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2025 was the year AI stopped feeling chaotic and started feeling buildable. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down the surprises of the year, from shifting model dominance to why the real opportunity is moving back to the application layer, and why...

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Y Combinator

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102,635 görüntüleme • 6 ay önce •via X (Twitter)

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Happy New Year! In this mini-episode of the Lightcone Podcast, hosts Garry Tan, Harj Taggar, Jared Friedman, and Diana ring in 2025 with their predictions for startups, AI, crypto, and more.
7:02

Happy New Year! In this mini-episode of the Lightcone Podcast, hosts Garry Tan, Harj Taggar, Jared Friedman, and Diana ring in 2025 with their predictions for startups, AI, crypto, and more.

Y Combinator

31,984 görüntüleme • 1 yıl önce

Anthropic Co-Founder Tom Brown: Why Anthropic Models Are The Best at Coding "The benchmarks are so easy to game. All the other big AI labs have teams whose job it is to make the benchmark scores good. We don't have such a team. That is the biggest factor." Anthropic's Tom Brown on Y Combinator's Lightcone Podcast with Garry Tan, Harj Taggar, Diana, and Jared Friedman
1:20

Anthropic Co-Founder Tom Brown: Why Anthropic Models Are The Best at Coding "The benchmarks are so easy to game. All the other big AI labs have teams whose job it is to make the benchmark scores good. We don't have such a team. That is the biggest factor." Anthropic's Tom Brown on Y Combinator's Lightcone Podcast with Garry Tan, Harj Taggar, Diana, and Jared Friedman

Overlap: Business & Tech

62,964 görüntüleme • 11 ay önce

MIT's new State of AI in Business report went viral for claiming that 95% of enterprise AI projects fail. But the real story isn't that AI doesn't work — it's just big companies can't build it. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down what the study really says, why in-house enterprise AI efforts keep stalling, and how startups are filling the gap with products that learn, integrate, and actually deliver value. 2:08 - The enterprise AI adoption gap and why the failure rate is high 3:32 - Even Apple can be bad at software 4:30 - Why getting enterprise software to actually work is so hard 11:08 - The Reducto case study 13:39 - The type of enterprise employee you should find as a founder 14:39 - Meet founders who’ve been acquired by enterprises 15:25 - Enterprise/startup tension and symbiosis
21:43

MIT's new State of AI in Business report went viral for claiming that 95% of enterprise AI projects fail. But the real story isn't that AI doesn't work — it's just big companies can't build it. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down what the study really says, why in-house enterprise AI efforts keep stalling, and how startups are filling the gap with products that learn, integrate, and actually deliver value. 2:08 - The enterprise AI adoption gap and why the failure rate is high 3:32 - Even Apple can be bad at software 4:30 - Why getting enterprise software to actually work is so hard 11:08 - The Reducto case study 13:39 - The type of enterprise employee you should find as a founder 14:39 - Meet founders who’ve been acquired by enterprises 15:25 - Enterprise/startup tension and symbiosis

Y Combinator

118,663 görüntüleme • 8 ay önce

Where are all the consumer AI apps??? This is the question I posed to s-tier consumer investors scott belsky (Uber, Pinterest) and steve jang (Coinbase, Postmates). We're almost 3 years into the AI hype the we're still all mostly just talking about ChatGPT, Perplexity, and Claude. We explore the answer through the ways in which the entire consumer stack (input, memory, personalization, browsers, hardware) are being re-written by AI and how that may give birth to the consumer opportunity we've all been waiting for. Chapters: 00:00 Welcome and Introductions 00:43 The Current State of AI Products 02:48 Surprises and Challenges with LLMs 05:24 Future of Consumer AI and Personal AI 15:49 Memory and Personalization in AI 21:52 Potential Risks and Business Models 24:22 The Battle for User Data in AI 25:11 Optimism in AI Model Inference 27:00 The Role of Open Source Models 28:13 The Future of AI Hardware 28:54 Challenges and Opportunities in AI Hardware Startups 30:29 The Evolution of Consumer Hardware 38:36 The Reinvention of Browsers 46:23 The Potential of AI-Enhanced Browsers 47:54 Conclusion and Final Thoughts Many thanks to my good friends for joining me in this discussion 🙏
45:47

