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Interview with Jay Parikh, EVP of CoreAI Microsoft 00:00 - Intro 00:25 - Microsoft's Core AI Team 05:08 - In-Person Work Culture 10:15 - How AI Changes Engineering Roles 15:24 - Data Centers & Power Constraints 19:00 - AI Bubble & Dark GPUs 22:34 - Model efficiency 25:17 -... show more

Matthew Berman

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40,712 просмотров • 9 месяцев назад •via X (Twitter)

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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:

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:

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Caught up with Andrej Karpathy for a new No Priors: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects 02:55 - What Capability Limits Remain? 06:15 - What Mastery of Coding Agents Looks Like 11:16 - Second Order Effects of Coding Agents 15:51 - Why AutoResearch 22:45 - Relevant Skills in the AI Era 28:25 - Model Speciation 32:30 - Collaboration Surfaces for Humans and AI 37:28 - Analysis of Jobs Market Data 48:25 - Open vs. Closed Source Models 53:51 - Autonomous Robotics and Atoms 1:00:59 - MicroGPT and Agentic Education 1:05:40 - End Thoughts

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Engineers need to communicate effectively when building AI Systems. These terms will help you use a shared vocabulary. This is useful when discussing concepts, reading papers, or collaborating with teammates. Listed in order. 00:00 Agenda 00:28 1. Large Language Model 01:28 2. Tokenization 02:53 3. Vectorization 04:15 4. Attention 07:22 5. Self-Supervised Learning 12:07 6. Transformer 14:32 7. Fine-tuning 17:05 8. Few-shot Prompting 18:11 9. Retrieval Augmented Generation 20:33 10. Vector Database 23:03 11. Model Context Protocol 25:43 12. Context Engineering 28:17 13. Agents 29:19 14. Reinforcement Learning 34:42 15. Chain of Thought 35:55 16. Reasoning Models 36:36 17. Multi-modal Models 38:21 18. Small Language Models 40:24 19. Distillation 41:47 20. Quantization If you are a software engineer looking to transition to AI, click the link below. AI Engineering Course: #AI #SoftwareEngineering #Agents

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.Satya Nadella on: - why he doesn’t believe in AGI but does believe in 10% economic growth - Microsoft’s new topological qubit breakthrough and gaming world models - whether Office commoditizes LLMs or the other way around Links below. Enjoy! Timestamps 0:00:00 - Intro 0:05:48 - AI won't be winner-take-all 0:16:02 - World economy growing by 10% 0:22:23 - Decreasing price of intelligence 0:31:03 - Microsoft's Quantum breakthrough 0:43:35 - Microsoft's gaming world model 0:50:35 - Legal barriers to AI 0:56:30 - Getting AGI safety right 1:05:43 - 34 years at Microsoft 1:11:31 - Does Satya Nadella believe in AGI?

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

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My interview with Amazon Web Services CEO Matt Garman. 0:00 Intro 0:57 White Collar Jobs 8:51 How much of AWS's code is written by AI? 12:54 How to have a career in the AI era 15:43 AI Bottlenecks 18:06 Inference vs Training Growth 20:05 AWS Custom Silicon 25:50 Annapurna Acquisition 27:53 AI Models 33:35 Open vs Closed Models 41:28 Benchmarks 47:13 Agents

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A New Episode of the Hivemind is Live! This week Tommy joins us to debate whether AI frontier companies can justify their valuations, the rise of open-source AI, and where enterprise spending is actually going. We also cover SpaceX’s IPO, Hyperliquid’s growth, and the latest around Zcash’s private Bitcoin thesis. Timestamps: 00:00 Introduction & Market Outlook 05:00 OpenAI, Anthropic & Enterprise AI Spending 08:53 Open Source vs Frontier Models 24:41 Are We In An AI Bubble? 35:17 SpaceX IPO & Equity Issuance 38:13 AI Regulation & Political Risk 53:36 Hyperliquid & HYPE 1:04:14 Zcash & The Private Bitcoin Thesis 1:13:16 Final Thoughts

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Delphi Digital

21,214 просмотров • 2 месяцев назад

ICYMI, full No Priors discussion at Microsoft Build with Satya Nadella 01:48 – Reflections from Microsoft Build, ecosystem 03:12 – MAI Training, Model Strategy 05:48 – Complexity of Real-World Deployment of AI 07:33 – Augmenting Human Capital 09:37 – Harnesses for Enterprise 11:49 – Value Capture By Developers 15:09 – Can Everybody Operate at the Frontier? 15:51 – The Definition of IP in 2026 17:38 – Vendor vs. Enterprise Agents 21:48 – Predictions on Model Pricing 24:02 – Durability of SaaS, SaaSpocalypse 25:58 – What Satya’s Coding Himself 28:18 – Future of Engineering 30:54 – How Microsoft Can Be More Ambitious? 34:36 – Data Centers and Community Impact 38:01 – AI’s Impact on Society 39:52 - AI and Education

