Podcast
No Priors: Artificial Intelligence | Technology | Startups
Hosted by Conviction · EN
At this moment of inflection in technology, co-hosts Elad Gil and Sarah Guo talk to the world's leading AI engineers, researchers and founders about the biggest questions: How far away is AGI? What markets are at risk for disruption? How will commerce, culture, and society change? What’s happening in state-of-the-art in research? “No Priors” is your guide to the AI revolution. Email feedback to show@no-priors.com.
Sarah Guo is a startup investor and the founder of Conviction, an investment firm purpose-built to serve intelligent software, or "Software 3.0" companies. She spent nearly a decade incubating and investing at venture firm Greylock Partners.
Elad Gil is a serial entrepreneur and a startup investor. He was co-founder of Color Health, Mixer Labs (which was acquired by Twitter). He has invested in over 40 companies now worth $1B or more each, and is also author of the High Growth Handbook.
169episodes
Episodes
Newest firstAll episodes
How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor
5d ago01:01:26Summary readyWhile the rest of the nuclear industry still relies on simulations and paper designs, Valar Atomics is busy splitting atoms. In fact, they just powered an NVIDIA Blackwell chip directly with a live nuclear reactor in order to power the world’s first nuclear powered website. Sarah Guo joins Valar Atomics founder and CEO Isaiah Taylor on-site at their California headquarters to talk about how Valar is shifting nuclear energy from the theoretical to the practical by building and perfecting reactors via hardware iteration. Isaiah discusses why the US stopped building nuclear reactors in the 1970s, and how Valar utilized a little-known pathway via the Department of Energy, revived by a Trump administration executive order, to successfully develop and run their advanced reactor. He also shares Valar’s strategy for vertical integration, their venture-backed approach to financing, their giga-site plans, and why he believes cheap, abundant atomic energy has the power to vastly improve the quality of human life. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @isaiah_p_taylor | @valaratomics Chapters: 00:00 – Cold Open 00:57 – Isaiah Taylor Introduction 01:30 - Valar’s Mission and Origin 04:24 - Why Nuclear Development Stalled 07:18 - Reviving Nuclear through DoE and Executive Order 10:59 - Control Room Tour 16:17 - Misunderstandings About Nuclear 20:07 - Issues with Reliability 22:14 - Nuclear is a Hardware Execution Problem 24:32 - Timeline to Scale Production 26:32 - Introducing Ward 250 30:42 - Speed Through Simplicity 33:33 - AI Drives Nuclear Demand 35:02 - Running a Reactor with NVIDIA Blackwell 36:27 - Valar’s Nuclear Conviction 40:16 - Verticalization as Path to Scale 43:58 - Valar’s Control Skid 48:00 - Venture-Backed Nuclear 50:51 - Gigasite Strategy 53:11 - CEO Tick Rate 55:37 - Abundant Energy and Hyper-Techno Industrialism 1:01:27 – Conclusion
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Why Traditional Benchmarks Fail Modern AI Models with OpenAI Research Scientist Noam Brown
2w ago00:36:18Summary readyWhen a new AI model drops, it’s judged based on a static benchmark grid that doesn’t account for how long the model is allowed to think. How then should we measure a model’s true capability? OpenAI research scientist Noam Brown returns to talk with Sarah Guo about his latest essay on why the AI industry’s traditional benchmark grids are broken, and how large-scale test-time compute is fundamentally changing how models are evaluated. Noam explains how, if properly scaffolded, today’s models can reason for weeks or even months on complex tasks. He also discusses real-world implications of test-time compute, from building poker solver bots to disproving legendary math conjectures. Together, they also unpack the large gaps in current AI safety frameworks, explore the bottlenecks for recursive self-improvement, and look ahead at the future of multi-agent collaboration and global knowledge sharing. Read more: Implications of Large-Scale Test-Time Compute Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @polynoamial | @OpenAI Chapters: 00:00 – Cold Open 00:43 – Noam Brown Introduction 01:23 – Why Benchmarks Are Broken 04:19 – Compute Budgets and Projections 05:34 – How Long Should Models Think? 06:47 – Benchmark-Maxxing 08:34 – Using Poker Bots as Evals 11:26 – Safety Evals When Model Capability Scales With Budget 14:41 – Release Cycle vs. Agent Runtime 17:06 – Latent Model Capability 20:59 – Limits on Recursive Self-Improvement 27:09 – Large-Scale Multi-Agent Coordination 29:11 – Competition at the Frontier 31:51 – Breaking the Benchmark Grid Equilibrium 33:29 – Why Benchmarks Should be Evaluated by Cost 36:18 – Conclusion
