving the Courtyard 00:38:11 The Exploding Microphone 00:45:09 Joe Kent Says He Was Stopped 00:46:50 The Mic That Should Have Recorded It 00:52:58 O'Neill, the Hamptons, and 39 Minutes 00:57:28 "You Don't Have an FBI" 00:59:26 Butler and the Roof Nobody Covered 01:06:27 Harpole, Shawn Ryan, and the Drones 01:11:48 The Prosecutor's Fallacy 01:15:29 Drones and a Plane at 200 Feet 01:22:06 Foreign Nexus, or Domestic 01:29:07 Retroactive Continuity 01:33:21 What Ballistics Can and Cannot Show 01:38:10 A Potemkin Explanation 01:44:14 TPUSA After Charlie 01:49:20 Iran, Motive, and What Charlie Opposed 01:51:26 "Who I Fear Is the People..." 01:56:31 A Nation, or Whatever Controls It 02:00:43 The Phone, the Necklace, the Car 02:04:39 The Emergency Cleanup Order 02:07:20 When No Answer Will Be Believed 02:09:34 Conspiracy Psychosis 02:10:47 Closing Thoughts

Bret Weinstein

327,259 views • 29 days ago

Grant Sanderson, (Grant Sanderson) created one of the most beloved math channels on the internet. Grant is a Stanford math grad, Khan Academy alum, and self-taught animator who built his own open-source visualization engine from scratch. From students learning linear algebra for the first time, to researchers, to millions of curious people on the internet, Grant Sanderson makes math feel beautiful. Topics we cover - How Grant wrote the "best wedding speech anyone's ever heard" with 24 hours notice - Why he's never felt the burnout other creators describe after 10+ years His take on the algorithm - The real problem with modern education - Being a source vs. being a relay and original thinking - Why he's now building a team and rethinking sponsorships - and much more! Timestamps 00:00 Intro 01:05 How to Write a Wedding Speech 07:04 Use Pauses Like a Pro 11:39 Going Full Time on YouTube 17:27 Why I Left Academia 20:51 Explain It vs. Discover It 27:53 Be a Source, Not a Relay 39:00 The Analytics Dopamine Trap 43:23 Your Algorithm = Your Audience 47:36 Fun Work vs. Strategic Work 52:12 Mental Hygiene for Creators 54:15 Write to Think, Not to Publish 56:49 How My Team Changed Everything 01:01:36 New Ways I'm Making Money 01:06:05 The Loneliness of Solo Creating 01:09:37 How Ego Shapes Your Topics 01:11:31 The Beauty of High Dimensions 01:17:36 Pretty Videos vs. Clear Videos 01:23:14 Will LLMs Kill Motivation to Learn? 01:29:32 Don't Niche Down Too Early 01:34:37 Happiness vs. Fulfillment 01:38:01 Growth vs. Serving Your Audience 01:48:37 Teaching Empathy to Kids 01:51:48 Lightning Round I hope you enjoy this one!! Grant Sanderson (Grant Sanderson): The High Cost of Being a Second-Hand Thinker is below and on all the major platforms.
1:55:28

