Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Ep35 - Hypernative Security Beyond the Audit ALEX RABKE ⚡️ and Joe Georgeou walked around the Fashion District with me in NYC talking about Real-Time Monitoring, Post-Audit Security, Institutional Traders, Hacks, Oracle Manipulation, Pre-Crime 00:00 - What is Hypernative? 00:35 - Why Audits Aren't Enough 00:50 - Beyond Security...

jarednotjerry's profile picture

Jared not Jerry

4,292 subscribers

23,330 Aufrufe • vor 9 Monaten •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

내가 보려고 모은 #조이 역대 브릿지 파트 모음.zip (Ice Cream Cake~Sweet Dreams) 💚 * 레드벨벳 앨범만 포함했습니다 00:00 Somethin Kinda Crazy 00:05 Take It Slow 00:13 사탕 (Candy) 00:20 Dumb Dumb 00:22 Campfire 00:31 Lady’s Room 00:33 Day 1 00:43 Coold World 00:51 My Dear 00:55 Bad Dracula 00:58 Happily Ever After 01:03 빨간 맛 (Red Flavor) 01:09 여름빛 (Mojito) 01:13 I Just 01:17 Kingdom Come 01:23 두 번째 데이트 (My Second Date) 01:27 Attaboy 01:36 Perfect 10 01:42 달빛소리 01:53 Bad Boy 01:59 Time To Love 02:09 #Cookie Jar 02:13 Aitai-tai 02:20 Power Up 02:23 한 여름의 크리스마스 (With You) 02:30 Mr.E 02:35 Mosquito 02:41 RBB (Really Bad Boy) 02:47 So Good 02:51 멋있게 (Sassy Me) 02:54 Swimming Pool 02:57 Sayonara 03:04 짐살라빔 (Zimzalabim) 03:12 Sunny Side Up! 03:16 Milkshake 03:21 친구가 아냐 (Bing Bing) 03:29 안녕, 여름 (Parade) 03:32 LP 03:41 음파음파 (Umpah Umpah) 03:48 카풀 (Carpool) 03:57 Love Is The Way 04:05 Jumpin’ 04:11 눈 맞추고, 손 맞대고 (Eyes Locked, Hand Locked) 04:17 Psycho 04:24 In & Out 04:34 Remember Forever 04:44 Milky Way 04:52 Queendom 05:00 Pose 05:07 Knock On Wood 05:15 Better Be 05:25 Feel My Rhythm 05:29 Rainbow Halo 05:36 Beg For Me 05:43 In My Dreams 05:48 Marionette 05:50 WILDSIDE 05:54 Jackpot 06:00 Snap Snap 06:08 ‘Cause it’s you 06:14 Color of Love 06:16 Birthday 06:19 BYE BYE 06:22 롤러코스터 (On A Ride) 06:29 Zoom 06:40 Celebrate 06:48 Chill Kill 06:56 Knock Knock (Who’s There?) 06:59 Nightmare 07:03 One Kiss 07:10 Wings 07:21 풍경화 (Scenery) 07:32 Sunflower 07:38 Love Arcade 07:44 Bubble 07:51 Night Drive 07:57 Sweet Dreams
8:06

내가 보려고 모은 #조이 역대 브릿지 파트 모음.zip (Ice Cream Cake~Sweet Dreams) 💚 * 레드벨벳 앨범만 포함했습니다 00:00 Somethin Kinda Crazy 00:05 Take It Slow 00:13 사탕 (Candy) 00:20 Dumb Dumb 00:22 Campfire 00:31 Lady’s Room 00:33 Day 1 00:43 Coold World 00:51 My Dear 00:55 Bad Dracula 00:58 Happily Ever After 01:03 빨간 맛 (Red Flavor) 01:09 여름빛 (Mojito) 01:13 I Just 01:17 Kingdom Come 01:23 두 번째 데이트 (My Second Date) 01:27 Attaboy 01:36 Perfect 10 01:42 달빛소리 01:53 Bad Boy 01:59 Time To Love 02:09 #Cookie Jar 02:13 Aitai-tai 02:20 Power Up 02:23 한 여름의 크리스마스 (With You) 02:30 Mr.E 02:35 Mosquito 02:41 RBB (Really Bad Boy) 02:47 So Good 02:51 멋있게 (Sassy Me) 02:54 Swimming Pool 02:57 Sayonara 03:04 짐살라빔 (Zimzalabim) 03:12 Sunny Side Up! 03:16 Milkshake 03:21 친구가 아냐 (Bing Bing) 03:29 안녕, 여름 (Parade) 03:32 LP 03:41 음파음파 (Umpah Umpah) 03:48 카풀 (Carpool) 03:57 Love Is The Way 04:05 Jumpin’ 04:11 눈 맞추고, 손 맞대고 (Eyes Locked, Hand Locked) 04:17 Psycho 04:24 In & Out 04:34 Remember Forever 04:44 Milky Way 04:52 Queendom 05:00 Pose 05:07 Knock On Wood 05:15 Better Be 05:25 Feel My Rhythm 05:29 Rainbow Halo 05:36 Beg For Me 05:43 In My Dreams 05:48 Marionette 05:50 WILDSIDE 05:54 Jackpot 06:00 Snap Snap 06:08 ‘Cause it’s you 06:14 Color of Love 06:16 Birthday 06:19 BYE BYE 06:22 롤러코스터 (On A Ride) 06:29 Zoom 06:40 Celebrate 06:48 Chill Kill 06:56 Knock Knock (Who’s There?) 06:59 Nightmare 07:03 One Kiss 07:10 Wings 07:21 풍경화 (Scenery) 07:32 Sunflower 07:38 Love Arcade 07:44 Bubble 07:51 Night Drive 07:57 Sweet Dreams

맑음쨩 🍏

20,678 Aufrufe • vor 1 Jahr

Risk isn't just about numbers: it's about understanding what breaks first. Carson Brown breaks down how risk really works in DeFi and why liquidity concentration is more dangerous than people think. On the latest episode of Blueprints, Carson sits down with Edgar of Symbiotic to discuss the evolution of shared security, institutional risk appetite, and how stablecoins are reshaping the space. Topics discussed in this episode: - 00:00 Introduction - 03:35 Rapid Fire Q&A - 05:05 Carson's Path into Crypto - 09:03 Inside Gauntlet's Restaking Team - 16:27 The Overlooked Risk Metric - 24:34 Would TVL Survive Without Incentives? - 27:26 Evolution of Shared Security - 37:07 Stablecoin Staking Insights - 46:10 Balancing Growth and Trust Watch the latest episode of Blueprints:
53:29