Where are all the consumer AI apps??? This is the question I posed to s-tier consumer investors scott belsky (Uber, Pinterest) and steve jang (Coinbase, Postmates). We're almost 3 years into the AI hype the we're still all mostly just talking about ChatGPT, Perplexity, and Claude. We explore the answer through the ways in which the entire consumer stack (input, memory, personalization, browsers, hardware) are being re-written by AI and how that may give birth to the consumer opportunity we've all been waiting for. Chapters: 00:00 Welcome and Introductions 00:43 The Current State of AI Products 02:48 Surprises and Challenges with LLMs 05:24 Future of Consumer AI and Personal AI 15:49 Memory and Personalization in AI 21:52 Potential Risks and Business Models 24:22 The Battle for User Data in AI 25:11 Optimism in AI Model Inference 27:00 The Role of Open Source Models 28:13 The Future of AI Hardware 28:54 Challenges and Opportunities in AI Hardware Startups 30:29 The Evolution of Consumer Hardware 38:36 The Reinvention of Browsers 46:23 The Potential of AI-Enhanced Browsers 47:54 Conclusion and Final Thoughts Many thanks to my good friends for joining me in this discussion 🙏

Michael Mignano

25,155 görüntüleme • 1 yıl önce

Another mindblowing conversation with my good friend .Emad... Enjoy!! 00:00 - Introduction 00:22 - AI: The Biggest Shift in Human History 00:42 - AI’s Impact on Society and the Economy 01:03 - Conversation with Emad Mostaque Begins 01:50 - The Acceleration of AI and Economic Takeoff 03:07 - AI Intelligence: Beyond Human IQ 04:08 - The Rise of AI Chefs and Super Cooks 05:07 - Breaking AI Constraints: Compute and Energy 07:03 - The Future of AI: Ubiquitous Intelligence 08:04 - The Shift to Local AI Models 10:07 - Why Has Apple Lagged in AI? 11:21 - The AI Race: OpenAI, Grok, Gemini, and More 13:11 - China’s Open-Source AI Strategy 14:57 - AI Bias and Ethical Challenges 16:57 - AI’s Cross-Pollination and Memory 18:02 - Are AI Models Becoming Self-Aware? 19:16 - AI, Bitcoin, and Self-Sustaining Algorithms 21:26 - AI-Driven Economies and Autonomous Companies 23:41 - The Future of Labor: A World Without Jobs? 25:26 - AI-Powered Robots: The Next Workforce Revolution 27:28 - The End of Traditional Economic Models 30:27 - The Political Shift: Humanist vs. Transhumanist 33:04 - AI in Financial Markets: The End of Human Traders? 36:03 - The Evolution of Investing in an AI World 38:33 - AI’s Impact on Capital Formation and Business Disruption 40:01 - The Rise of Digital Twins and Post-Capital Society 42:45 - Building AI for Education, Healthcare, and Governance 46:42 - The Future of Money in an AI-Driven World 50:11 - Universal Basic AI: A New Economic Model 54:29 - The Deflationary Impact of AI and Crypto’s Role 57:02 - The AI Singularity: Five Years Until Everything Changes 58:56 - The Road Ahead: AI, Crypto, and the Future of Civilization 01:02:24 - Final Thoughts: The Most Exciting and Terrifying Time in History
1:04:51