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Re-engineering the Semiconductor Supply Chain with Intel CEO Lip Bu Tan
3w ago00:44:59Summary readyAt 66 years old, instead of heading towards retirement, former Cadence CEO and legendary investor Lip Bu Tan decided to take on the hardest job in tech: turning Intel around. Elad Gil and Sarah Guo sit down with Intel CEO Lip Bu Tan to talk about why he took the job and what “saving” Intel actually looks like. Tan explains how his experience in startup culture informed his decisions to drive Intel’s culture towards faster decisions, focus on customer satisfaction, and engineer accountability. He also discusses his strategy to strengthen Intel’s balance sheet by welcoming investments from Jensen Huang’s Nvidia, Softbank, and the US government. Tan also shares his product roadmap that centers the CPU for agentic AI and inference, the collaboration with Elon Musk on Terafab, his investing framework for semiconductors, and his views on how AI is reshaping design and operations at, as he puts it, a ‘legacy spreadsheet’ tech company. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LipBuTan1 | @intel Chapters: 00:00 – Cold Open 01:01 – Lip Bu Tan Introduction 01:24 – Why Lip Bu Took the Reins at Intel 03:00 – Fixing Culture 04:08 – Intel’s 10-Year Vision 07:57 – Working with Elon Musk on Terafab 09:59 – Shifting Supply Chain for Semiconductors 15:34 – Limits to Scaling and Packaging 18:30 – Physical Limits to Engineering and Design 20:33 – Challenges in Semiconductor Investing 26:29 – Lessons from Cadence 28:02 – Scaling and Investment Decisions 32:03 – Rethinking Teams in AI Era 34:31 – Industrial Policy and Funding 37:25 – What Investors Misunderstand About Intel 41:10 – Where Compute Will Live 44:59 – Conclusion
SummaryBiohub: The Future of Biology is Open-Source with Co-Founders Mark Zuckerberg, Priscilla Chan, and Head of Science Alex Rives
4w ago00:56:20Summary readyBiohub started with an ambitious goal of curing, preventing, and managing all disease by the end of the century. A decade later, thanks to the convergence of frontier AI and biological data, that goal may have been too conservative. In this episode, Elad Gil and Sarah Guo sit down with Biohub co-founders Mark Zuckerberg and Priscilla Chan, alongside Biohub Head of Science Alex Rives. Together, they discuss Biohub’s $500 million virtual biology initiative, which integrates frontier AI with wet-lab work to build predictive world models of cells, proteins, and systems. They also talk about their newly announced open-source engine for digital protein and antibody design, ESMFold2; why Biohub is a nonprofit rather than a venture-backed startup; and how hierarchical simulations will soon allow doctors to treat patients at an individual, mechanistic level. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Biohub | @finkd | @alexrives | @ChanZuckerberg Chapters: 00:00 – Cold Open 01:02 - Mark Zuckerberg, Priscilla Chan, and Alex Rives Introduction 01:26 – Why Biohub and Their Mission 08:27 – Integrating Frontier AI and Frontier Biology 09:45 – Micro to Macro Biological Modeling 14:22 – Mechanistic Interpretiability 16:58 – Why Biohub is a Non-Profit 21:41 – Understanding How Biology Works 24:23 – Timeline for Curing All Diseases 26:25 – Translating Research to Patient Impact 28:04 – Launch of ESMFold2 32:13 – Tackling Off-Target Effects and Edge Cases 38:39 – Putting the Tech in Individual Hands 41:06 – Talent at Biohub 44:25 – What’s Next After ESMFold2 46:10 – Connecting ESMFold2 to Agentic Systems 46:51 – The Virtual Cell 49:33 – Defining Success for Biohub 51:52 – Biohub Strategy Update 56:20 – Conclusion
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The Rise of the Full-Stack Builder and Hyper-Leveraged Generalist with Microsoft CEO Satya Nadella