ICYMI, full No Priors discussion at Microsoft Build with Satya Nadella 01:48 – Reflections from Microsoft Build, ecosystem 03:12 – MAI Training, Model Strategy 05:48 – Complexity of Real-World Deployment of AI 07:33 – Augmenting Human Capital 09:37 – Harnesses for Enterprise 11:49 – Value Capture By Developers 15:09 – Can Everybody Operate at the Frontier? 15:51 – The Definition of IP in 2026 17:38 – Vendor vs. Enterprise Agents 21:48 – Predictions on Model Pricing 24:02 – Durability of SaaS, SaaSpocalypse 25:58 – What Satya’s Coding Himself 28:18 – Future of Engineering 30:54 – How Microsoft Can Be More Ambitious? 34:36 – Data Centers and Community Impact 38:01 – AI’s Impact on Society 39:52 - AI and Education

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12,341 просмотров • 2 месяцев назад

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BG2. Ep 17. Double $NVDA! System Level Comp Moat, “Insane Demand”, Inference Explosion 1 B x, Memphis Supercluster, OpenAI, & more. Brad Gerstner Clark Tang Bill Gurley (00:00) Intro (1:50) The Evolution of AGI and Personal Assistants (06:03) NVIDIA's Competitive Moat (15:51 ) The Future of Inference and Training in AI (19:01) Building the AI Infrastructure (31:35) Inventing a New Market in an AI Future (38:40) The Impact of OpenAI (43:25) The Future of AI Models (46.44) and Memphis Supercluster (51:21) Distributed Computing and Inference Scaling (55:54) Inference Time Reasoning and Its Importance (01:00:46) AI's Role in Growing Business and Improving Productivity (01:08:00) Ensuring Safe AI Development (01:12:31) The Balance of Open Source and Closed Source AI

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Exclusive: Meta just released Llama 3.1 405B — the first-ever open-sourced frontier AI model, beating top closed models like GPT-4o across several benchmarks. I sat down with Mark Zuckerberg, diving into why this marks a major moment in AI history. Timestamps: 00:00 Intro 00:38 Meta’s Llama 3.1 rundown 03:44 Real-world use cases for Llama 3.1 06:15 Educating developers on open-source AI tools 09:43 Societal implications of open-source AI 13:00 Balancing power and managing bad actors 14:40 Open source and global competition 16:59 Accelerating innovation and economic growth 20:04 Zuck on Apple and lessons from the past 24:22 Future of AI: Llama 3 and beyond 26:43 Prediction: Billions of personalized AI agents 31:32 Factors to changing anti-AI sentiment

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Rowan Cheung

2,657,430 просмотров • 2 лет назад

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

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Matt Turck

75,091 просмотров • 16 дней назад

EPISODE 142: Understanding the AI Wave Joe Lonsdale sits down with 8VC Partners Alex Kolicich & Jack Moshkovich Why is AI fundamentally disruptive? What does it mean for large software incumbents? Will LLMs become commodities? And are we entering a bubble, or just getting started? (00:00) Episode intro (01:40) Smart enterprise thesis (04:00) Did enterprise software dramatically boost productivity? (08:30) Understanding the AI wave (11:45) Will LLMs become commodities? (17:10) OpenAI vs Anthropic vs Meta vs Grok (20:30) Frontier models vs enterprise incumbents (25:27) What did Palantir get right? (32:30) AI case studies/new possibilities (43:00) The most surprising aspect of the AI wave (46:12) Are we entering a bubble? Or just getting started? (52:40) Biggest concern with AI (58:00) Biggest reason for optimism

EPISODE 142: Understanding the AI Wave Joe Lonsdale sits down with 8VC Partners Alex Kolicich & Jack Moshkovich Why is AI fundamentally disruptive? What does it mean for large software incumbents? Will LLMs become commodities? And are we entering a bubble, or just getting started? (00:00) Episode intro (01:40) Smart enterprise thesis (04:00) Did enterprise software dramatically boost productivity? (08:30) Understanding the AI wave (11:45) Will LLMs become commodities? (17:10) OpenAI vs Anthropic vs Meta vs Grok (20:30) Frontier models vs enterprise incumbents (25:27) What did Palantir get right? (32:30) AI case studies/new possibilities (43:00) The most surprising aspect of the AI wave (46:12) Are we entering a bubble? Or just getting started? (52:40) Biggest concern with AI (58:00) Biggest reason for optimism

American Optimist

417,594 просмотров • 6 месяцев назад

Stanford '26, Session 3 (Full lecture) The Future of Voice Systems with @matiii from ElevenLabs 00:00 Welcome and Intro 01:31 Origin Story on Discord 05:15 The Dubbing Problem 07:44 Pipeline and Early Pivot 12:38 Building the First Model 15:24 Compute Costs and Patents 17:34 Roadmap Through 2025 22:00 Cascaded vs Fused Agents 30:38 Collaboration Over Competition 35:05 Revenue Growth and Team Design 37:56 Predictable Deployment Engine 42:32 Voice Safety and Watermarking 44:27 Research Bottlenecks Personalization 46:24 Training Tradeoffs Cascade vs Fuse 48:20 Five Year Vision Platform 51:08 Impact Work ALS and Ukraine 54:40 China Distillation and Openness 59:24 Studios AI Voice Economics 01:03:04 On Device Models and Platform Gap 01:04:36 Enterprise Tooling and Wrap Up