Grant Sanderson, (Grant Sanderson) created one of the most beloved math channels on the internet. Grant is a Stanford math grad, Khan Academy alum, and self-taught animator who built his own open-source visualization engine from scratch. From students learning linear algebra for the first time, to researchers, to millions of curious people on the internet, Grant Sanderson makes math feel beautiful. Topics we cover - How Grant wrote the "best wedding speech anyone's ever heard" with 24 hours notice - Why he's never felt the burnout other creators describe after 10+ years His take on the algorithm - The real problem with modern education - Being a source vs. being a relay and original thinking - Why he's now building a team and rethinking sponsorships - and much more! Timestamps 00:00 Intro 01:05 How to Write a Wedding Speech 07:04 Use Pauses Like a Pro 11:39 Going Full Time on YouTube 17:27 Why I Left Academia 20:51 Explain It vs. Discover It 27:53 Be a Source, Not a Relay 39:00 The Analytics Dopamine Trap 43:23 Your Algorithm = Your Audience 47:36 Fun Work vs. Strategic Work 52:12 Mental Hygiene for Creators 54:15 Write to Think, Not to Publish 56:49 How My Team Changed Everything 01:01:36 New Ways I'm Making Money 01:06:05 The Loneliness of Solo Creating 01:09:37 How Ego Shapes Your Topics 01:11:31 The Beauty of High Dimensions 01:17:36 Pretty Videos vs. Clear Videos 01:23:14 Will LLMs Kill Motivation to Learn? 01:29:32 Don't Niche Down Too Early 01:34:37 Happiness vs. Fulfillment 01:38:01 Growth vs. Serving Your Audience 01:48:37 Teaching Empathy to Kids 01:51:48 Lightning Round I hope you enjoy this one!! Grant Sanderson (Grant Sanderson): The High Cost of Being a Second-Hand Thinker is below and on all the major platforms.

luba yudasina

151,856 views • 4 months ago

My goal was to record a conversation completely free of "AI doomer" takes as a timeline cleanser. For this episode, I interviewed Casey Muratori (Casey Muratori) who is a video game developer and programming creator also known for his talks about the history of computing. In this episode: • Surprising findings in computer history • Where bad code comes from • The only unbreakable law in software engineering • His career in the video game industry • Why you should read technical papers Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 01:08 Digging into computer science history 04:08 What shocked him 16:23 Dijkstra was depressed 26:17 The personal side of goto considered harmful 35:09 The anatomy of a 35 year mistake 50:12 Clean code horrible performance 58:33 How to write high performance code 01:01:18 Where bad code comes from 01:06:37 Why design docs before code is a bad idea 01:09:20 The only unbreakable law in software engineering 01:15:57 How he got into programming 01:21:16 Why he didnt work in big tech 01:30:44 Should you work at a startup early on 01:34:52 What video game engineering is like 01:39:57 Why preventing recursion is reasonable 01:43:24 Is vibe coding bad for the industry 01:50:17 Technical reading recommendation 01:54:27 Advice for his younger self 01:56:54 Outro
1:57:50

My goal was to record a conversation completely free of "AI doomer" takes as a timeline cleanser. For this episode, I interviewed Casey Muratori (Casey Muratori) who is a video game developer and programming creator also known for his talks about the history of computing. In this episode: • Surprising findings in computer history • Where bad code comes from • The only unbreakable law in software engineering • His career in the video game industry • Why you should read technical papers Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 01:08 Digging into computer science history 04:08 What shocked him 16:23 Dijkstra was depressed 26:17 The personal side of goto considered harmful 35:09 The anatomy of a 35 year mistake 50:12 Clean code horrible performance 58:33 How to write high performance code 01:01:18 Where bad code comes from 01:06:37 Why design docs before code is a bad idea 01:09:20 The only unbreakable law in software engineering 01:15:57 How he got into programming 01:21:16 Why he didnt work in big tech 01:30:44 Should you work at a startup early on 01:34:52 What video game engineering is like 01:39:57 Why preventing recursion is reasonable 01:43:24 Is vibe coding bad for the industry 01:50:17 Technical reading recommendation 01:54:27 Advice for his younger self 01:56:54 Outro