Risk isn't just about numbers: it's about understanding what breaks first. Carson Brown breaks down how risk really works in DeFi and why liquidity concentration is more dangerous than people think. On the latest episode of Blueprints, Carson sits down with Edgar of Symbiotic to discuss the evolution of shared security, institutional risk appetite, and how stablecoins are reshaping the space. Topics discussed in this episode: - 00:00 Introduction - 03:35 Rapid Fire Q&A - 05:05 Carson's Path into Crypto - 09:03 Inside Gauntlet's Restaking Team - 16:27 The Overlooked Risk Metric - 24:34 Would TVL Survive Without Incentives? - 27:26 Evolution of Shared Security - 37:07 Stablecoin Staking Insights - 46:10 Balancing Growth and Trust Watch the latest episode of Blueprints:

Symbiotic

11,928 Aufrufe • vor 11 Monaten

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

205,444 Aufrufe • vor 26 Tagen

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks
1:15:17

This week on The Knowledge Project: A rare interview with Bruce Flatt, the quiet force behind 19% annual returns for 30 years, reveals the investment principles that transformed Brookfield into a $1T global powerhouse. "Our view always has been 'Buy the best.' Own the best, buy the best; continue to reinvest into the best." (00:00:54) Changes in Investing Over the Past 25 Years (00:02:50) How Private Enterprise Has Built Our Tech Infrastructure (00:05:07) Implications and Opportunities of Passive Investing (00:14:40) AI (00:19:39) Transition to Low-Carbon Energy (00:23:19) Future of Data Centers (00:25:28) De-globalization of Industry (00:27:55) Implications of Manufacturing Repatriation (00:29:06) Long-term Prospects for America (00:31:35) Changes in Real Estate (00:34:13) Approach to Risk and Debt (00:38:40) Managing Market Dislocations (00:40:22) Long-term Investing Strategy (00:42:59) History and Future of Brookfield (00:45:48) Exploration of Private Markets and Insurance (00:46:41) Investment Decision Process (00:48:34) Introduction to Annuities (00:53:10) Understanding Brookfield’s Structure (01:00:51) Focus on Downside Protection (01:02:56) Accountability in Investment Decisions (01:04:24) Understanding Investment Cycles (01:06:59) Postmortem Analysis of Investments (01:09:07) Consideration of Geopolitical Risks

The Knowledge Project

453,197 Aufrufe • vor 1 Jahr

Dr. Jordan Peterson: How to Best Guide Your Life Decisions & Path Dr Jordan B Peterson This Huberman Lab episode is available in full on X, YouTube and all podcast platforms. (00:00:00) Dr. Jordan Peterson (00:02:32) Sponsors: David & Levels (00:05:19) Brain, Impulses, Integration, Personalities (00:14:08) Personalities, Motivation (00:18:18) Context & Children; Religion, Motivation & Personality (00:24:08) Hypothalamus, Context, Maturation (00:29:46) Psychopathy, Kids & Aggressive Behavior & Socialization (00:33:37) Polytheistic & Monotheistic Religions; Rage, Sociopathy & Addiction (00:41:05) Sponsors: AG1 & ROKA (00:43:58) Belief in God, Addiction (00:50:34) Pornography, Dopamine, Processed Foods (00:56:20) Clean Diet, Satiety; Fundamental Pleasures, Food, Sexuality (01:04:44) Power, Target, Sin (01:06:46) Sponsor: Function (01:08:33) Abraham; Call to Adventure, Success, Respect, Community (01:21:30) Wisdom, Noah; Religion, Incentive Structure & Motivation (01:26:52) Dopamine & Target, Sin; Frontal Eye Fields (01:31:59) Meta-Target & Goals, Sermon on the Mount; Fears (01:40:36) Sponsor: LMNT (01:41:51) Ultimate vs. Local Victory, Pearl of Great Price (01:45:05) Time Scales & Rewards; Entropy, Dopamine & Goals (01:51:20) Pornography, Effortless Gratification; Revelation & Sexuality Demise (02:02:33) Adventure & Responsibility, Sacrifice; Tool: Ordering Room (02:12:02) Storytelling, Science, Career Advancement, Pursuing Truth (02:23:46) Abraham & Adventure; Purposeful Satisfaction, Podcast (02:28:13) Finding Your Calling, Tools: Calling & Conscience; Creating Order (02:35:06) Order vs. Chaos; Public Shootings, Narcissism (02:40:16) Long-Term Goals, Pursuit, Curiosity, Commitment (02:45:43) Finding Purpose, Tool: Fixing Messes; Conscience & Voice of Divine (02:54:26) Prayer, Aim, Revelation; Thought (03:00:34) Religion, Common Themes (03:10:55) Psychoanalytical Traditions; Play (03:19:23) Play; Humor, Discourse, Alternative Media (03:27:18) Democrats, Republicans; Fear & Growth (03:34:59) Tour, Peterson Academy, YouTube, Cancel Culture (03:48:30) Zero-Cost Support, YouTube, Spotify & Apple Follow & Reviews, Sponsors, YouTube Feedback, Protocols Book, Social Media, Neural Network Newsletter Includes paid partnerships.
3:51:10