Another mindblowing conversation with my good friend .Emad... Enjoy!! 00:00 - Introduction 00:22 - AI: The Biggest Shift in Human History 00:42 - AI’s Impact on Society and the Economy 01:03 - Conversation with Emad Mostaque Begins 01:50 - The Acceleration of AI and Economic Takeoff 03:07 - AI Intelligence: Beyond Human IQ 04:08 - The Rise of AI Chefs and Super Cooks 05:07 - Breaking AI Constraints: Compute and Energy 07:03 - The Future of AI: Ubiquitous Intelligence 08:04 - The Shift to Local AI Models 10:07 - Why Has Apple Lagged in AI? 11:21 - The AI Race: OpenAI, Grok, Gemini, and More 13:11 - China’s Open-Source AI Strategy 14:57 - AI Bias and Ethical Challenges 16:57 - AI’s Cross-Pollination and Memory 18:02 - Are AI Models Becoming Self-Aware? 19:16 - AI, Bitcoin, and Self-Sustaining Algorithms 21:26 - AI-Driven Economies and Autonomous Companies 23:41 - The Future of Labor: A World Without Jobs? 25:26 - AI-Powered Robots: The Next Workforce Revolution 27:28 - The End of Traditional Economic Models 30:27 - The Political Shift: Humanist vs. Transhumanist 33:04 - AI in Financial Markets: The End of Human Traders? 36:03 - The Evolution of Investing in an AI World 38:33 - AI’s Impact on Capital Formation and Business Disruption 40:01 - The Rise of Digital Twins and Post-Capital Society 42:45 - Building AI for Education, Healthcare, and Governance 46:42 - The Future of Money in an AI-Driven World 50:11 - Universal Basic AI: A New Economic Model 54:29 - The Deflationary Impact of AI and Crypto’s Role 57:02 - The AI Singularity: Five Years Until Everything Changes 58:56 - The Road Ahead: AI, Crypto, and the Future of Civilization 01:02:24 - Final Thoughts: The Most Exciting and Terrifying Time in History

Raoul Pal

326,827 görüntüleme • 1 yıl önce

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George
31:52

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George

a16z

92,096 görüntüleme • 8 ay önce

Brex co-founder and CEO Pedro Franceschi believes most people still underestimate how much AI will change the way companies are built. AI isn't just another tool, it's a new foundation for building products, teams, and companies. In this episode of Lightcone Podcast, Pedro Franceschi explains why we're only months into a platform shift as significant as the invention of electricity, why the CEO needs to be the chief AI officer, and why founders should rethink what's possible when intelligence is available on demand. 01:13 – How Pedro Became AI-Pilled 04:08 – The Electricity Analogy 05:21 – Free the Claw 06:56 – Making AI Safe for Enterprise 10:57 – Why Most Companies Are Behind 13:09 – AI Teammates, Not Chatbots 14:22 – The Case for Tokenmaxxing 18:24 – The Company of One 20:54 – The One Thing AI Can't Replace 28:06 – Building Customer World Models 32:58 – Rebuilding Brex Around AI 39:02 – The CEO Must Be the Chief AI Officer 43:50 – Building Company AGI 51:43 – Why We're Still So Early
54:06

Brex co-founder and CEO Pedro Franceschi believes most people still underestimate how much AI will change the way companies are built. AI isn't just another tool, it's a new foundation for building products, teams, and companies. In this episode of Lightcone Podcast, Pedro Franceschi explains why we're only months into a platform shift as significant as the invention of electricity, why the CEO needs to be the chief AI officer, and why founders should rethink what's possible when intelligence is available on demand. 01:13 – How Pedro Became AI-Pilled 04:08 – The Electricity Analogy 05:21 – Free the Claw 06:56 – Making AI Safe for Enterprise 10:57 – Why Most Companies Are Behind 13:09 – AI Teammates, Not Chatbots 14:22 – The Case for Tokenmaxxing 18:24 – The Company of One 20:54 – The One Thing AI Can't Replace 28:06 – Building Customer World Models 32:58 – Rebuilding Brex Around AI 39:02 – The CEO Must Be the Chief AI Officer 43:50 – Building Company AGI 51:43 – Why We're Still So Early

Y Combinator

197,159 görüntüleme • 1 ay önce

Why AI Progress Suddenly Feels Real - my conversation with Yann Dubois, who co-leads the Post-Training Frontiers team at OpenAI 00:00 - Intro 01:30 - Why recent AI progress feels like a step function 04:13 - Model reliability & the emotional rollercoaster of shipping GPT-5.5 07:33 - How OpenAI structures vertical and horizontal teams 09:49 - Improving model efficiency and test-time compute 12:32 - Yann's journey from Switzerland to OpenAI 15:37 - Reasoning in 2026: Real-world utility vs verifiable rewards 18:34 - GPT-5.5 Thinking vs Pro: Scaling test-time compute 20:09 - How reasoning models become more efficient 23:23 - Pre-training scaling and overcoming the data wall 27:03 - Multimodal data, synthetic data, and embodied AI 31:05 - Demystifying mid-training and post-training 37:21 - Does RL create new capabilities in AI? 38:53 - The challenges and frontier of scaling RL 43:09 - Is building AI models a craft or a strict science 48:21 - How AI models generalize across different domains 54:18 - How reinforcement learning cures AI hallucinations 56:04 - Negative generalization and conflicting instructions 58:05 - Can RL scale to law, medicine, and the broader economy? 1:00:19 - The evaluation bottleneck and Model as a Judge 1:04:21 - Continuous AI progress & continual learning 1:08:49 - Will foundation models eat the agent harness 1:11:23 - Why startups should focus on the last mile of AI
1:13:56