Ryan Peterman

60,951 views • 7 days ago

Reasoning from scratch round 2: In this video, I cover the text generation process in LLMs and KV caching (to prepare the base model before adding reasoning techniques in the upcoming ones). 00:00 Introduction and reasoning model demo 01:55 How to work through the book 05:00 Chapter 2 overview 08:25 Checking PyTorch and hardware support 10:26 Apple silicon and MPS caveats 15:00 Cloud GPU options 16:08 Tokens and tokenization 18:20 Qwen3 and the Reasoning From Scratch package 23:05 Encoding and decoding text 26:24 Downloading weights and selecting a device 31:01 Loading the pretrained Qwen3 model 34:32 How LLMs generate text 36:47 Input tensors and batch dimensions 41:48 Running the model in inference mode 44:11 Logits and next-token predictions 49:21 Greedy decoding with argmax 52:28 Building a streaming text generator 01:01:28 Generating text and handling end-of-sequence tokens 01:06:00 Benchmarking text generation 01:14:34 How KV caching works 01:17:22 Adding KV caching and measuring the speedup 01:24:31 Model compilation with torch.compile 01:30:33 Combining compilation with KV caching 01:32:53 Comparing CPU and GPU performance 01:35:32 Recap and next steps
1:36:42

Reasoning from scratch round 2: In this video, I cover the text generation process in LLMs and KV caching (to prepare the base model before adding reasoning techniques in the upcoming ones). 00:00 Introduction and reasoning model demo 01:55 How to work through the book 05:00 Chapter 2 overview 08:25 Checking PyTorch and hardware support 10:26 Apple silicon and MPS caveats 15:00 Cloud GPU options 16:08 Tokens and tokenization 18:20 Qwen3 and the Reasoning From Scratch package 23:05 Encoding and decoding text 26:24 Downloading weights and selecting a device 31:01 Loading the pretrained Qwen3 model 34:32 How LLMs generate text 36:47 Input tensors and batch dimensions 41:48 Running the model in inference mode 44:11 Logits and next-token predictions 49:21 Greedy decoding with argmax 52:28 Building a streaming text generator 01:01:28 Generating text and handling end-of-sequence tokens 01:06:00 Benchmarking text generation 01:14:34 How KV caching works 01:17:22 Adding KV caching and measuring the speedup 01:24:31 Model compilation with torch.compile 01:30:33 Combining compilation with KV caching 01:32:53 Comparing CPU and GPU performance 01:35:32 Recap and next steps

Sebastian Raschka

65,595 views • 15 days ago

Months ago, Dustin Kittle reached out to me to tell me how our farmers are losing their farmland and the government is allowing it to happen. Dustin was one of the inspirations for starting my show in the first place because I thought to myself, "if people only knew." Last week I drove down to Tennessee to film this episode of him telling his story. I know I am a very small fish, but I hope this reaches the right people to make a difference to save our family farms. Dustin is not just a farmer, he is also a very successful lawyer. If he can't stop this, our small farms have no chance. We need President Trump and congress to step in immediately. --- 01:18 Dustin’s Background 03:30 Buying a Farm 07:35 What is Farm Credit? 09:27 Farm Credit Administration 12:34 Getting a Loan 22:37 Farm Credit Goes After His Mom 41:09 Extortion 47:22 File Complaint with FCA 58:51 What the FCA Did 01:05:47 Why is this Happening? 01:10:38 Foreclosure 01:19:21 After the Loan was Paid 01:25:08 FCA Releases Findings 01:31:21 Dustin Kittle Sues the President 02:02:25 What can we do? 02:06:56 Why Dustin was Targeted 02:21:05 Keeping People Quiet 02:22:51 What can Farmers Do? 02:25:38 Farm Credit Sues Dustin 02:29:35 Threats Against Dustin 02:34:20 Suing Biden and Not Trump 02:36:32 Foreign Governments Buying Farmland 02:37:46 What Farm Credit Does with the Land 02:43:14 What can we do - continued Quick Hitters 02:51:52 Thoughts on Brooke Rollins 02:56:35 Subsidies 03:01:54 Bird Flu 03:08:34 Country of Origin Labeling 03:10:32 Pesticide Immunity
3:28:52