Dr. Jordan Peterson: How to Best Guide Your Life Decisions & Path Dr Jordan B Peterson This Huberman Lab episode is available in full on X, YouTube and all podcast platforms. (00:00:00) Dr. Jordan Peterson (00:02:32) Sponsors: David & Levels (00:05:19) Brain, Impulses, Integration, Personalities (00:14:08) Personalities, Motivation (00:18:18) Context & Children; Religion, Motivation & Personality (00:24:08) Hypothalamus, Context, Maturation (00:29:46) Psychopathy, Kids & Aggressive Behavior & Socialization (00:33:37) Polytheistic & Monotheistic Religions; Rage, Sociopathy & Addiction (00:41:05) Sponsors: AG1 & ROKA (00:43:58) Belief in God, Addiction (00:50:34) Pornography, Dopamine, Processed Foods (00:56:20) Clean Diet, Satiety; Fundamental Pleasures, Food, Sexuality (01:04:44) Power, Target, Sin (01:06:46) Sponsor: Function (01:08:33) Abraham; Call to Adventure, Success, Respect, Community (01:21:30) Wisdom, Noah; Religion, Incentive Structure & Motivation (01:26:52) Dopamine & Target, Sin; Frontal Eye Fields (01:31:59) Meta-Target & Goals, Sermon on the Mount; Fears (01:40:36) Sponsor: LMNT (01:41:51) Ultimate vs. Local Victory, Pearl of Great Price (01:45:05) Time Scales & Rewards; Entropy, Dopamine & Goals (01:51:20) Pornography, Effortless Gratification; Revelation & Sexuality Demise (02:02:33) Adventure & Responsibility, Sacrifice; Tool: Ordering Room (02:12:02) Storytelling, Science, Career Advancement, Pursuing Truth (02:23:46) Abraham & Adventure; Purposeful Satisfaction, Podcast (02:28:13) Finding Your Calling, Tools: Calling & Conscience; Creating Order (02:35:06) Order vs. Chaos; Public Shootings, Narcissism (02:40:16) Long-Term Goals, Pursuit, Curiosity, Commitment (02:45:43) Finding Purpose, Tool: Fixing Messes; Conscience & Voice of Divine (02:54:26) Prayer, Aim, Revelation; Thought (03:00:34) Religion, Common Themes (03:10:55) Psychoanalytical Traditions; Play (03:19:23) Play; Humor, Discourse, Alternative Media (03:27:18) Democrats, Republicans; Fear & Growth (03:34:59) Tour, Peterson Academy, YouTube, Cancel Culture (03:48:30) Zero-Cost Support, YouTube, Spotify & Apple Follow & Reviews, Sponsors, YouTube Feedback, Protocols Book, Social Media, Neural Network Newsletter Includes paid partnerships.

Andrew D. Huberman, Ph.D.

668,694 Aufrufe • vor 1 Jahr

Ethereum's biggest catalyst isn't another ETF. It's demand. Joseph Lubin says the next wave won't come from traders; it'll come from AI agents, tokenized assets, stablecoins, and institutions settling trillions onchain. If that plays out, today's price looks very different in a few years. FT John Gillen - WartimeEthereum.eth Joseph Chalom Sharplink Tune in to know more ⏱ TIME POINTS ⏱ 00:00 - Intro 01:21 – Why SharpLink Bought More ETH 03:06 – Surviving the Crypto Bear 05:35 – Russell Index Milestone 08:28 – SharpLink's DeFi Strategy 14:39 – Fiduciary Duty Explained 18:07 – ETH Labs Explained 24:02 – ETH Labs Priorities 30:12 – ETH Institutional vs. Etherealize 34:03 – Can Ethereum's New Orgs Win? 38:26 – Sponsor: Securitize 39:04 – Sponsor: Bitget 39:36 – Ethereum vs. Legacy Finance 45:44 – Ethereum's Future Governance 46:57 – SharpLink vs. Bitmine? 50:07 – 1 Million Ethereum Developers 51:30 – Glamsterdam Upgrade 56:44 – Why ETH Gains Value 01:02:59 – Measuring Ethereum's Success 01:08:03 – Wrap-Up
1:09:09

Ethereum's biggest catalyst isn't another ETF. It's demand. Joseph Lubin says the next wave won't come from traders; it'll come from AI agents, tokenized assets, stablecoins, and institutions settling trillions onchain. If that plays out, today's price looks very different in a few years. FT John Gillen - WartimeEthereum.eth Joseph Chalom Sharplink Tune in to know more ⏱ TIME POINTS ⏱ 00:00 - Intro 01:21 – Why SharpLink Bought More ETH 03:06 – Surviving the Crypto Bear 05:35 – Russell Index Milestone 08:28 – SharpLink's DeFi Strategy 14:39 – Fiduciary Duty Explained 18:07 – ETH Labs Explained 24:02 – ETH Labs Priorities 30:12 – ETH Institutional vs. Etherealize 34:03 – Can Ethereum's New Orgs Win? 38:26 – Sponsor: Securitize 39:04 – Sponsor: Bitget 39:36 – Ethereum vs. Legacy Finance 45:44 – Ethereum's Future Governance 46:57 – SharpLink vs. Bitmine? 50:07 – 1 Million Ethereum Developers 51:30 – Glamsterdam Upgrade 56:44 – Why ETH Gains Value 01:02:59 – Measuring Ethereum's Success 01:08:03 – Wrap-Up

Milk Road

30,324 Aufrufe • vor 1 Monat

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead
1:09:53

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead

Raoul Pal

172,640 Aufrufe • vor 1 Jahr

We don't know what most microbial genes do. Can genomic language models help? there's only one way to find out! this is a 1 hour and 42 minute interview with an MIT professor (the famous Yunha Hwang) chatting about these questions, her work in solving them at Tatta Bio, and more. zoomer captions are back too Links in reply! Timestamps: 00:00:00 - Clips + sponsor roll from the wonderful LatchBio 00:02:07 – Introduction 00:02:23 – Why do microbial genomes matter 00:04:07 – Deep learning acceptance in metagenomics 00:05:25 – The case for genomic “context” over sequence matching 00:06:43 – OMG: the only ML-ready metagenomic dataset 00:09:27 – gLM2: A multimodal genomic language model 00:11:06 – What do you do with the output of genomic language models? 00:17:41 – How will OMG evolve? 00:20:26 – Why train on only microbial genomes, as opposed to all genomes? 00:22:58 – Do we need more sequences or more annotations? 00:23:54 – Is there a conserved microbial genome ‘language’? 00:28:11 – What non-obvious things can this genomic language model tell you? 00:33:08 – Semantic deduplication and evaluation 00:37:33 – How does benchmarking work for these types of models? 00:41:31 – Gaia: A genomic search engine 00:44:18 – Even ‘well-studied’ genomes are mostly unannotated 00:50:51 – Using agents on Gaia 00:54:53 – Will genomic language models reshape the tree of life? 00:59:18 – Current limitations of genomic language models 01:08:54 – Directed evolution as training data 01:12:35 – What is Tatta Bio? 01:19:02 – Building Google for genomic sequences (SeqHub) 01:25:46 – How to create communities around scientific OSS 01:29:06 – What’s the purpose in the centralization of the software? 01:35:37 – How will the way science is done change in 10 years?
1:42:41

