As generative AI hits hardware and latency bottlenecks, Stanford professor, diffusion pioneer, and Inception co-founder and CEO Stefano Ermon is betting on a radical new architecture. Stefano joins Sarah Guo to talk about Inception, and how his team is applying diffusion architecture beyond images and video into discrete text and code generation. Stefano explains the limitations of autoregressive LLMs, as well as why parallel token generation in diffusion models offers superior inference scaling and hardware utilization on standard GPUs. He also shares details about Inception’s Mercury models, real-world voice agent applications, the software stack required to serve diffusion-based models at scale, academia’s role at the frontier of AI innovations, and why the next era of AI competition will be defined by efficiency.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @StefanoErmon | @_inception_ai Chapters: 00:00 – Stefano Ermon Introduction 00:35 – Research Background 02:54 – Starting Inception 05:59 – Why Diffusion Beats Autoregressive 11:10 – Discrete vs. Continuous Modalities 13:19 – Inception Today 16:45 – Where Speed Wins 17:31 – Inception Customer Base 18:49 – Interaction with Hardware Landscape 19:34 – Inception and the Broader Industry 21:41 – Data Compression and Structure 24:45 – Controllability of Diffusion Modeles 27:25 – Emergent Capabilities at Scale 29:02 – Future Workload Split Between Diffusion vs. Traditional 30:03 – Adoption Challenges 31:44 – Hiring and Team Organization 32:50 – Recursive Self Improvement 34:02 – Resource Allocation 35:10 – Impact of Academia 38:13 – Conclusion

From the tokenization of real-world assets to funding research on anti-aging therapeutics, Coinbase co-founder and CEO Brian Armstrong is focused on solving meta-problems for the benefit of society. Brian joins Elad Gil this episode to discuss the intersections of artificial intelligence, crypto rails, and biotechnology. He details Coinbase’s vision for agentic finance, as well as how Coinbase is becoming the ‘Everything Exchange’, which includes tokenized real-world stocks, stablecoin payment adoption, and prediction markets. Brian also introduces his new venture, New Limit, a company founded to tackle longevity through epigenetic reprogramming, and outlines initial therapeutic programs and the roadmap toward clinical trials.   Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @brian_armstrong | @Coinbase Chapters: 00:00 – Cold Open Trailer 00:45 – Brian Armstrong Introduction 01:13 – Coinbase and the Everything Exchange 05:52 – Agentic Commerce 10:00 – AI and Crypto 10:49 – AI Inside Coinbase 15:39 – Productivity and Company Size 17:26 – The Everything Exchange and Tokenization 20:53 – Prediction Markets 23:15 – Introducing New Limit 34:17 – Looking Forward Five Years 40:24 – Special Economic Zones 44:26 – Conclusion

From data center orchestrators to AGI and robotics, CPUs remain the heart of modern computing. Arm CEO Rene Haas joins Elad Gil and Sarah Guo to explore how Arm is positioned at the epicenter of AI-driven demands for compute. Rene explains Arm’s position in the chip supply chain, and how Arm transitioned from an IP licensing model to producing physical chips like the Arm AGI CPU for Meta. He also discusses bottlenecks in hardware supply chains, SoftBank’s ecosystem and capital strategy, why US semiconductor manufacturing independence is critical, the future of robotics, and why CPUs remain crucial for executing AI workloads. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @renehaas237 | @Arm Chapters: 00:00 – Cold Open Trailer 00:49 – Rene Haas Introduction 01:14 – Arm and Chip Supply Chain 02:37 – Shift from IP to Manufacturing CPUs 04:23 – CPU IP and Customers 06:55 – AI Adoption at Arm 10:15 – Changes in Chip Time to Market 13:27 – Data Center Buildout Bottleneck 15:13 – Softbank Leverage and Capital Strategy 17:43 – Softbank Portfolio Overview 20:13 – Robotics Opportunities for Arm 24:49 – US Manufacturing Protectionism 28:59 – Data Center Backlash 32:30 – Arm Outlook 33:31 – CPU Opportunity 37:06 – Conclusion