Months ago, Dustin Kittle reached out to me to tell me how our farmers are losing their farmland and the government is allowing it to happen. Dustin was one of the inspirations for starting my show in the first place because I thought to myself, "if people only knew." Last week I drove down to Tennessee to film this episode of him telling his story. I know I am a very small fish, but I hope this reaches the right people to make a difference to save our family farms. Dustin is not just a farmer, he is also a very successful lawyer. If he can't stop this, our small farms have no chance. We need President Trump and congress to step in immediately. --- 01:18 Dustin’s Background 03:30 Buying a Farm 07:35 What is Farm Credit? 09:27 Farm Credit Administration 12:34 Getting a Loan 22:37 Farm Credit Goes After His Mom 41:09 Extortion 47:22 File Complaint with FCA 58:51 What the FCA Did 01:05:47 Why is this Happening? 01:10:38 Foreclosure 01:19:21 After the Loan was Paid 01:25:08 FCA Releases Findings 01:31:21 Dustin Kittle Sues the President 02:02:25 What can we do? 02:06:56 Why Dustin was Targeted 02:21:05 Keeping People Quiet 02:22:51 What can Farmers Do? 02:25:38 Farm Credit Sues Dustin 02:29:35 Threats Against Dustin 02:34:20 Suing Biden and Not Trump 02:36:32 Foreign Governments Buying Farmland 02:37:46 What Farm Credit Does with the Land 02:43:14 What can we do - continued Quick Hitters 02:51:52 Thoughts on Brooke Rollins 02:56:35 Subsidies 03:01:54 Bird Flu 03:08:34 Country of Origin Labeling 03:10:32 Pesticide Immunity

Anna Matson

88,930 views • 1 year ago

He just quit. He was a primary editor for Diary of a CEO. So I asked him to tell all of his secrets for how he helps the Diary of a CEO be the number 1 podcast on YouTube. 00:00:00 Why Trailers Are Essential for Podcast Growth 00:03:30 Why Most People Are Doing Trailers Wrong 00:06:36 From Film and TV to Diary of a CEO 00:11:48 Retention Rates and What They Actually Mean 00:14:52 What Actually Makes a Podcast Good 00:17:00 Why the Guest Is 50% of Everything 00:22:59 What Makes a Great Podcast Host 00:26:31 Red Flags in Podcast Trailers 00:30:33 The Jefferson Fisher Hook Breakdown 00:34:16 The Louis Tomlinson Hook Breakdown 00:42:35 The 15 Point Checklist for the Perfect Trailer 00:45:28 The Oz Pearlman Hook (41 Second Rule) 00:48:06 The Laughter Track Hack 00:54:11 Sound Design and Visual Details 00:57:04 How to Choose Music Like a Film Director 01:00:02 Disney Imagineering Lesson 01:02:46 The Vanessa Van Edwards Hook Breakdown 01:07:02 The Kevin Hart Narrative Arc Breakdown 01:16:40 The A-B-C Storytelling Framework 01:20:13 The Easiest Win You Can Implement Right Now 01:22:36 How Diary of a CEO Uses AI
1:30:01

He just quit. He was a primary editor for Diary of a CEO. So I asked him to tell all of his secrets for how he helps the Diary of a CEO be the number 1 podcast on YouTube. 00:00:00 Why Trailers Are Essential for Podcast Growth 00:03:30 Why Most People Are Doing Trailers Wrong 00:06:36 From Film and TV to Diary of a CEO 00:11:48 Retention Rates and What They Actually Mean 00:14:52 What Actually Makes a Podcast Good 00:17:00 Why the Guest Is 50% of Everything 00:22:59 What Makes a Great Podcast Host 00:26:31 Red Flags in Podcast Trailers 00:30:33 The Jefferson Fisher Hook Breakdown 00:34:16 The Louis Tomlinson Hook Breakdown 00:42:35 The 15 Point Checklist for the Perfect Trailer 00:45:28 The Oz Pearlman Hook (41 Second Rule) 00:48:06 The Laughter Track Hack 00:54:11 Sound Design and Visual Details 00:57:04 How to Choose Music Like a Film Director 01:00:02 Disney Imagineering Lesson 01:02:46 The Vanessa Van Edwards Hook Breakdown 01:07:02 The Kevin Hart Narrative Arc Breakdown 01:16:40 The A-B-C Storytelling Framework 01:20:13 The Easiest Win You Can Implement Right Now 01:22:36 How Diary of a CEO Uses AI

