No Priors: Artificial Intelligence | Technology | Startups

AI agents can already collaborate, but they lack a trustworthy medium in which to store value and execute contracts. Enter Circle’s Arc Blockchain, an economic “operating system” designed for a world where machines drive the real economy. Circle co-founder and CEO Jeremy Allaire joins Elad Gil to dive into the future of programmable money and the agentic economy. Jeremy explains why traditional banking fails to support the needs of AI agents, and how stablecoins like USDC facilitate an internet-native economy. They also discuss the tokenization of real-world assets, the move toward full-reserve banking, and Jeremy’s predictions for double-digit GDP growth as AI and blockchain reach their “broadband moment.”  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jerallaire | @circle Chapters: 00:00 – Cold Open 00:05 – Jeremy Allaire Introduction 00:21 – Origin Story of Circle 02:11 – Rethinking the Financial System 05:26 – The Role of Stablecoins 09:52 – Use Cases for USDC 11:30 – Programmable Money  12:25 – Blockchain as Operating System 14:37 – The Agentic Economy 17:45 – Arc Blockchain Use Cases 27:00 – Scaling Models and Privacy Tech 30:45 – Securitization of Other Assets Under the Blockchain 34:16 – Prediction Markets 35:09 – Incremental Revenue Through GPU Usage 37:19 – Jeremy’s 10 Year Future Vision 41:12 – AI and GDP 44:00 – Conclusion

What happens when you apply the scaling laws of large language models to the physical work of atoms? Elad Gil sits down with Liam Fedus, co-founder at Periodic Labs, which is pioneering an AI foundation lab for atoms. Liam discusses how he pivoted from dark matter physics research to the front lines of artificial intelligence, including stints at Google Brain and working on ChatGPT at OpenAI. He talks about how Periodic is connecting massive language models to the physical world to overcome data bottlenecks in material science. Liam also shares how they use language models as an orchestration layer operating alongside specialized neural nets to run closed-loop physical experiments. They also explore the future of AGI and ASI, as well as the role of robotics in lab automation. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LiamFedus | @periodiclabs Chapters: 00:00 – Cold Open 00:05 – Liam Fedus Introduction 00:39 – Liam’s Background at Google Brain, OpenAI 05:14 – From ChatGPT to Materials and Atoms 06:34 – Training Data in the Physical World 09:52 – Generalization Across Domains 11:31 – Models as an Orchestration Layer 12:48 – Commercialization and Business Model 16:10 – How Periodic’s Success May Shape the Future  17:45 – Multidisciplinary Scaling 19:41 – Capital and Compute 21:12 – Hiring at Periodic 21:44 – Thoughts on AGI and ASI 23:30 – Timeline for Machine-Directed Self-Improvement 25:39 – Automation and Data Generation 27:59 – Why Liam is Excited About the Future of Robotics 29:25 – Conclusion

What happens when AI agents can design experiments, collect data, and improve — without a human in the loop? Andrej Karpathy joins Sarah Guo on the state of models, the future of engineering and education, thinking about impact on jobs, and his project AutoResearch: where agents close the loop on a piece of AI research (experimentation, training, and optimization, autonomously). 00:00 Andrej Karpathy Introduction 02:55 What Capability Limits Remain? 06:15 What Mastery of Coding Agents Looks Like 11:16 Second Order Effects of Natural Language Coding 15:51 Why AutoResearch  22:45 Relevant Skills in the AI Era 28:25 Model Speciation 32:30 Building More Collaboration Surfaces for Humans and AI 37:28 Analysis of Jobs Market Data 48:25 Open vs. Closed Source Models 53:51 Autonomous Robotics 1:00:59 MicroGPT and Agentic Education 1:05:40 Conclusion