Google’s purchase of Spirit Airlines’ data out of bankruptcy signaled a shift in how the tech world values real-world datasets. Although compute and models get much of the attention, in this landscape, it’s data that is a company’s protective moat. Eon CEO / Co-Founder Ofir Ehrlich and President / Co-Founder Gonen Stein join Elad Gil to talk about how Eon is redefining cloud backup into a secure data foundation designed to power and protect enterprise AI. Ofir and Gonen discuss why historical enterprise data is in demand by AI labs, and how Eon facilitates access to scattered and locked data across business units through providing the mapping, classification, and access controls needed to connect it into AI workflows. They also explore how traditional ransomware defenses must now protect against rogue AI agents with legitimate system permissions, concerns around the influx of autonomous agents and non-human identities, and the implications for the breakneck speed of AI adoption compared to the slowness of the cloud era.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Eon_io_ | @OfirEhrlich Chapters: 00:00 – Cold Open Trailer 00:59 – Ofir Ehrlich and Gonen Stein Introduction 01:27 – What Eon Does 02:41 – Data as Moat 06:43 – Training Agents with Good Data 09:39 – Data is the New Oil  15:00 – Autonomous Security Threats 18:15 – How Agents Change the Enterprise Stack 22:11 – Re-imagining Data Infrastructure 27:52 – Cloud vs. AI Era Shift 30:26 – How AI is Changing Companies 34:31 – Conclusion

Max Hodak, co-founder and CEO of Science Corporation, joins Sarah Guo to discuss the future of vision, brain-computer interfaces, and the human experience. Max explains how Science’s PRIMA retinal implant could restore functional vision for people who have lost their sight, and why treating the brain as a computational system could unlock new approaches to medicine. They explore the broader potential of neural devices, from restoring lost capabilities to expanding human potential, as well as deeper questions around identity, consciousness, and whether the human experience can persist as our biological hardware changes. Max also shares Science’s long-term vision for reducing the fragility of the human condition by repairing, replacing, and ultimately upgrading parts of ourselves. Finally, he discusses the surprising parallels between AI models and biological brains, and why AI may offer a powerful new lens for understanding intelligence. Chapters: 00:00 – Cold Open Trailer 01:40 – Max Hodak Introduction 02:00 – Science Corporation Overview and Origin 02:53 – A Revolutionary Solve for Blindness  06:32 – Scope of Timeline and Engineer Cost 09:10 – Clinic Trial Process 09:45 - The Response from Clinicians 12:21 – Broader Biotech Landscape 14:59 – Brain’s Relationship to Senses 17:35 – The Study of Consciousness  19:50 – Investments in Brain Computer Interface 22:10 – Fertile Ways to Study Neuroscience 24:46 – Biotech Expansion for Science Corporation 27:50 – What Success Looks Like in Neuroscience and Tech 29:06 - Goals Within Human Preservation vs. Adaptation  30:25 – Conclusion

In a world of infinite gaming and entertainment possibilities, how does a centuries-old game stay so popular? Chess.com co-founder and CEO Erik Allebest joins Sarah Guo to explain how the evolution of technology has kept people coming back to chess, even when machines can beat us at the game. Erik talks about how the desire to build a MySpace-like community for chess led to the purchase of a domain name from a bankruptcy sale back in 2005, and scaled into a community with 10 million daily active users and 250 million total registered members. He also discusses the growth of the cultural relevance of chess, how investments from private equity firms General Atlantic and CVC helped grow and strengthen their platform, and how Chess.com is leveraging AI both within the business itself and to make a better product for its community. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @chesscom | @erikallebest Chapters: 00:00 – Cold Open Trailer 01:05 – Erik Allebest Introduction 01:48 – Chess.com Today 02:57 – Buying and Scaling Chess.com  06:29 – Competition and Growth 11:52 – Chess and Cultural Relevance 14:32 – Private Equity Investment 19:31 – Playing Games Amid Evolving Tech 25:09 – Tech, Skill Distribution, and Expertise 28:40 – Chess and Cheating 31:20 – What Makes Chess Special 33:17 – Chess.com Future Vision 34:54 – Founder Advice 36:48 – AGI/ASI Predictions 40:02 – AI Investments at Chess.com  42:13 – How AI May Change Product at Chess.com 43:27 – Poker Rating Algorithms 46:07 – Conclusion

Is the tech industry moving too quickly, or are founders letting fear of AI labs stunt their ambitions? Sarah and Elad explore the current landscape of artificial intelligence, venture capital, and startup dynamics. They discuss the realities of building multi-trillion-dollar companies, shifting market sizes and outcome-based pricing models, and how founders are reacting to the rise of major AI labs. They also talk about what the framework for startup exits should look like, the potential for researcher burnouts in the next eighteen months as ASI looms on the horizon, bottlenecks for compute, and the impact of regulatory capture and shifting ecosystems from California to Texas. Apply for Embed - Conviction’s Catalyst for AI-Native Startups Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Cold Open Trailer 00:31 – Episode Introduction 01:44 – The Next Trillion-Dollar Company 03:12 – Tech Waves as Punctuated Equilibria  04:42 – TAM vs. Revenue Reality 07:14 – Market Size vs. Speed 10:32 – When Founders Should Sell 14:04 – Financing and Time Cost 17:57 – RSI and the Looming Promise of ASI 21:49 – Compute Power Laws 28:12 – Regulations and Disruption 33:06 – Beyond Transformers 34:26 – Tradeoffs - Safety vs. Progress 39:11 – Conclusion