Grant

206,702 views • 1 month ago

How GPT-5 thinks, with OpenAI VP of Research Jerry Tworek 00:00 - Intro 01:01 - What Reasoning Actually Means in AI 02:32 - Chain of Thought: Models Thinking in Words 05:25 - How Models Decide How Long to Think 07:24 - Evolution from o1 to o3 to GPT-5 11:00 - The Road to OpenAI: Growing up in Poland, Dropping out of School, Trading 20:32 - Working on Robotics and Rubik's Cube Solving 23:02 - A Day in the Life: Talking to Researchers 24:06 - How Research Priorities Are Determined 26:53 - OpenAI's Culture of Transparency 29:32 - Balancing Research with Shipping Fast 31:52 - Using OpenAI's Own Tools Daily 32:43 - Pre-Training Plus RL: The Modern AI Stack 35:10 - Reinforcement Learning 101: Training Dogs 40:17 - The Evolution of Deep Reinforcement Learning 42:09 - When GPT-4 Seemed Underwhelming at First 45:39 - How RLHF Made GPT-4 Actually Useful 48:02 - Unsupervised vs Supervised Learning 49:59 - GRPO and How DeepSeek Accelerated US Research 53:05 - What It Takes to Scale Reinforcement Learning 55:36 - Agentic AI and Long-Horizon Thinking 59:19 - Alignment as an RL Problem 1:01:11 - Winning ICPC World Finals Without Specific Training 1:05:53 - Applying RL Beyond Math and Coding 1:09:15 - The Path from Here to AGI 1:12:23 - Pure RL vs Language Models
1:16:04

How GPT-5 thinks, with OpenAI VP of Research Jerry Tworek 00:00 - Intro 01:01 - What Reasoning Actually Means in AI 02:32 - Chain of Thought: Models Thinking in Words 05:25 - How Models Decide How Long to Think 07:24 - Evolution from o1 to o3 to GPT-5 11:00 - The Road to OpenAI: Growing up in Poland, Dropping out of School, Trading 20:32 - Working on Robotics and Rubik's Cube Solving 23:02 - A Day in the Life: Talking to Researchers 24:06 - How Research Priorities Are Determined 26:53 - OpenAI's Culture of Transparency 29:32 - Balancing Research with Shipping Fast 31:52 - Using OpenAI's Own Tools Daily 32:43 - Pre-Training Plus RL: The Modern AI Stack 35:10 - Reinforcement Learning 101: Training Dogs 40:17 - The Evolution of Deep Reinforcement Learning 42:09 - When GPT-4 Seemed Underwhelming at First 45:39 - How RLHF Made GPT-4 Actually Useful 48:02 - Unsupervised vs Supervised Learning 49:59 - GRPO and How DeepSeek Accelerated US Research 53:05 - What It Takes to Scale Reinforcement Learning 55:36 - Agentic AI and Long-Horizon Thinking 59:19 - Alignment as an RL Problem 1:01:11 - Winning ICPC World Finals Without Specific Training 1:05:53 - Applying RL Beyond Math and Coding 1:09:15 - The Path from Here to AGI 1:12:23 - Pure RL vs Language Models