Why AI Progress Suddenly Feels Real - my conversation with Yann Dubois, who co-leads the Post-Training Frontiers team at OpenAI 00:00 - Intro 01:30 - Why recent AI progress feels like a step function 04:13 - Model reliability & the emotional rollercoaster of shipping GPT-5.5 07:33 - How OpenAI structures vertical and horizontal teams 09:49 - Improving model efficiency and test-time compute 12:32 - Yann's journey from Switzerland to OpenAI 15:37 - Reasoning in 2026: Real-world utility vs verifiable rewards 18:34 - GPT-5.5 Thinking vs Pro: Scaling test-time compute 20:09 - How reasoning models become more efficient 23:23 - Pre-training scaling and overcoming the data wall 27:03 - Multimodal data, synthetic data, and embodied AI 31:05 - Demystifying mid-training and post-training 37:21 - Does RL create new capabilities in AI? 38:53 - The challenges and frontier of scaling RL 43:09 - Is building AI models a craft or a strict science 48:21 - How AI models generalize across different domains 54:18 - How reinforcement learning cures AI hallucinations 56:04 - Negative generalization and conflicting instructions 58:05 - Can RL scale to law, medicine, and the broader economy? 1:00:19 - The evaluation bottleneck and Model as a Judge 1:04:21 - Continuous AI progress & continual learning 1:08:49 - Will foundation models eat the agent harness 1:11:23 - Why startups should focus on the last mile of AI

Matt Turck

100,493 görüntüleme • 1 ay önce

For nearly two decades, Box co-founder and CEO Aaron Levie (Aaron Levie) has been at the frontlines of how technology reshapes work—guiding the company through the rise of mobile, the cloud, and now the age of AI. In his fireside with YC's David Lieb at AI Startup School, Aaron reflects on adapting a company for the long term, staying relevant across multiple waves, and why he believes AI is the most transformative shift yet. 00:00 – AI hype vs. reality inside companies 01:00 – Early days: starting Box in 2005 03:30 – Pivoting from consumer storage to enterprise cloud 05:45 – Cloud transition lessons vs. AI today 07:10 – Why unstructured data is AI’s biggest opportunity 09:05 – Will AI replace jobs or create more work? 13:15 – Startups vs. incumbents in the AI era 15:20 – Finding the next “nouns and verbs” for startups 20:25 – Rethinking SaaS business models for AI agents 27:05 – Why companies won’t just build everything in-house 31:15 – Advice to young founders 35:40 – Fulfillment and meaning of life 36:40 – Enterprise design and craft in SaaS 39:00 – Competing with incumbents
40:27

For nearly two decades, Box co-founder and CEO Aaron Levie (Aaron Levie) has been at the frontlines of how technology reshapes work—guiding the company through the rise of mobile, the cloud, and now the age of AI. In his fireside with YC's David Lieb at AI Startup School, Aaron reflects on adapting a company for the long term, staying relevant across multiple waves, and why he believes AI is the most transformative shift yet. 00:00 – AI hype vs. reality inside companies 01:00 – Early days: starting Box in 2005 03:30 – Pivoting from consumer storage to enterprise cloud 05:45 – Cloud transition lessons vs. AI today 07:10 – Why unstructured data is AI’s biggest opportunity 09:05 – Will AI replace jobs or create more work? 13:15 – Startups vs. incumbents in the AI era 15:20 – Finding the next “nouns and verbs” for startups 20:25 – Rethinking SaaS business models for AI agents 27:05 – Why companies won’t just build everything in-house 31:15 – Advice to young founders 35:40 – Fulfillment and meaning of life 36:40 – Enterprise design and craft in SaaS 39:00 – Competing with incumbents