When your AC fails in a heatwave, you don’t want a busy signal; you need a solution. Netic founder and CEO Melisa Tokmak joins host Elad Gil to explain how Netic’s autonomous AI platform acts as an intermediary between companies and customers, deploying agents to instantly handle essential services, from emergency home repairs to hospitality to pet care. Melisa describes the complexity of these real-world workloads, which have traditionally relied on large human support teams, and how over 70% of Netic’s customers interact first with AI. She also talks about the reasoning behind building a scalable product company rather than an AI roll-up, why she believes robotics will not catch up in these industries in the near future, why she doesn’t view large frontier labs as competitive threats, and how private equity’s playbook has shifted toward measurable ROI in the AI-era. Plus, why Melisa is optimistic about the impact AI will have on education. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @netic_AI | @melisatokmak Chapters: 00:00 – Melisa Tokmak Introduction 00:32 – What Netic Builds 03:53 – Automating Workflows for Essential Services 06:26 – Building a Service vs. AI Roll-Up 10:38 – AI for the Real World Timeline 12:56 – Can Big Labs Compete? 15:35 – Modern Founder Mindset 19:09 – Screening for Agency 22:25 – Five Year Vision 23:53 – Selling to Slow Industries 27:23 – How Private Equity Approached AI 31:14 – What Excites Melisa About the Future of AI 34:27 – Conclusion

DoorDash is not just a delivery company. From its inception, co-founders Andy Fang and Stanley Tang operated it as a robotics and autonomy company. Andy and Stanley join Sarah Guo to explain how autonomous tech and AI are reshaping consumer habits, commerce, and delivery. Andy and Stanley talk about the rollout of Ask DoorDash, a natural-language interface that’s driving both restaurant discovery and larger grocery orders. They also discuss Dot, their in-house autonomous delivery robot that has operated in Phoenix for over two years, and how it highlights the operational and hardware challenges they have faced and solved in autonomous tech. Andy and Stanley also speak about the “first and last 100 feet problem” in autonomous delivery, why multimodal strategies are the key to success, scaling autonomy and operations, and why they believe that more Dashers, not fewer, are the future of DoorDash.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @stanleytang | @andyfang | @DoorDash Chapters: 00:00 – Andy Fang and Stanley Tang Introduction 00:34 – Agentic Commerce and Behavioral Changes 03:52 – Next Steps for Ask DoorDash 06:54 – Investing in Robotics and Autonomy 16:31 – Building Autonomous Tech in the Physical World 21:20 – Dot: DoorDash’s Autonomous Delivery Robot 22:08 – Collecting Realistic Data 25:48 – Why Work at DoorDash 28:04 – Challenges in Scaling Up Autonomy 39:30 – Productivity Benchmarks 44:56 – Future of Agentic Commerce 49:10 – Conclusion

When Glenn Fogel joined Priceline in 2000, the business was worth a few hundred million dollars. One week later, the Nasdaq peaked, eventually sending its stock down to a dollar a share. But over 25 years later, Booking Holdings has scaled over 1000x into an over $100 billion dollar global travel behemoth. Elad Gil is joined by Booking Holdings CEO Glenn Fogel to discuss his career, from law school and Wall Street to working at Priceline through the dot-com crash, and to helping grow the business into a multifaceted, dynamic travel marketplace in the AI era. Glenn explains how leveraging AI and agents such as Priceline’s ‘Penny’ makes travel planning and customer service better, while emphasizing the importance of preserving some human support for some users. He also talks about Booking’s strategy of reinvesting over $700 million into AI and other technologies while still offering stock buybacks and dividends, the durability of their scale and complexities of dealing with a large portfolio physical properties across the world, and why upskilling is so important for employees amid concerns about AI-driven job displacement.      Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @bookingcom | @priceline Chapters: 00:00 – Cold Open 00:05 – Glenn Fogel Introduction 00:41 – Glenn’s Early Career 06:49 – Lessons from the Early Internet 09:24 – Deciding Factors for Exiting 10:56 – Travel Through the Lens of AI 13:30 – Agentic Travel Planning  18:59 – Agents, Token Economics, and ROI 22:46 – Booking’s Capital Investment Philosophy 25:23 – Scale as Durable Asset 29:40 – Purpose and Choosing Wisely 33:18 – AI’s Impact on Jobs 36:38 – Upskilling in the AI Era 38:36 – Public Perception of AI 40:24 – Conclusion