Matt Turck

451,229 views • 11 months ago

Top Performance Coach Jim Murphy (Jim Murphy) reveals how to quiet the mind and execute when it matters most. Jim spent 5 years writing Inner Excellence, the mental toughness manual that shot from obscurity to #1 New York Times bestseller overnight when star athlete A.J. Brown was caught reading it on the sidelines of an NFL playoff game. 00:00 Introduction 01:01 The 3 Pillars of Inner Excellence 04:14 A Manual on Mental Toughness 07:55 Goals are Secondary 11:53 Clean Fuel vs. Dirty Fuel 14:23 What You Want Most 16:26 Ad Break 18:41 The Achievement Treadmill 21:47 The Busy Trap 22:34 The Best Vacation 25:39 What's Your Purpose? 27:41 The Spiral of Isolation 31:09 The Key to Performance 34:00 The Courage to Be Disliked 35:55 What the Most Successful People Do 39:49 Redefine Success and Failure 41:43 Comparison & Envy 42:53 Individual Cost and Collective Gain 46:31 Talking to Your Kids About Mental Toughness 47:34 Discovering Your Inner Excellence (Where to Start) 51:25 Tension Between Achievement and Happiness 55:09 Dealing With Guilt 58:10 Knowledge vs. Wisdom 01:01:21 Changing Focus to Accomplish Goals 01:05:40 Using Automatic Rules 01:10:40 Daily Mantras for Success 01:12:15 Ambition or Love? 01:14:52 Train Your Mind 01:15:38 What Is Success? Out now wherever you listen to the knowledge project. Includes paid partnerships.
1:16:32

Top Performance Coach Jim Murphy (Jim Murphy) reveals how to quiet the mind and execute when it matters most. Jim spent 5 years writing Inner Excellence, the mental toughness manual that shot from obscurity to #1 New York Times bestseller overnight when star athlete A.J. Brown was caught reading it on the sidelines of an NFL playoff game. 00:00 Introduction 01:01 The 3 Pillars of Inner Excellence 04:14 A Manual on Mental Toughness 07:55 Goals are Secondary 11:53 Clean Fuel vs. Dirty Fuel 14:23 What You Want Most 16:26 Ad Break 18:41 The Achievement Treadmill 21:47 The Busy Trap 22:34 The Best Vacation 25:39 What's Your Purpose? 27:41 The Spiral of Isolation 31:09 The Key to Performance 34:00 The Courage to Be Disliked 35:55 What the Most Successful People Do 39:49 Redefine Success and Failure 41:43 Comparison & Envy 42:53 Individual Cost and Collective Gain 46:31 Talking to Your Kids About Mental Toughness 47:34 Discovering Your Inner Excellence (Where to Start) 51:25 Tension Between Achievement and Happiness 55:09 Dealing With Guilt 58:10 Knowledge vs. Wisdom 01:01:21 Changing Focus to Accomplish Goals 01:05:40 Using Automatic Rules 01:10:40 Daily Mantras for Success 01:12:15 Ambition or Love? 01:14:52 Train Your Mind 01:15:38 What Is Success? Out now wherever you listen to the knowledge project. Includes paid partnerships.

Shane Parrish

575,883 views • 9 months ago

Judea Pearl (Judea Pearl) is a Turing Award winner famous for his contributions to artificial intelligence and causal reasoning. We talked about the greatest scientist of all time, his major breakthroughs and his predictions for AI today. Full conversation also on my YouTube, Spotify, and Apple Podcasts. Timestamps: 00:00 Intro 00:54 How he got into AI 11:17 Greatest scientist of all time 20:15 What people thought of AI in the 80s 26:23 Entering academia and researching AI 34:52 The invention of Bayesian networks 46:28 Pioneering work in causality 55:38 The causal hierarchy 59:34 LLMs and predictions 01:20:12 A restless mind pays 01:24:36 Advice for his younger self 01:26:37 Outro
1:27:33