Jun 400:42:26Summary readyWhat does it mean for a business to truly operate at the AI frontier? In a special crossover episode at Microsoft Build, Sarah Guo and Elad Gil team up with Latent Space host “swyx” to talk with Microsoft Chairman and CEO Satya Nadella about the future of AI platforms, software development, and the tech ecosystem. Satya reflects on the latest breakthroughs from Microsoft Build, the strategic shift toward multi-model harnesses, and why private evaluations (evals) are now a company’s most important intellectual property. They also discuss how autonomous AI agents are reshaping the role of software engineers, the durability of SaaS business models, and why showing communities the ROI on data centers is so critical. Plus, Satya shares his thoughts on the economic and societal impacts of the token economy, as well as the future of AI-driven education startups. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @satyanadella | @Microsoft | @latentspacepod | @swyx Chapters: 00:00 – Satya Nadella Introduction 01:48 – Reflections from Microsoft Build 03:12 – Microsoft’s AI Training Strategy 05:48 – Complexity of Real-World Deployment of AI 07:33 – Augmenting Human Capital 09:37 – Harnesses for Enterprise 11:49 – Developer Value 15:09 – Can Everybody Operate at the Frontier with Their Frontier Intelligence? 15:51 – Modern Definition of IP 17:38 – Future of Vendor vs. Enterprise Agents 21:48 – Near-Term Predictions on Model Pricing 24:02 – Durability of SaaS 25:58 – What Satya’s Building 28:18 – Future of Engineering Roles 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 42:28 – Conclusion
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Building an AI Guardian for Enterprise with Onyx Security CEO Maxim Bar Kogan
May 2800:41:08Summary readyWe are now closer than ever before to living in a world where AI agents are smart enough to run our power grids and manage water supplies. How do we keep them from going rogue? Sarah Guo sits down with Maxim Bar Kogan, founder and CEO of Onyx Securities, to explore the complexities of supervising and securing autonomous agents at the enterprise level. Maxim explains Onyx’s product as an AI control plane, which oversees the permissions and flexible contexts of agents while balancing latency, cost, and reliability. He also discusses how current controls have insufficient context to monitor agent intent, tradeoffs for gradual model rollout, the need for vendor-independent oversight, and Israel’s growing AI and security talent ecosystem. Plus, why Maxim is all-in on AGI. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @maximbarkogan Chapters: 00:00 – Cold Open 00:45 – Maxim Bar Kogan Introduction 01:10 – AutoGPT and Betting on Agent Actions 05:17 – What Onyx Product Does 07:47 – State of Deployment in Large Enterprises 09:58 – Securing Agents 12:45 – Why Proxies Don’t Work 14:11 – Why Onyx Trains Its Own Models 18:38 – Onyx’s Talent Culture 21:24 – Mechanistic Interpretability 23:35 – How Onyx Builds Customer Trust 25:10 – Mitigating Risk at the Foundational Level 27:45 – Phased Rollout of Glasswing and Daybreak 29:11 – Large Enterprise Holdouts 30:46 – Onyx and the Larger AI Security Space 32:36 – Should Labs Address Model Trust and Governance? 36:56 – What Needs to Happen in Security 39:14 – Why Maxim is AGI-Pilled 41:15 – Conclusion
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The Story Behind Cerebras’ $63 Billion IPO with Founder and CEO Andrew Feldman
May 2100:30:33Summary readyCompanies in Silicon Valley from Nvidia to AMD are racing to fuel the AI revolution with postage stamp-sized AI chips. Meanwhile, a chip the size of a dinner plate just fueled a $63 billion IPO for Cerebras. Elad Gil and Sarah Guo sit down with Cerebras founder and CEO Andrew Feldman to discuss the company’s journey to making one of the largest tech go-publics in history. Andrew details the multi-year journey of pioneering wafer-scale AI computing, including surviving a brutal period of being ahead of market demand. He also explains the engineering breakthroughs that led to delivering inference speeds at 20x that of standard GPUs. Andrew then shares how a remarkable $20 billion deal with OpenAI came together in only four weeks. Plus, Andrew’s thoughts on why architecting the future of AI requires the fortitude to be a “professional David” against the Goliaths of tech. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @andrewdfeldman | @Cerebras Chapters: 00:00 – Cold Open 00:36 – Andrew Feldman Introduction 01:19 – Cerebras’ Evolution 02:48 – Wafer-Scale Bet Pays Off 06:38 – Challenges and Breakthroughs 08:37 – Crossing the Market Chasm 10:38 – Scaling Software and Hardware 12:03 – Relevance of AI-Generated Coding 13:31 – Leadership and Hiring Culture 17:16 – When to Quit vs. Persist 19:40 – Why Cerebras Went Public 22:57 – The OpenAI Deal 25:54 – Open Source and Post-Trained Workloads 27:37 – How Speed Opens Up New Business 30:33 – Conclusion
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Pax Silica: Inside the Trump Administration’s Tech Strategy with US Under Secretary of State for Economic Affairs Jacob Helberg