We don't know what most microbial genes do. Can genomic language models help? there's only one way to find out! this is a 1 hour and 42 minute interview with an MIT professor (the famous Yunha Hwang) chatting about these questions, her work in solving them at Tatta Bio, and more. zoomer captions are back too Links in reply! Timestamps: 00:00:00 - Clips + sponsor roll from the wonderful LatchBio 00:02:07 – Introduction 00:02:23 – Why do microbial genomes matter 00:04:07 – Deep learning acceptance in metagenomics 00:05:25 – The case for genomic “context” over sequence matching 00:06:43 – OMG: the only ML-ready metagenomic dataset 00:09:27 – gLM2: A multimodal genomic language model 00:11:06 – What do you do with the output of genomic language models? 00:17:41 – How will OMG evolve? 00:20:26 – Why train on only microbial genomes, as opposed to all genomes? 00:22:58 – Do we need more sequences or more annotations? 00:23:54 – Is there a conserved microbial genome ‘language’? 00:28:11 – What non-obvious things can this genomic language model tell you? 00:33:08 – Semantic deduplication and evaluation 00:37:33 – How does benchmarking work for these types of models? 00:41:31 – Gaia: A genomic search engine 00:44:18 – Even ‘well-studied’ genomes are mostly unannotated 00:50:51 – Using agents on Gaia 00:54:53 – Will genomic language models reshape the tree of life? 00:59:18 – Current limitations of genomic language models 01:08:54 – Directed evolution as training data 01:12:35 – What is Tatta Bio? 01:19:02 – Building Google for genomic sequences (SeqHub) 01:25:46 – How to create communities around scientific OSS 01:29:06 – What’s the purpose in the centralization of the software? 01:35:37 – How will the way science is done change in 10 years?

owl

44,279 Aufrufe • vor 8 Monaten

Running Through Ethereum with hamdi (Ep. 1) I started craic overflow because I had questions about where Ethereum is headed, and I wanted to ask them to the people shaping it. I decided to interview Hamdi while jogging because as a software engineer, I honestly spend way too much time sitting on my ass. Never been more bullish on the future of Ethereum. 00:00 - Intro 00:08 - Hamdi 00:40 - What's The Craic? 01:59 - How did Hamdi get into crypto? 02:40 - Why not plasma? 03:24 - Working at OP Labs/Optimism 04:06 - Shipping L2 Interoperability 05:12 - Building on the Superchain 05:30 - Asynchronicity in Solidity 07:00 - Predications for Ethereum 08:46 - What are the hurdles for Ethereum? 09:47 - Stablecoins 10:22 - Application specific chains 11:53 - Wallet UX 13:18 - Quick breather 13:30 - Why are you in crypto? 14:20 - How do you find balance? 16:20 - Hot take on ETH the asset 17:39 - The chains security 18:53 - Market talk 19:45 - Data availability 21:01 - Onchain L2 configs 21:22 - Outro
21:34

Running Through Ethereum with hamdi (Ep. 1) I started craic overflow because I had questions about where Ethereum is headed, and I wanted to ask them to the people shaping it. I decided to interview Hamdi while jogging because as a software engineer, I honestly spend way too much time sitting on my ass. Never been more bullish on the future of Ethereum. 00:00 - Intro 00:08 - Hamdi 00:40 - What's The Craic? 01:59 - How did Hamdi get into crypto? 02:40 - Why not plasma? 03:24 - Working at OP Labs/Optimism 04:06 - Shipping L2 Interoperability 05:12 - Building on the Superchain 05:30 - Asynchronicity in Solidity 07:00 - Predications for Ethereum 08:46 - What are the hurdles for Ethereum? 09:47 - Stablecoins 10:22 - Application specific chains 11:53 - Wallet UX 13:18 - Quick breather 13:30 - Why are you in crypto? 14:20 - How do you find balance? 16:20 - Hot take on ETH the asset 17:39 - The chains security 18:53 - Market talk 19:45 - Data availability 21:01 - Onchain L2 configs 21:22 - Outro

malone

11,924 Aufrufe • vor 1 Jahr

ARC-AGI is redefining how to measure progress on the path to AGI - focusing on reasoning, generalization, and adaptability instead of memorization or scale. At NeurIPS 2025, YC's Diana sat down with ARC Prize President Greg Kamradt to find out why most AI benchmarks fail, how ARC-AGI reveals the limits of today’s models, and why measuring intelligence may be harder than building it. 00:11 — What ARC Prize is and why it exists 00:38 — François Chollet’s definition of AGI 01:48 — What ARC-AGI Actually Tests 02:25 — When LLMs Failed the ARC Benchmark 03:38 — ARC-AGI Becomes the Standard 04:49 — False Positives in AI Progress 06:06 — The Evolution of ARC-AGI 08:55 — Measuring Intelligence beyond just accuracy 10:25 — What happens if a model solves ARC-AGI?
11:59

ARC-AGI is redefining how to measure progress on the path to AGI - focusing on reasoning, generalization, and adaptability instead of memorization or scale. At NeurIPS 2025, YC's Diana sat down with ARC Prize President Greg Kamradt to find out why most AI benchmarks fail, how ARC-AGI reveals the limits of today’s models, and why measuring intelligence may be harder than building it. 00:11 — What ARC Prize is and why it exists 00:38 — François Chollet’s definition of AGI 01:48 — What ARC-AGI Actually Tests 02:25 — When LLMs Failed the ARC Benchmark 03:38 — ARC-AGI Becomes the Standard 04:49 — False Positives in AI Progress 06:06 — The Evolution of ARC-AGI 08:55 — Measuring Intelligence beyond just accuracy 10:25 — What happens if a model solves ARC-AGI?

Y Combinator

98,369 Aufrufe • vor 8 Monaten

Yoshua Bengio thinks he knows how to make provably safe superintelligent agents. Bengio built the foundations of modern AI and is the most cited living scientist. He believes his alternative training setup would: 1. Guarantee honesty 2. Prevent unintended goals 3. Produce capable agents 4. Port over most data and techniques from current LLMs 5. Not be inherently more expensive, and perhaps be more intelligent Bengio claims the honesty and lack of unintended goals can be proven mathematically, at least given particular assumptions. And his new organization, LawZero, is aiming to build a scrappy prototype as soon as possible. The architecture is called 'Scientist AI' and it's based on training a model to explain empirical observations, including what people say, rather than training AIs that mimic human behaviour or seek our approval. (Bengio's frank assessment is that "reinforcement learning is evil" and that allowing AIs to independently train their successors is "the most crazy, dangerous bet that unfortunately we are on track to do.") But skeptics question whether Scientist AI really does solve the fundamental problem of 'eliciting latent knowledge' from AI models. And with the commercial race for superintelligence so intense, it's not clear whether the proposal will be able to compete or have time to bear fruit, even if it's sound in theory. On The 80,000 Hours Podcast, links below – enjoy! • Making AI honest and safe (00:00:00) • Scientist AI in plain English (00:02:27) • How Scientist AI differs from LLMs (00:06:32) • How the training data works (00:14:02) • Can this become an agent? (00:21:02) • Why Yoshua is now more optimistic (00:32:11) • Why companies can’t stop racing (00:36:35) • A working prototype won't take long (00:49:15) • Scientist models might be more capable (00:53:34) • “Reinforcement learning is evil” (01:01:27) • Scientist AI from guardrail to agent (01:08:37) • Can safe AI still be competent? (01:12:38) • How much will this cost? (01:19:29) • Can it generalise beyond maths and science? (01:23:26) • A multi-national push for superintelligence (01:39:19) • Want to work with or fund Yoshua? (01:51:16) • Why smart people ignore AI risk (01:54:45) • Don’t let AI build the next AI (02:01:33) • Why politicians miss the real risks (02:12:28) • Why Yoshua changed his mind about AI risk (02:21:27)
2:35:26