Judea Pearl (Judea Pearl) is a Turing Award winner famous for his contributions to artificial intelligence and causal reasoning. We talked about the greatest scientist of all time, his major breakthroughs and his predictions for AI today. Full conversation also on my YouTube, Spotify, and Apple Podcasts. Timestamps: 00:00 Intro 00:54 How he got into AI 11:17 Greatest scientist of all time 20:15 What people thought of AI in the 80s 26:23 Entering academia and researching AI 34:52 The invention of Bayesian networks 46:28 Pioneering work in causality 55:38 The causal hierarchy 59:34 LLMs and predictions 01:20:12 A restless mind pays 01:24:36 Advice for his younger self 01:26:37 Outro

Ryan Peterman

11,629 views • 1 month ago

Dianne Penn is Head of Product for Research and Labs at Anthropic. She joined in 2023 as their first technical PM (when there were just five product engineers) and has helped ship every Claude model from Claude 2 to Mythos. We discuss: 02:31 Early Anthropic 08:55 The two biggest inflections 13:50 Inside the exponential 20:02 Token maxing 23:30 Anthropic Labs and the incubation model 27:30 How the AI research role works 31:35 How to become a top AI researcher 35:18 Frontier model safeguards 39:38 Hiring in the AI era 44:16 Building evals 47:48 Evals are the new PRDs 49:55 The importance of hands-on leadership 52:46 Finding joy in AI 58:10 How Dianne uses Claude 01:01:05 Avoiding overreliance on AI 01:03:50 The constitution that makes Claude better 01:07:11 AI writing and verification 01:11:40 Where human brains will continue to be valuable 01:14:10 Navigating AI with kids 01:16:26 Alignment, the future of the PM role, and burnout 01:21:54 Lightning round and final thoughts
1:33:50

Dianne Penn is Head of Product for Research and Labs at Anthropic. She joined in 2023 as their first technical PM (when there were just five product engineers) and has helped ship every Claude model from Claude 2 to Mythos. We discuss: 02:31 Early Anthropic 08:55 The two biggest inflections 13:50 Inside the exponential 20:02 Token maxing 23:30 Anthropic Labs and the incubation model 27:30 How the AI research role works 31:35 How to become a top AI researcher 35:18 Frontier model safeguards 39:38 Hiring in the AI era 44:16 Building evals 47:48 Evals are the new PRDs 49:55 The importance of hands-on leadership 52:46 Finding joy in AI 58:10 How Dianne uses Claude 01:01:05 Avoiding overreliance on AI 01:03:50 The constitution that makes Claude better 01:07:11 AI writing and verification 01:11:40 Where human brains will continue to be valuable 01:14:10 Navigating AI with kids 01:16:26 Alignment, the future of the PM role, and burnout 01:21:54 Lightning round and final thoughts

Lenny Rachitsky

157,470 views • 1 month ago

In 2026, it's quite likely that a pill will hit the market which makes dogs live longer. This is a big deal for many reasons. The pill will come from Loyal and Celine Halioua. And they have more therapies in the pipeline. In this episode, we chat about Celine's life and career and Loyal's unique work in the longevity field. The Core Memory podcast - which makes people smarter - is brought to you by the finance wizards at Brex and the genius investors E1 Ventures 🇺🇸. Enjoy! Timestamps 00:00 – Intro 02:47 – Why Start With Dogs 06:05 – Aging Science Explained 09:12 – Inside FDA Trials 13:18 – Designing a Longevity Drug 17:42 – Metabolism and Aging 22:35 – Lessons From Biotech 26:48 – Building Loyal 31:54 – From Neuroscience to Founder 38:19 – GLP-1 vs Longevity Drugs 43:28 – Ethics of Longer Life 49:44 – What Dog Data Shows 54:59 – Longevity Hype & Peptides 59:47 – Biotech Needs Artists 01:05:20 – Investor Hype vs Reality 01:11:35 – AI in Drug Discovery 01:17:49 – Future of Aging Research 01:23:05 – Dogs and the End of Aging
1:29:44