Y Combinator

236,530 görüntüleme • 10 ay önce

We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens
41:29

We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens

Y Combinator

67,145 görüntüleme • 2 ay önce

FULL INTERVIEW: Airbnb CEO Brian Chesky joins TBPN to discuss recent earnings, founder mode, the future of consumer AI, marketing, and more. 01:04 How Airbnb got its startup energy back 03:40 Founder mode and fixing one corner of the business at a time 06:14 How Chesky would disrupt Airbnb today 07:18 Why chatbots are wrong for travel 09:37 The SaaSpocalypse and AI interfaces 12:25 Why everyone is building enterprise AI 17:05 Why consumer AI hasn’t broken out yet 18:15 Why Silicon Valley keeps chasing trends 23:08 Advice for designers in the AI era 31:43 Why different marketing works best
35:18

FULL INTERVIEW: Airbnb CEO Brian Chesky joins TBPN to discuss recent earnings, founder mode, the future of consumer AI, marketing, and more. 01:04 How Airbnb got its startup energy back 03:40 Founder mode and fixing one corner of the business at a time 06:14 How Chesky would disrupt Airbnb today 07:18 Why chatbots are wrong for travel 09:37 The SaaSpocalypse and AI interfaces 12:25 Why everyone is building enterprise AI 17:05 Why consumer AI hasn’t broken out yet 18:15 Why Silicon Valley keeps chasing trends 23:08 Advice for designers in the AI era 31:43 Why different marketing works best

TBPN

15,497 görüntüleme • 2 ay önce

Australia's Productivity Commission Chair Danielle Wood on: - why AI probably won't cause a jobpocalypse, - how Australia can get a piece of the AI action, - why profits may not flow to the model layer of the stack, - and why Australia shouldn't follow the EU in legislating an AI Act -- even if AI turns out to be an "abnormal" technology. Watch below, or wherever you get your podcasts. Enjoy! Timestamps: (0:00:00) – Introduction. (0:01:43) – Is AI as big as the Industrial Revolution? (0:06:35) – The labour market implications of AI (0:21:18) – Industry policy for AI: when to intervene, when to step back (0:31:27) – Where will the profits flow? Chips, models, or applications? (0:52:37) – Data centres: should Australia support them? (1:15:07) – AI risks, and why Australia shouldn't pass an AI Act (1:23:27) – Measuring progress in the age of AI: beyond GDP and labour productivity
1:38:12

Australia's Productivity Commission Chair Danielle Wood on: - why AI probably won't cause a jobpocalypse, - how Australia can get a piece of the AI action, - why profits may not flow to the model layer of the stack, - and why Australia shouldn't follow the EU in legislating an AI Act -- even if AI turns out to be an "abnormal" technology. Watch below, or wherever you get your podcasts. Enjoy! Timestamps: (0:00:00) – Introduction. (0:01:43) – Is AI as big as the Industrial Revolution? (0:06:35) – The labour market implications of AI (0:21:18) – Industry policy for AI: when to intervene, when to step back (0:31:27) – Where will the profits flow? Chips, models, or applications? (0:52:37) – Data centres: should Australia support them? (1:15:07) – AI risks, and why Australia shouldn't pass an AI Act (1:23:27) – Measuring progress in the age of AI: beyond GDP and labour productivity

Joseph Noel Walker

11,751 görüntüleme • 1 ay önce

AI has ignited a consumer renaissance. My friend Kevin Rose is a legend in consumer tech. He founded a number of early internet startups, including Digg, where he invented an early predecessor to the now ubiquitous like button. He’s now a partner at True Ventures and recently relaunched Digg. We had a wide-ranging conversation on all things consumer tech, including why I think AI code will be an entire industry, why Kevin looks for “weird and working” products, Kevin’s dinners with Mark Zuckerberg, and how AI products will affect the human experience. 00:00 Intro 02:10 How we met 07:50 AI’s Renaissance for Consumer Products 11:48 Companionship apps and the future of human connection 14:01 The optimistic and pessimistic views on AI relationships 19:18 Poke and emotional primitives 21:05 Weird and working: how to spot great founders 30:05 AI companions and AI in relationships 40:08 The modern AI dev stack and building apps solo 47:25 AI music, creativity, and the next cultural wave 53:50 Curiosity, risk, and finding the next big thing 01:15:00 Always-on recording and social norms in tech
1:24:14