Yoshua Bengio thinks he knows how to make provably safe superintelligent agents. Bengio built the foundations of modern AI and is the most cited living scientist. He believes his alternative training setup would: 1. Guarantee honesty 2. Prevent unintended goals 3. Produce capable agents 4. Port over most data and techniques from current LLMs 5. Not be inherently more expensive, and perhaps be more intelligent Bengio claims the honesty and lack of unintended goals can be proven mathematically, at least given particular assumptions. And his new organization, LawZero, is aiming to build a scrappy prototype as soon as possible. The architecture is called 'Scientist AI' and it's based on training a model to explain empirical observations, including what people say, rather than training AIs that mimic human behaviour or seek our approval. (Bengio's frank assessment is that "reinforcement learning is evil" and that allowing AIs to independently train their successors is "the most crazy, dangerous bet that unfortunately we are on track to do.") But skeptics question whether Scientist AI really does solve the fundamental problem of 'eliciting latent knowledge' from AI models. And with the commercial race for superintelligence so intense, it's not clear whether the proposal will be able to compete or have time to bear fruit, even if it's sound in theory. On The 80,000 Hours Podcast, links below – enjoy! • Making AI honest and safe (00:00:00) • Scientist AI in plain English (00:02:27) • How Scientist AI differs from LLMs (00:06:32) • How the training data works (00:14:02) • Can this become an agent? (00:21:02) • Why Yoshua is now more optimistic (00:32:11) • Why companies can’t stop racing (00:36:35) • A working prototype won't take long (00:49:15) • Scientist models might be more capable (00:53:34) • “Reinforcement learning is evil” (01:01:27) • Scientist AI from guardrail to agent (01:08:37) • Can safe AI still be competent? (01:12:38) • How much will this cost? (01:19:29) • Can it generalise beyond maths and science? (01:23:26) • A multi-national push for superintelligence (01:39:19) • Want to work with or fund Yoshua? (01:51:16) • Why smart people ignore AI risk (01:54:45) • Don’t let AI build the next AI (02:01:33) • Why politicians miss the real risks (02:12:28) • Why Yoshua changed his mind about AI risk (02:21:27)

Rob Wiblin

65,088 Aufrufe • vor 3 Monaten

🚨 PARTNERSHIP INTERVIEW: TON EX-PRESIDENT ON TELEGRAM’S PAVEL DUROV, THE FUTURE OF CRYPTO, AND WHY TON COULD HIT $1 TRILLION. He is the largest investor in Animoca, largest investor in TON, and one of crypto’s biggest whales A friend of Telegram’s Pavel Durov, Manuel Stotz stepped down as the President of TON Blockchain (launched by Telegram) to launch the world’s first TON Digital Asset Treasury. What Michael Saylor did with Bitcoin, and Tom Lee did with ETH, Manny is doing with TON. We discuss: – Why the 40-year debt supercycle is ending – Why central banks want you to believe inflation is temporary – Why fiat is “a bug in the system, not a feature” – Why TON, with its Telegram integration, is the most underrated trillion-dollar blockchain opportunity – Why billionaires are quietly buying Bitcoin In his view, the game is rigged and it’s time to play accordingly. 00:00 – TON partners with Telegram and Pavel Durov’s vision revealed. 02:00 – Manny Stotz explains why TON is crypto’s most underrated project. 04:30 – The insane story of Telegram: one billion users, zero funding. 07:00 – How Manny became President of TON Foundation. 09:30 – Pavel Durov: the GOAT of social media and free speech. 12:00 – Telegram’s shocking truth: only one product manager, Pavel himself. 15:00 – The secret genius of Nikolai Durov and TON’s whitepaper. 18:00 – VK vs Facebook: how the Durov brothers crushed Silicon Valley. 21:00 – “I’m not your lapdog, Mr. Putin”: Pavel’s bold stand against the FSB. 24:00 – How Telegram was born under surveillance and raids. 27:00 – Building Telegram in exile: Dubai, freedom and TON’s future. 30:00 – Why TON’s partnership with Telegram could change crypto forever. 34:00 – France investigates Pavel Durov: the West vs free speech. 38:00 – Did EU intelligence ask Durov to censor Romanian elections? 42:00 – Pavel posts explosive revelations while under investigation. 46:00 – The fight for freedom of speech at the core of TON and Telegram. 50:00 – Manny Stotz on Animoca, blockchain gaming and TON dominance. 54:00 – How TON serves the unbanked in Africa, Asia and Latin America. 58:00 – Billion-dollar crypto adoption: TON, Bitcoin, Solana and beyond. 01:02:00 – The dark side of fiat: hyperinflation from Zimbabwe to Venezuela. 01:06:00 – Why TON is positioned to lead the next crypto cycle. 01:10:00 – Manny compares Pavel Durov to Elon Musk’s vision. 01:14:00 – How governments fear TON’s unstoppable growth. 01:18:00 – The future of TON: global freedom, finance and innovation. 01:22:00 – Final verdict: Why Pavel Durov and TON may reshape the internet.
1:14:05