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Anjney Midha

79,532 просмотров • 4 месяцев назад

SPECIAL: How Erik Voorhees Built the Leading Private, Uncensored AI Venice Timestamps: 00:00 Intro & ShapeShift Origin Story 05:25 Did Crypto Play Out as Expected? 06:25 AI vs. Crypto: Are They Similar? 07:23 What Is Venice AI? 09:38 From ShapeShift to Venice 10:31 Censorship in AI & the Open Source Alternative 11:38 Hibachi, infiniFi Ads 12:00 Are AI Labs Too Censored? 13:24 Relay Ad 13:41 Geopolitics: Chinese Open Source vs. US Closed Models 14:15 SBF, the Anthropic Investment & Crypto Scammers 16:26 NearCon, Illia & the AI/Crypto Convergence

SPECIAL: How Erik Voorhees Built the Leading Private, Uncensored AI Venice Timestamps: 00:00 Intro & ShapeShift Origin Story 05:25 Did Crypto Play Out as Expected? 06:25 AI vs. Crypto: Are They Similar? 07:23 What Is Venice AI? 09:38 From ShapeShift to Venice 10:31 Censorship in AI & the Open Source Alternative 11:38 Hibachi, infiniFi Ads 12:00 Are AI Labs Too Censored? 13:24 Relay Ad 13:41 Geopolitics: Chinese Open Source vs. US Closed Models 14:15 SBF, the Anthropic Investment & Crypto Scammers 16:26 NearCon, Illia & the AI/Crypto Convergence

The Rollup

47,718 просмотров • 5 месяцев назад

More good News for Intel, AI Model Trends, Future of Datacenter With Ben Bajarin and Jay Goldberg 顾忠南 Chapters (00:00) Intel's New Partnership with Tesla (03:02) Market Reactions and Implications for Intel (05:53) Google's Collaboration with Intel (08:56) The Semiconductor Market Dynamics (12:06) Valuation Discrepancies in the Semiconductor Sector (14:59) Deep Dive into Semiconductor Supply Chains (17:56) Future of Data Centers and Energy Efficiency (22:38) The Evolution of Data Center Design (31:24) AI's Impact on Software and Productivity (39:10) Token Usage and Efficiency in AI (42:35) Cost Dynamics in the Semiconductor Industry

More good News for Intel, AI Model Trends, Future of Datacenter With Ben Bajarin and Jay Goldberg 顾忠南 Chapters (00:00) Intel's New Partnership with Tesla (03:02) Market Reactions and Implications for Intel (05:53) Google's Collaboration with Intel (08:56) The Semiconductor Market Dynamics (12:06) Valuation Discrepancies in the Semiconductor Sector (14:59) Deep Dive into Semiconductor Supply Chains (17:56) Future of Data Centers and Energy Efficiency (22:38) The Evolution of Data Center Design (31:24) AI's Impact on Software and Productivity (39:10) Token Usage and Efficiency in AI (42:35) Cost Dynamics in the Semiconductor Industry

The Circuit

17,871 просмотров • 4 месяцев назад

New pod with the legend Dan Ives is live! We break down the AI trade, including Chinese open-source models, Anthropic's slowing revenue growth, the biggest bottlenecks in chips, memory, and energy, and the political battles over data centers. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 0:51 - Chinese vs American open-source models, & the Anthropic IP lawsuit 4:36 - Falling model costs and the pricing war 5:55 - Cultural bias baked into Chinese AI models? 7:44 - Will AI models eat the whole stack? 11:20 - Specialized AI workflows & model routing 14:00 - Mag 7 free cash flow vs. exploding semiconductor revenue 17:37 - The real AI bottlenecks: memory chips, data centers & energy 30:13 - Anthropic's revenue growth is slowing — should investors worry? 31:17 - Why Dan is leaving Wall Street to build Yorkville Ives 34:32 - Dan's AI market predictions & closing thoughts

New pod with the legend Dan Ives is live! We break down the AI trade, including Chinese open-source models, Anthropic's slowing revenue growth, the biggest bottlenecks in chips, memory, and energy, and the political battles over data centers. YouTube: Spotify: Apple: TIMESTAMPS: 0:00 - Intro 0:51 - Chinese vs American open-source models, & the Anthropic IP lawsuit 4:36 - Falling model costs and the pricing war 5:55 - Cultural bias baked into Chinese AI models? 7:44 - Will AI models eat the whole stack? 11:20 - Specialized AI workflows & model routing 14:00 - Mag 7 free cash flow vs. exploding semiconductor revenue 17:37 - The real AI bottlenecks: memory chips, data centers & energy 30:13 - Anthropic's revenue growth is slowing — should investors worry? 31:17 - Why Dan is leaving Wall Street to build Yorkville Ives 34:32 - Dan's AI market predictions & closing thoughts

Anthony Pompliano 🌪

86,547 просмотров • 27 дней назад