AI has ignited a consumer renaissance. My friend Kevin Rose is a legend in consumer tech. He founded a number of early internet startups, including Digg, where he invented an early predecessor to the now ubiquitous like button. He’s now a partner at True Ventures and recently relaunched Digg. We had a wide-ranging conversation on all things consumer tech, including why I think AI code will be an entire industry, why Kevin looks for “weird and working” products, Kevin’s dinners with Mark Zuckerberg, and how AI products will affect the human experience. 00:00 Intro 02:10 How we met 07:50 AI’s Renaissance for Consumer Products 11:48 Companionship apps and the future of human connection 14:01 The optimistic and pessimistic views on AI relationships 19:18 Poke and emotional primitives 21:05 Weird and working: how to spot great founders 30:05 AI companions and AI in relationships 40:08 The modern AI dev stack and building apps solo 47:25 AI music, creativity, and the next cultural wave 53:50 Curiosity, risk, and finding the next big thing 01:15:00 Always-on recording and social norms in tech

Anish Acharya

38,002 görüntüleme • 8 ay önce

My interview with Helen Toner on firing Altman, AGI geopolitics in China & Middle East, and military use of AI. Toner co-founded and now leads the Center for Security and Emerging Technology at Georgetown in DC, maybe the leading think tank on natsec and AI. We discuss: • Is China actually racing to build AGI? [00:27:56] • Why you shouldn't say 'alignment' [01:45:11] • Is Congress starting to take superintelligence seriously? [01:47:42] • Are data centres in the UAE “good for democracy”? [00:52:41] • Sure China could steal AI model weights, but does it matter [00:39:13] • Is it good if the world uses US not Chinese AI models? [00:21:58] • Why non-proliferation is a misguided model for AI [01:30:20] • Helen thinks AI progress isn't slowing down [01:50:10] • Will AI inevitably concentrate power? [01:07:49] • Helen’s defence of how the board handled firing Altman [00:01:32] • Will the military be willing to defer to AI in decision-making? [01:38:23] Available any place you get podcasts on the '80,000 Hours Podcast'. Links below — enjoy!
2:23:01

My interview with Helen Toner on firing Altman, AGI geopolitics in China & Middle East, and military use of AI. Toner co-founded and now leads the Center for Security and Emerging Technology at Georgetown in DC, maybe the leading think tank on natsec and AI. We discuss: • Is China actually racing to build AGI? [00:27:56] • Why you shouldn't say 'alignment' [01:45:11] • Is Congress starting to take superintelligence seriously? [01:47:42] • Are data centres in the UAE “good for democracy”? [00:52:41] • Sure China could steal AI model weights, but does it matter [00:39:13] • Is it good if the world uses US not Chinese AI models? [00:21:58] • Why non-proliferation is a misguided model for AI [01:30:20] • Helen thinks AI progress isn't slowing down [01:50:10] • Will AI inevitably concentrate power? [01:07:49] • Helen’s defence of how the board handled firing Altman [00:01:32] • Will the military be willing to defer to AI in decision-making? [01:38:23] Available any place you get podcasts on the '80,000 Hours Podcast'. Links below — enjoy!

Rob Wiblin

20,369 görüntüleme • 8 ay önce

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

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

a16z crypto

24,109 görüntüleme • 2 ay önce

State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, The Rise of Headless, and AI-Proofing Your Job 00:00 Intro 01:18 Silicon Valley engineering vs. everyone else 05:35 Are enterprise CIOs actually bullish on AI? 08:51 Tokenmaxxing & why your AI bill is about to explode 11:34 The myth of falling token costs and AI spend escaping IT budgets 17:37 The $5B startup hiding in AI compute 18:14 The mosaic of models inside every enterprise 21:28 Why coding works and the rest of knowledge work doesn't 25:53 The Bob and Sally problem: access control breaks agents 30:31 Will enterprise AI really take 10 years to roll out 32:24 The capability overhang: why faster models slow diffusion 34:23 Data is the bottleneck (it always was) 39:02 The rise of internal forward-deployed engineers 41:23 Why the AI doomers are wrong about jobs 43:43 Headless software is inevitable 46:14 What replaces per-seat pricing 47:37 How Box itself is going headless 49:42 How the org chart actually evolves 1:00:33 Future-proofing yourself as an enterprise employee 1:06:40 Are we all just going to work for OpenAI and Anthropic? 1:07:11 Where startups can still win as the labs move up
1:12:54