🚨 PARTNERSHIP INTERVIEW: TON EX-PRESIDENT ON TELEGRAM’S PAVEL DUROV, THE FUTURE OF CRYPTO, AND WHY TON COULD HIT $1 TRILLION. He is the largest investor in Animoca, largest investor in TON, and one of crypto’s biggest whales A friend of Telegram’s Pavel Durov, Manuel Stotz stepped down as the President of TON Blockchain (launched by Telegram) to launch the world’s first TON Digital Asset Treasury. What Michael Saylor did with Bitcoin, and Tom Lee did with ETH, Manny is doing with TON. We discuss: – Why the 40-year debt supercycle is ending – Why central banks want you to believe inflation is temporary – Why fiat is “a bug in the system, not a feature” – Why TON, with its Telegram integration, is the most underrated trillion-dollar blockchain opportunity – Why billionaires are quietly buying Bitcoin In his view, the game is rigged and it’s time to play accordingly. 00:00 – TON partners with Telegram and Pavel Durov’s vision revealed. 02:00 – Manny Stotz explains why TON is crypto’s most underrated project. 04:30 – The insane story of Telegram: one billion users, zero funding. 07:00 – How Manny became President of TON Foundation. 09:30 – Pavel Durov: the GOAT of social media and free speech. 12:00 – Telegram’s shocking truth: only one product manager, Pavel himself. 15:00 – The secret genius of Nikolai Durov and TON’s whitepaper. 18:00 – VK vs Facebook: how the Durov brothers crushed Silicon Valley. 21:00 – “I’m not your lapdog, Mr. Putin”: Pavel’s bold stand against the FSB. 24:00 – How Telegram was born under surveillance and raids. 27:00 – Building Telegram in exile: Dubai, freedom and TON’s future. 30:00 – Why TON’s partnership with Telegram could change crypto forever. 34:00 – France investigates Pavel Durov: the West vs free speech. 38:00 – Did EU intelligence ask Durov to censor Romanian elections? 42:00 – Pavel posts explosive revelations while under investigation. 46:00 – The fight for freedom of speech at the core of TON and Telegram. 50:00 – Manny Stotz on Animoca, blockchain gaming and TON dominance. 54:00 – How TON serves the unbanked in Africa, Asia and Latin America. 58:00 – Billion-dollar crypto adoption: TON, Bitcoin, Solana and beyond. 01:02:00 – The dark side of fiat: hyperinflation from Zimbabwe to Venezuela. 01:06:00 – Why TON is positioned to lead the next crypto cycle. 01:10:00 – Manny compares Pavel Durov to Elon Musk’s vision. 01:14:00 – How governments fear TON’s unstoppable growth. 01:18:00 – The future of TON: global freedom, finance and innovation. 01:22:00 – Final verdict: Why Pavel Durov and TON may reshape the internet.

Mario Nawfal

1,017,537 Aufrufe • vor 1 Jahr

Aidan Gomez (Aidan Gomez) is a computer scientist, co-author of the seminal paper ‘Attention Is All You Need,’ and the CEO of Cohere. In this episode, we discussed his upbringing in the cabin his grandfather built in Codrington, a small town North of Brighton, and the values that were instilled in him through his family. We explored his path from Codrington to his undergraduate studies at the University of Toronto, emailing Geoffrey Hinton, and joining Google Brain where he co-wrote the paper on transformers. We discussed how he met his co-founders Ivan Zhang and Nick Frosst, and his insights on what it means to build a meaningful, successful company in Canada. Aidan shares his conviction about what is at stake — for Canada and for the world at large. This is a conversation about family, values, and what it means to live with conviction. The Other Stuff is hosted by internetVin — filmmaker, entrepreneur, and possibly the most curious man on Earth. Produced by New. The Other Stuff #29 — Aidan Gomez: Empathy and Conviction — Timestamps 00:00:00 Intro 00:03:10 The Malleability of Toronto 00:11:06 Growing Up in Codrington 00:13:50 The Story of Aidan Gomez’s Family 00:27:23 Introduction to the Internet 00:30:39 Values and Work Ethic 00:35:46 University of Toronto’s AI Scene 00:40:48 Emailing Geoffrey Hinton 00:42:16 Google Brain 00:45:15 Dropout: A Simple Way to Prevent Neural Networks from Overfitting 00:49:48 The Beauty of Research 00:54:24 One Model to Rule Them All 00:59:54 Meeting Ivan Zhang and Nick Frosst 01:04:00 The Birth of Cohere 01:06:56 Twitter Influencers and Alex Friedland 01:11:48 Being the CEO 01:12:51 Building for Canada 01:15:01 Three Fundamental Ingredients of Building a Company 01:21:39 Working with the Canadian Government 01:24:39 Reflexivity in Canada 01:36:22 What Is Evil? 01:42:40 The Role of AI in the World
1:46:27

Aidan Gomez (Aidan Gomez) is a computer scientist, co-author of the seminal paper ‘Attention Is All You Need,’ and the CEO of Cohere. In this episode, we discussed his upbringing in the cabin his grandfather built in Codrington, a small town North of Brighton, and the values that were instilled in him through his family. We explored his path from Codrington to his undergraduate studies at the University of Toronto, emailing Geoffrey Hinton, and joining Google Brain where he co-wrote the paper on transformers. We discussed how he met his co-founders Ivan Zhang and Nick Frosst, and his insights on what it means to build a meaningful, successful company in Canada. Aidan shares his conviction about what is at stake — for Canada and for the world at large. This is a conversation about family, values, and what it means to live with conviction. The Other Stuff is hosted by internetVin — filmmaker, entrepreneur, and possibly the most curious man on Earth. Produced by New. The Other Stuff #29 — Aidan Gomez: Empathy and Conviction — Timestamps 00:00:00 Intro 00:03:10 The Malleability of Toronto 00:11:06 Growing Up in Codrington 00:13:50 The Story of Aidan Gomez’s Family 00:27:23 Introduction to the Internet 00:30:39 Values and Work Ethic 00:35:46 University of Toronto’s AI Scene 00:40:48 Emailing Geoffrey Hinton 00:42:16 Google Brain 00:45:15 Dropout: A Simple Way to Prevent Neural Networks from Overfitting 00:49:48 The Beauty of Research 00:54:24 One Model to Rule Them All 00:59:54 Meeting Ivan Zhang and Nick Frosst 01:04:00 The Birth of Cohere 01:06:56 Twitter Influencers and Alex Friedland 01:11:48 Being the CEO 01:12:51 Building for Canada 01:15:01 Three Fundamental Ingredients of Building a Company 01:21:39 Working with the Canadian Government 01:24:39 Reflexivity in Canada 01:36:22 What Is Evil? 01:42:40 The Role of AI in the World