May 1400:38:00Summary readySecuring AI dominance requires more than just semiconductors; it demands a complete overhaul of how the West manages everything that goes into them, from rare earth minerals to actuators. Enter: Pax Silica. Sarah Guo and Elad Gil sit down with US Under Secretary of State for Economic Affairs Jacob Helberg to discuss the launch and expansion of Pax Silica, a 14-country economic security coalition designed to secure the entire AI supply chain. Jacob talks about the creation of a forward-deployed industrial base in the Philippines, where 4,000 acres will be developed into an “economic security zone.” He also compares and contrasts Pax Silica with China’s Belt and Road initiative, explains how the US plans to reindustrialize through automation and robotics, and explores how the Trump administration envisions making these policies durable across future presidencies. Plus, we hear why Jacob believes America to be a “global underdog.” Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jacobhelberg | @UnderSecE Chapters: 00:00 – Cold Open 00:41 – Jacob Helberg Introduction 01:02 – Pax Silica’s Mission 03:51 – Investing in AI Chip Supply Chains 05:43 – Comparing Pax Silica to China’s Belt and Road Initiative 12:38 – Pax Silica’s Value Proposition 14:38 – US vs. Partnered Manufacturing 19:10 – Rare Earth Mineral Pricing 22:16 – Role of Venture Capital in Pax Silica 24:50 – Near vs. Long-Term Priorities 27:09 – Making AI Policy Durable 28:09 – How Policies Impact Entrepreneurs 31:00 – Trump’s Entrepreneurial Administration 33:00 – Why America is a Global Underdog 38:00 – Conclusion
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Amex Global Business Travel: The World’s First AI Take Private with Long Lake CEO Alexander Taubman
May 1100:22:00Summary readyThe world’s first AI-take-private just proved that AI can revolutionize the real economy. Long Lake Management co-founder and CEO Alexander Taubman joins Elad Gil to discuss his firm’s agreement to acquire the legacy platform American Express Global Business Travel (Amex GBT) in a deal valued at $6.3 billion. Alexander explains the mechanics of AI-driven roll-ups, and why Long Lake chooses to acquire and transform businesses rather than simply selling them software. He also talks about how Long Lake’s horizontal AI platform, Nexus, automates workflows across diverse verticals, and how automation through AI not only powers growth for their portfolio companies, but results in both satisfied customers and employees. Plus, they explore Alexander’s vision of Amex GBT as a multi-decade compounding machine. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alextaubman | @amexgbt Chapters: 00:00 – Alexander Taubman Introduction 00:30 – Long Lake’s Nexus Platform 03:35 – Retention and Talent Flywheel 05:01 – Acquisition vs. Offering Software 06:57 – Building Long Lake’s Founding Team 10:37 – Taking American Express Global Business Travel Private 13:36 – Taking Berkshire Hathaway’s Approach to Management 16:37 – How AI Strategy Makes Long Lake Stand Out 19:32 – AI Makes Services Scale 22:00 – Conclusion
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Baseten CEO Tuhin Srivastava on the AI Inference Crunch, Custom Models, and Building the Inference Cloud
May 100:42:57Summary readyBaseten CEO and co-founder Tuhin Srivastava sits down with Sarah Guo and Elad Gil to discuss the rapid growth of AI inference demand, Baseten’s 30x growth, and why inference is becoming the strategic “last market.” Tuhin Srivastava argues the application layer will persist because companies with unique user signals can encode value into workflows and post-train specialized models, citing examples like Abridge and support workflows. The conversation covers GPU capacity constraints, Baseten’s multi-cloud fabric across 18 clouds and 90 clusters, long-term contracting dynamics, the importance of the software layer for stickiness, evolving workloads, multichip possibilities, and operational lessons at scale. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Tuhinone Chapters: 00:31 Baseten growth 01:55 Why the app layer wins 05:57 Serving frontier customers 07:55 Open source model mix 09:21 Chinese models and geopolitics 13:07 Custom inference dominates 14:22 Post training acquisition 17:10 When to invest in custom models 18:35 Supply crunch and data centerse 22:25 Longer GPU Contracts 24:09 What Makes a Winner 26:07 Multi Chip Future 28:19 Runtime Roadmap 31:08 Scaling Edge Cases 33:48 Hiring and Leadership 36:44 Operations Pager Culture 38:19 Efficiency Drives Demand 40:41 Concierge Everything Future 42:34 Conclusion
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