State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, The Rise of Headless, and AI-Proofing Your Job 00:00 Intro 01:18 Silicon Valley engineering vs. everyone else 05:35 Are enterprise CIOs actually bullish on AI? 08:51 Tokenmaxxing & why your AI bill is about to explode 11:34 The myth of falling token costs and AI spend escaping IT budgets 17:37 The $5B startup hiding in AI compute 18:14 The mosaic of models inside every enterprise 21:28 Why coding works and the rest of knowledge work doesn't 25:53 The Bob and Sally problem: access control breaks agents 30:31 Will enterprise AI really take 10 years to roll out 32:24 The capability overhang: why faster models slow diffusion 34:23 Data is the bottleneck (it always was) 39:02 The rise of internal forward-deployed engineers 41:23 Why the AI doomers are wrong about jobs 43:43 Headless software is inevitable 46:14 What replaces per-seat pricing 47:37 How Box itself is going headless 49:42 How the org chart actually evolves 1:00:33 Future-proofing yourself as an enterprise employee 1:06:40 Are we all just going to work for OpenAI and Anthropic? 1:07:11 Where startups can still win as the labs move up

Matt Turck

49,373 görüntüleme • 1 ay önce

In this episode of the Lightcone Podcast, we sat down with Mukund Jha and Madhav Jha, the founders of Emergent - an AI platform that lets anyone build and ship production-ready software. In just eight months, users have created more than 7 million apps on Emergent, with the number doubling in just the last 45 days. We discuss how they built one of the most powerful AI coding agents, why they focused on non-technical users and what it's like building for a global audience from India. 00:00 - Intro 01:06 - What Is Emergent? 01:18 - Founder Backstory 02:09 - From AI Testing to General Coding Agents 02:52 - Getting Ahead of the Market 04:18 - The Pivot to Non-Technical Users 05:22 - Why Second Movers Can Win in AI 09:04 - Building for Production, Not Just Prototypes 18:21 - Live Demo: Building Apps with Emergent 24:40 - How Emergent Hires and Runs a Lean Team 29:04 - Is SaaS Dead? The Rise of Personalized Software 34:04 - The Future: Niche Apps, Solo Builders and AI Agency
39:32

In this episode of the Lightcone Podcast, we sat down with Mukund Jha and Madhav Jha, the founders of Emergent - an AI platform that lets anyone build and ship production-ready software. In just eight months, users have created more than 7 million apps on Emergent, with the number doubling in just the last 45 days. We discuss how they built one of the most powerful AI coding agents, why they focused on non-technical users and what it's like building for a global audience from India. 00:00 - Intro 01:06 - What Is Emergent? 01:18 - Founder Backstory 02:09 - From AI Testing to General Coding Agents 02:52 - Getting Ahead of the Market 04:18 - The Pivot to Non-Technical Users 05:22 - Why Second Movers Can Win in AI 09:04 - Building for Production, Not Just Prototypes 18:21 - Live Demo: Building Apps with Emergent 24:40 - How Emergent Hires and Runs a Lean Team 29:04 - Is SaaS Dead? The Rise of Personalized Software 34:04 - The Future: Niche Apps, Solo Builders and AI Agency

Y Combinator

107,448 görüntüleme • 4 ay önce

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

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

University of Austin (UATX)

27,770 görüntüleme • 5 ay önce

INTERVIEW - Venice Is Here to Win: How Private AI Takes On OpenAI and Anthropic David Hoffman sits down with Jon ShapeShift and Jesse Proudman to unpack how Venice is taking on OpenAI and Anthropic with private AI. They talk about: - why AI is becoming the biggest data honeypot ever - private Grok access through Venice - unrestricted AI as a consumer wedge - how non-crypto users still feed the $VVV economy - $DIEM, tokenized inference, and AI agents --- TIMESTAMPS 0:00 Intro 1:12 Why Private AI Matters 3:01 The AI Data Honeypot 6:07 Venice’s Consumer AI Ambition 8:01 Beating the Big AI Labs 10:19 Model Aggregation and Agentic Chat 12:29 Open Source, Closed Source, and Private Grok 17:14 Who Actually Needs Private AI? 21:58 Venice’s User Base 23:53 What Drove Venice’s Recent Growth 27:21 $VVV, $DIEM, and Tokenized Inference 29:00 Where Venice Gets Its Compute 32:17 Bonding Curves and DIEM Monetary Policy 39:14 Real Tokenomics, Not Just a Pie Chart 45:46 AI Agents Need Inference to Exist 52:54 ShapeShift DNA Inside Venice 55:53 Regulation, AI, and Individual Rights
58:52