The Other Stuff Podcast

45,297 Aufrufe • vor 8 Monaten

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
1:16:39

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

33,195 Aufrufe • vor 3 Monaten

EXCLUSIVE: Inside Tether’s KPMG Audit: Gold Bars, Bitcoin, and $6B in Excess Equity Tether CEO Paolo Ardoino joins The Starting Block to unpack details of their KPMG US audit. Ardoino explains how Tether finally cleared the biggest hurdle in the room with a Big Four audit from KPMG US, why the timing mattered, and what the new yearly audit plus quarterly attestations mean for the company and the industry. Timestamps 00:00 - Paolo Ardoino joins to discuss Tether’s Big Four audit announcement 01:16 - Why the audit took years and what made it possible now 03:31 - Why Tether chose KPMG US after earlier controversy around attestations 04:58 - Yearly audits and quarterly attestations as a transparency standard 05:15 - Responding to critics who still question Tether’s transparency 06:36 - The 7 billion redemption stress test in 2022 07:57 - Why auditors counted gold bars in Tether’s reserves 08:40 - Tether’s gold and Bitcoin reserve holdings 09:23 - The private fundraising narrative and why Tether says it does not need capital 12:31 - Tether’s AI effort, Qvac, and the mission to serve the unbanked 14:59 - Supporting Bitcoin security work after the Coldcard exploit 16:52 - Confirming annual audits and quarterly attestations going forward
15:13

EXCLUSIVE: Inside Tether’s KPMG Audit: Gold Bars, Bitcoin, and $6B in Excess Equity Tether CEO Paolo Ardoino joins The Starting Block to unpack details of their KPMG US audit. Ardoino explains how Tether finally cleared the biggest hurdle in the room with a Big Four audit from KPMG US, why the timing mattered, and what the new yearly audit plus quarterly attestations mean for the company and the industry. Timestamps 00:00 - Paolo Ardoino joins to discuss Tether’s Big Four audit announcement 01:16 - Why the audit took years and what made it possible now 03:31 - Why Tether chose KPMG US after earlier controversy around attestations 04:58 - Yearly audits and quarterly attestations as a transparency standard 05:15 - Responding to critics who still question Tether’s transparency 06:36 - The 7 billion redemption stress test in 2022 07:57 - Why auditors counted gold bars in Tether’s reserves 08:40 - Tether’s gold and Bitcoin reserve holdings 09:23 - The private fundraising narrative and why Tether says it does not need capital 12:31 - Tether’s AI effort, Qvac, and the mission to serve the unbanked 14:59 - Supporting Bitcoin security work after the Coldcard exploit 16:52 - Confirming annual audits and quarterly attestations going forward

The Block

66,216 Aufrufe • vor 13 Tagen

Ep38 - MoreMarkets Unlocking Yield for Idle Assets cofounder MoreMarkets walked around Central Park with me in NYC talking about XRP, Ripple Swell, projects pivoting, DeFi yield, TradFi, founder life, and a lot more! 00:00 - What is MoreMarkets? 00:44 - Why Isn't Tokenized Gold Bigger? 01:15 - The Hard Life of a Founder 02:11 - #1 Founder Advice: "Don't get scared of pivoting" 03:30 - What is the XRP Community Really Like? 04:30 - Ripple's Big TradFi Moves (Citadel, Acquisitions) 05:58 - Ripple: From "Meme" to "Real" 07:43 - Why Crypto Was More Interesting Than AI 08:24 - MoreMarkets' Launch: 8-9M Cap Filled Fast 10:15 - The Future: A Decentralized "Everything App" 10:52 - Shout out to NEAR Intents 14:59 - The Simple Pitch to XRP Holders 17:00 - Learning to Pivot while walking Times Square 18:20 - The Vision: A Decentralized "Everything App" I met Altan while we were working at NEAR and have been so stoked to see his growth as a founder!
19:06

Ep38 - MoreMarkets Unlocking Yield for Idle Assets cofounder MoreMarkets walked around Central Park with me in NYC talking about XRP, Ripple Swell, projects pivoting, DeFi yield, TradFi, founder life, and a lot more! 00:00 - What is MoreMarkets? 00:44 - Why Isn't Tokenized Gold Bigger? 01:15 - The Hard Life of a Founder 02:11 - #1 Founder Advice: "Don't get scared of pivoting" 03:30 - What is the XRP Community Really Like? 04:30 - Ripple's Big TradFi Moves (Citadel, Acquisitions) 05:58 - Ripple: From "Meme" to "Real" 07:43 - Why Crypto Was More Interesting Than AI 08:24 - MoreMarkets' Launch: 8-9M Cap Filled Fast 10:15 - The Future: A Decentralized "Everything App" 10:52 - Shout out to NEAR Intents 14:59 - The Simple Pitch to XRP Holders 17:00 - Learning to Pivot while walking Times Square 18:20 - The Vision: A Decentralized "Everything App" I met Altan while we were working at NEAR and have been so stoked to see his growth as a founder!

Jared

27,632 Aufrufe • vor 9 Monaten

New episode with Dr. Konrad Kording (Kording Lab 🦖), professor of bioengineering and neuroscience at the University of Pennsylvania (Penn) and co-director of CIFAR's Learning in Machines & Brains program (CIFAR). Konrad works at the intersection of causality, machine learning, and neuroscience, building rigorous methods for causal reasoning when experiments aren't possible — and challenging how researchers interpret neural data and build AI. Konrad argues the most promising path to understanding how the brain works is to read the brain’s wiring directly, down to the molecular detail of each connection, and to build compilers and simulations to understand the brain’s computation directly. In this episode we go deep into how neurons work, how neurons wire together, and how organic and artificial neural networks differ. We discuss why organic neurons are doing much more; how a model of a single organic neuron can solve MNIST — computing more like a 3-layer artificial neural network; how the brain might learn by solving credit assignment with only local signals; how to approximate backprop without a global algorithm; why AI and humans are intelligent along different dimensions; why Konrad isn’t very worried about AI replacing us; economic models of intelligence and physical work; and much more. Konrad is a brilliant, contrarian thinker who explains complex concepts very intuitively. It is a solid computational neuroscience primer. I hope you enjoy this conversation as much as I did! Other links to this episode and references below. Chapters 00:00:00 Introduction 00:01:01 How organic neurons work 00:24:13 How the brain learns: circuits and credit assignment 00:45:29 Recording the brain 00:52:47 Why simulating brains is hard 01:05:00 A new approach: connectomes and compilers 01:21:00 Why simulate brains? 01:29:50 How AI and human intelligence differ 01:41:04 Evolution, intelligence and AI risk 01:52:42 Robotics, causality, and the roots of intelligence 02:05:53 AI for science and scientific rigor 02:13:05 The economics of intelligence 02:27:50 A hopeful future
2:29:40