Notion isn’t designing AI agents that just use tools. Their agents can autonomously build their own integrations, as well as write the code needed to finish a task. Sarah Guo sits down with Notion Co-Founder Simon Last to explore Notion’s rapid evolution from a simple writing assistant to a sophisticated platform for custom AI agents. Simon discusses the technical hurdles of indexing disparate data from sources like Slack and Google Drive, as well as the internal shift toward using coding agents to build Notion itself. Plus, Simon elaborates on what he sees as a fundamental transition in productivity: moving from a tool where humans do the work, to one where humans manage a swarm of agents. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @simonlast | @NotionHQ Chapters: 00:00 – Cold Open 00:05 – Simon Last Introduction 00:26 – Genesis of Notion AI 04:10 – Challenge of Semantic Indexing and Retrieval 07:16 – The Six-Month Rewrite Cycle 08:12 – Notion’s Coding Agent Era 09:44 – Impact on Team Dynamics 12:49 – Launching Custom Agents 15:39 – Notion as the ‘Switzerland’ for Models 17:33 – Designing APIs for Agent Customers 20:09 – Simon’s Personal Agentic Workflows 24:48 – Notion: Tool for Work is Now A Tool for Agents 27:28 – How Building Has Changed for Simon 29:00 – Conclusion

By the end of 2026, AI capital expenditure is projected to hit nearly $700 billion. The question isn’t who has the best model, but who has the most creative financing to build out AI infrastructure and beyond. Sarah Guo is joined by Neil Tiwari, Managing Director at Magnetar Capital, a financial innovator helping the AI industry scale from billions to trillions of dollars in CapEx. Neil explains some of the debt structures used to finance massive GPU clusters, who is taking the risk, and how the industry is maturing. Sarah and Neil also discuss how power distribution, energy storage, and physical materials like steel are the bottlenecks of the AI industry. Plus, Neil gives his take on the future of inference-optimized clouds, and why the market shift away from software and into infrastructure might be an overreaction. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Cold Open 00:05 – Neil Tiwari Introduction 00:26 – Magnetar’s Story 01:28 – Why CoreWeave Helped Magnetar Win 06:15 – Scaling CapEx Efficiently 09:02 – Debunking GPU Collateral Risk 11:42 – How Deal Structures Evolve 13:01 – What Bottlenecks Buildout 15:28 – Circular Financing Critiques 17:35 – The Shift from Training to Inference Workloads 23:10 – AI Factories 24:12 – Constraints of the Current Power Grid 28:27 – Sovereign Compute Buildouts 29:54 – Physical AI Capital Needs 32:48 – The Capital Rotation Away from SaaS 36:04 – Conclusion

In this episode of No Priors, Sarah and Elad dive into the evolving landscape of software, exploring how AI is transforming the traditional SaaS model. They discuss whether SaaS as we know it is coming to an end, what new business and sales strategies are emerging, and how AI is reshaping the way software is built, sold, and scaled. The conversation also examines whether or not these shifts are a good thing for both big and small companies, and how coders and software experts are reacting to abrupt AI transitions. They also dig into how AI is reshaping sales, automating workflows, and enabling more predictive customer strategies. Beyond individual companies, they examine how tech giants are increasingly dominating the S&P 500, and what this concentration of power means for the future of startups, innovation, and the broader entrepreneurial ecosystem. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil |  Chapters: 00:00 – Cold Open 00:35 – The SaaS-polcalypse discussion  4:55 – AI Change Management in Large vs. Small Companies 05:43 – “Is Software Eating the World?”  08:38 – Addressing the Unsolved Problems  14:00 – The Noise of the Last Month vs. Excitement  21:32  – What Proportion of GDP is Tech?  23:20 – Market Cap Shifts 25:02 – As a Company, When Should You Sell?  29:05 – Multi-Product Bundle Defense  30:45 – Conclusion

Autonomous vehicle technology has moved past human-coded rules and into an era of neural networks and custom computer chips. And to solve the most difficult driving scenarios, electric vehicle company Rivian abandoned its original technology platform to build a vertically integrated data stack. Sarah Guo sits down with Rivian Founder and CEO RJ Scaringe to explore the seismic shift in the automotive industry toward AI-driven, software-defined vehicles . RJ discusses the move away from function or domain-based architecture for vehicle electronic systems to software-defined architecture, which allows for dynamic, monthly updates to features in Rivian’s vehicles. RJ also talks about the upcoming launch of Rivian’s R2 model, which aims to be a distinct, affordable, mass-market alternative to the Tesla Model Y. Plus, RJ shares his vision for a future where vehicles don’t just drive us, but inspire personal freedom and exploration. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @RJScaringe | @Rivian  Chapters: 00:00 – Cold Open00:35 – RJ Scaringe Introduction0:58 – Rivian’s Autonomy Evolution05:19 – Why Rivian’s Tech is Vertically Integrated10:06 – Levels of Autonomous Driving Technologies14:00 – Importance of a Software-Defined Architecture19:28 – Differentiating Autonomous Vehicle Models23:20 – R2: The First Mass Market Autonomous Vehicle25:02 – Do Americans Want EVs?29:05 – How Our Relationship to Vehicles is Evolving30:45 – Conclusion