INTERVIEW - Venice Is Here to Win: How Private AI Takes On OpenAI and Anthropic David Hoffman sits down with Jon ShapeShift and Jesse Proudman to unpack how Venice is taking on OpenAI and Anthropic with private AI. They talk about: - why AI is becoming the biggest data honeypot ever - private Grok access through Venice - unrestricted AI as a consumer wedge - how non-crypto users still feed the $VVV economy - $DIEM, tokenized inference, and AI agents --- TIMESTAMPS 0:00 Intro 1:12 Why Private AI Matters 3:01 The AI Data Honeypot 6:07 Venice’s Consumer AI Ambition 8:01 Beating the Big AI Labs 10:19 Model Aggregation and Agentic Chat 12:29 Open Source, Closed Source, and Private Grok 17:14 Who Actually Needs Private AI? 21:58 Venice’s User Base 23:53 What Drove Venice’s Recent Growth 27:21 $VVV, $DIEM, and Tokenized Inference 29:00 Where Venice Gets Its Compute 32:17 Bonding Curves and DIEM Monetary Policy 39:14 Real Tokenomics, Not Just a Pie Chart 45:46 AI Agents Need Inference to Exist 52:54 ShapeShift DNA Inside Venice 55:53 Regulation, AI, and Individual Rights

Bankless

59,022 görüntüleme • 1 ay önce

This is my sixth conversation with Gavin Baker. As always with Gavin, the conversation covers a lot of ground, but we spend the most time on watts and wafers. We discuss: - Why the wafer shortage may prevent an AI bubble - Data centers in space (reframed) - Elon's Terafab and the new chip companies challenging Nvidia - Usage-based pricing - The disaggregation of GPUs - DRAM, frontier tokens, and open source Enjoy! Timestamps: 0:00 Intro 7:55 Anthropic and OpenAI Valuations 12:58 Watts, Wafers, and Infrastructure 14:39 Orbital Compute and Data Centers in Space 22:49 Avoiding the AI Bubble 28:26 Terafab and the Future of US Manufacturing 32:16 Returns to the Frontier 37:23 Continual Learning 42:03 New Chip Companies 48:52 Extending GPU Lifespans and Private Credit 51:22 The Application Layer 57:32 The Token Path and Open-Source Dynamics 1:01:37 Cybersecurity 1:05:46 Diversity Breakdown 1:11:59 Assessing the Big Tech Players in AI 1:19:02 Geopolitics, Personal Safety, and the AI Horizon
1:22:10

This is my sixth conversation with Gavin Baker. As always with Gavin, the conversation covers a lot of ground, but we spend the most time on watts and wafers. We discuss: - Why the wafer shortage may prevent an AI bubble - Data centers in space (reframed) - Elon's Terafab and the new chip companies challenging Nvidia - Usage-based pricing - The disaggregation of GPUs - DRAM, frontier tokens, and open source Enjoy! Timestamps: 0:00 Intro 7:55 Anthropic and OpenAI Valuations 12:58 Watts, Wafers, and Infrastructure 14:39 Orbital Compute and Data Centers in Space 22:49 Avoiding the AI Bubble 28:26 Terafab and the Future of US Manufacturing 32:16 Returns to the Frontier 37:23 Continual Learning 42:03 New Chip Companies 48:52 Extending GPU Lifespans and Private Credit 51:22 The Application Layer 57:32 The Token Path and Open-Source Dynamics 1:01:37 Cybersecurity 1:05:46 Diversity Breakdown 1:11:59 Assessing the Big Tech Players in AI 1:19:02 Geopolitics, Personal Safety, and the AI Horizon

Patrick OShaughnessy

1,657,625 görüntüleme • 1 ay önce