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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 views • 9 months ago •via X (Twitter)

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Shane Parrish

450,952 views • 4 months ago

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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sarah guo

3,040,848 views • 5 months ago

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11,297 views • 1 year ago

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18,008 views • 13 days ago

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49,150 views • 1 year ago

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Delphi Digital

21,214 views • 2 months ago

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

sarah guo

12,341 views • 2 months ago

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Bg2 Pod

87,806 views • 2 years ago

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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Bg2 Pod

487,379 views • 1 year ago

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 views • 2 years ago

🚨 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?

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

Matt Turck

75,091 views • 16 days ago

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

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American Optimist

417,594 views • 6 months ago

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

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

Anjney Midha

79,532 views • 4 months ago

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 views • 5 months ago

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 views • 4 months ago

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 views • 27 days ago