In 2026, it's quite likely that a pill will hit the market which makes dogs live longer. This is a big deal for many reasons. The pill will come from Loyal and Celine Halioua. And they have more therapies in the pipeline. In this episode, we chat about Celine's life and career and Loyal's unique work in the longevity field. The Core Memory podcast - which makes people smarter - is brought to you by the finance wizards at Brex and the genius investors E1 Ventures 🇺🇸. Enjoy! Timestamps 00:00 – Intro 02:47 – Why Start With Dogs 06:05 – Aging Science Explained 09:12 – Inside FDA Trials 13:18 – Designing a Longevity Drug 17:42 – Metabolism and Aging 22:35 – Lessons From Biotech 26:48 – Building Loyal 31:54 – From Neuroscience to Founder 38:19 – GLP-1 vs Longevity Drugs 43:28 – Ethics of Longer Life 49:44 – What Dog Data Shows 54:59 – Longevity Hype & Peptides 59:47 – Biotech Needs Artists 01:05:20 – Investor Hype vs Reality 01:11:35 – AI in Drug Discovery 01:17:49 – Future of Aging Research 01:23:05 – Dogs and the End of Aging

Ashlee Vance

63,172 views • 10 months ago

Pierre Poilievre (Pierre Poilievre) shares his vision for making Canada the world's best place to build a life—with practical solutions for a more prosperous future. TKP is not a political podcast—and won't become one. I've invited both major party leaders to share their visions because I'm deeply concerned about how public discourse has degraded into angry soundbites. We've lost the ability to explore complex issues with patience and good faith. This conversation is my small effort to model what better dialogue might look like. (01:41) Headline vs Reality (03:55) From Opposition Party to Unifier (07:05) Parenthood Shapes Priorities (10:05) Differentiating from the Liberals (13:44) Economic Value Creation in Canada (16:48) WEF Opposition Stance (22:37) Opportunity Has Eroded (24:07) Balanced Budget Plan (26:55) Attracting Investments (34:05) Productivity Gap Explained (37:30) Tariffs Response Tactics (39:50) Reducing US Dependency (42:55) Interprovincial Trade Impacts (44:20) China (46:22) Media Accountability Challenges (50:22) Digital Free Speech Protections (53:50) Crime (01:00:40) Access to Health Care (01:04:55) A modern and effective Canadian military (01:09:50) AI: balance innovation with protection (01:12:50) Trust in government post-COVID (01:14:36) Climate change (01:17:30) Biggest misconceptions about him (01:18:30) What success for Canada looks like
1:19:26

Pierre Poilievre (Pierre Poilievre) shares his vision for making Canada the world's best place to build a life—with practical solutions for a more prosperous future. TKP is not a political podcast—and won't become one. I've invited both major party leaders to share their visions because I'm deeply concerned about how public discourse has degraded into angry soundbites. We've lost the ability to explore complex issues with patience and good faith. This conversation is my small effort to model what better dialogue might look like. (01:41) Headline vs Reality (03:55) From Opposition Party to Unifier (07:05) Parenthood Shapes Priorities (10:05) Differentiating from the Liberals (13:44) Economic Value Creation in Canada (16:48) WEF Opposition Stance (22:37) Opportunity Has Eroded (24:07) Balanced Budget Plan (26:55) Attracting Investments (34:05) Productivity Gap Explained (37:30) Tariffs Response Tactics (39:50) Reducing US Dependency (42:55) Interprovincial Trade Impacts (44:20) China (46:22) Media Accountability Challenges (50:22) Digital Free Speech Protections (53:50) Crime (01:00:40) Access to Health Care (01:04:55) A modern and effective Canadian military (01:09:50) AI: balance innovation with protection (01:12:50) Trust in government post-COVID (01:14:36) Climate change (01:17:30) Biggest misconceptions about him (01:18:30) What success for Canada looks like

Shane Parrish

847,180 views • 1 year ago

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

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

University of Austin (UATX)

27,770 views • 8 months ago