New episode with Dr. Konrad Kording (Kording Lab 🦖), professor of bioengineering and neuroscience at the University of Pennsylvania (Penn) and co-director of CIFAR's Learning in Machines & Brains program (CIFAR). Konrad works at the intersection of causality, machine learning, and neuroscience, building rigorous methods for causal reasoning when experiments aren't possible — and challenging how researchers interpret neural data and build AI. Konrad argues the most promising path to understanding how the brain works is to read the brain’s wiring directly, down to the molecular detail of each connection, and to build compilers and simulations to understand the brain’s computation directly. In this episode we go deep into how neurons work, how neurons wire together, and how organic and artificial neural networks differ. We discuss why organic neurons are doing much more; how a model of a single organic neuron can solve MNIST — computing more like a 3-layer artificial neural network; how the brain might learn by solving credit assignment with only local signals; how to approximate backprop without a global algorithm; why AI and humans are intelligent along different dimensions; why Konrad isn’t very worried about AI replacing us; economic models of intelligence and physical work; and much more. Konrad is a brilliant, contrarian thinker who explains complex concepts very intuitively. It is a solid computational neuroscience primer. I hope you enjoy this conversation as much as I did! Other links to this episode and references below. Chapters 00:00:00 Introduction 00:01:01 How organic neurons work 00:24:13 How the brain learns: circuits and credit assignment 00:45:29 Recording the brain 00:52:47 Why simulating brains is hard 01:05:00 A new approach: connectomes and compilers 01:21:00 Why simulate brains? 01:29:50 How AI and human intelligence differ 01:41:04 Evolution, intelligence and AI risk 01:52:42 Robotics, causality, and the roots of intelligence 02:05:53 AI for science and scientific rigor 02:13:05 The economics of intelligence 02:27:50 A hopeful future

Juan Benet

50,121 Aufrufe • vor 2 Monaten

NEW EPISODE WITH Peter Attia Can we age more slowly and evade or forestall the diseases of aging? In today’s episode, the brilliant Peter Attia equips us with some of his favorite strategies and tools designed to delay or potentially prevent cardiovascular disease, cancer, and Alzheimer’s disease, aiming to preserve health, longevity, and ultimately win the ‘centenarian olympics.’ TIMESTAMPS: (00:08:02) What is cholesterol? (00:15:03) Why ApoB is a superior predictor of cardiovascular disease over LDL particle number (00:33:31) Whether there’s an ApoB level low enough that it’s impossible to die from atherosclerosis (00:37:20) Which dietary factors increase ApoB (00:51:04) Whether or not low LDL is a risk for cancer – and a variety of other surprising facts about LDL biology you really can’t find anywhere else (00:56:52) How statins and other lipid-lowering pharmacotherapies work, including their side effects and costs (01:23:51) Statin alternatives pros & cons: PCSK9 inhibitors, ezetimibe, & bempedoic acid (01:36:35) How increased muscle mass helps achieve lower blood sugar levels – reducing overall mortality – and the potential for suboptimal glycemic control long before doctors identify it (01:52:28) Peter’s 80% zone 2 / 20% VO2 max training protocol (02:08:08) The danger of visceral fat and why it correlates with increased cancer risk (02:12:03) Benefits & risks of aggressive cancer screening (02:24:49) Recommended mammogram & ultrasound frequency for women (02:31:41) Radiation from CT scans & mammograms (02:37:27) Menopause (hormonal changes, hot flashes, sexual changes, & bone loss) & hormone replacement therapy (02:59:57) How hormone replacement affects dementia, cancer, & heart disease risk in women (03:05:35) Vitamin D: Sunlight vs. supplements & optimal levels (03:23:01) Is it safe for a woman who’s 10 years post-menopause to do HRT? (03:21:45) Why symptoms of low testosterone are often more important than the actual levels when deciding whether or not to go on TRT (03:28:07) Why Peter’s recommended TRT dosing schedule differs from the standard (03:37:00) Methods for lowering blood pressure: exercise, nitrates, hot tubs, & cocoa flavanols (03:49:44) Peter’s exercise, sleep, nutrition, & alcohol routines for optimizing longevity You can find Dr. Peter Attia's book "Outlive: The Science and Art of Longevity” here: Full episode available on YouTube and where ever podcasts can be downloaded:
3:00:10

NEW EPISODE WITH Peter Attia Can we age more slowly and evade or forestall the diseases of aging? In today’s episode, the brilliant Peter Attia equips us with some of his favorite strategies and tools designed to delay or potentially prevent cardiovascular disease, cancer, and Alzheimer’s disease, aiming to preserve health, longevity, and ultimately win the ‘centenarian olympics.’ TIMESTAMPS: (00:08:02) What is cholesterol? (00:15:03) Why ApoB is a superior predictor of cardiovascular disease over LDL particle number (00:33:31) Whether there’s an ApoB level low enough that it’s impossible to die from atherosclerosis (00:37:20) Which dietary factors increase ApoB (00:51:04) Whether or not low LDL is a risk for cancer – and a variety of other surprising facts about LDL biology you really can’t find anywhere else (00:56:52) How statins and other lipid-lowering pharmacotherapies work, including their side effects and costs (01:23:51) Statin alternatives pros & cons: PCSK9 inhibitors, ezetimibe, & bempedoic acid (01:36:35) How increased muscle mass helps achieve lower blood sugar levels – reducing overall mortality – and the potential for suboptimal glycemic control long before doctors identify it (01:52:28) Peter’s 80% zone 2 / 20% VO2 max training protocol (02:08:08) The danger of visceral fat and why it correlates with increased cancer risk (02:12:03) Benefits & risks of aggressive cancer screening (02:24:49) Recommended mammogram & ultrasound frequency for women (02:31:41) Radiation from CT scans & mammograms (02:37:27) Menopause (hormonal changes, hot flashes, sexual changes, & bone loss) & hormone replacement therapy (02:59:57) How hormone replacement affects dementia, cancer, & heart disease risk in women (03:05:35) Vitamin D: Sunlight vs. supplements & optimal levels (03:23:01) Is it safe for a woman who’s 10 years post-menopause to do HRT? (03:21:45) Why symptoms of low testosterone are often more important than the actual levels when deciding whether or not to go on TRT (03:28:07) Why Peter’s recommended TRT dosing schedule differs from the standard (03:37:00) Methods for lowering blood pressure: exercise, nitrates, hot tubs, & cocoa flavanols (03:49:44) Peter’s exercise, sleep, nutrition, & alcohol routines for optimizing longevity You can find Dr. Peter Attia's book "Outlive: The Science and Art of Longevity” here: Full episode available on YouTube and where ever podcasts can be downloaded:

Dr. Rhonda Patrick

340,320 Aufrufe • vor 2 Jahren

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:
1:11:41

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:

Shane Parrish

450,952 Aufrufe • vor 4 Monaten