From “virtual doppelgängers” to “real-time dreaming,” online gaming platform Roblox is using AI technology to build the “Holodeck” envisioned in science fiction decades ago. Sarah Guo and Elad Gil sit down with Roblox CEO Dave Baszucki at Roblox headquarters to explore the intersection of AI, physics simulation, and the future of human connection. Dave discusses the evolution of the 4D creation tool in Roblox, a high-fidelity simulation that enables thousands of people to interact in real-time with photo-realistic graphics and acoustic physics. Dave reveals how Roblox is leveraging 13 billion hours of monthly user data to train native AI models that go beyond simple LLMs, enabling NPCs that can navigate and play games with human-like intuition. He also talks about how immersive communication will change video conferencing, how Roblox searches for unlikely talent outside of traditional elite universities, and how he balances rapid weekly iterations with keeping a “long view” on Roblox’s vision.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @DavidBaszucki | @Roblox  Chapters: 00:00 – Cold Open 00:36 – Dave Baszucki Introduction 01:16 – Realizing Robolox’s 20-Year Vision 05:29 – Using 4D Immersive Simulations in Virtual Interactions 08:22 – Physics Engine vs. Photorealism  11:50 – Storing Roblox History as Vector Data 14:00 – Training NPCs - Moving Beyond LLMs 18:05 – The Future of the Game Designer 19:54 – Video Latent World Models 23:53 – Social Simulation - AI Companions and Virtual Relationships 27:26 – Why Asset Costs Haven’t Changed the Gaming Industry 29:52 – AI Coding in Roblox Studio 31:36 – The Roblox Creator Economy 33:57 – Long-Term Conviction vs. Weekly Iteration 37:50 – Dave’s Hiring Philosophy for Roblox 43:44 – Conclusion

What if we could pause biological time to wait for a cure for a disease? Thanks to innovations and research in reversible cryopreservation, this possibility is no longer just science fiction. Sarah Guo sits down with Laura Deming, CEO and co-founder of biotech startup Until, to dive deep into the growing field of reversible cryopreservation. Laura talks about how her time as a Thiel Fellow as well as her founding of the Longevity Fund fueled her obsession with solving the “social blindspot” of aging. Laura details how her new startup, Until, seeks to build tools that allow for “pressing pause” on biological time, starting with human organs with the hopes of scaling up to full body medical hibernation. Together, they also discuss why ice is the enemy of tissue, using engineering tools to help solve biological problems, and how this technology may revolutionize organ transplantation by removing time as a variable.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LauraDeming | @untillabs  Chapters: 00:00 – Cold Open 01:08 – Laura Deming Introduction 01:53 – Why Laura Focused on Cryo Preservation and Longevity 06:20 – Bringing on Co-Founder Hunter Davis 07:55 – Until’s Goal 10:10 – Other Use Cases for Cryo Technology 12:22 – Scientific Challenges in Cryo Tech 15:36 – Using Engineering Principles to Solve Biological Problems 20:18 – Scaling Up Cryo Preservation 21:48 – Leading and Recruiting at Until 25:02 – Why Hasn’t Cryo Tech Been Worked On More? 27:14 – Making Time Not a Variable in Organ Transplants  29:06 – Changing How the Molecular World is Depicted 30:47 – Conclusion

Why are there only a handful of companies in the world with over $10 billion in pure-play software revenue? CJ Desai believes the reason is that products are replaceable, but platforms are forever. For No Priors’ very first live from MongoDB.local SF, Sarah Guo is joined by CJ Desai, CEO and President of software developer MongoDB, to discuss the shifting landscape of enterprise software. CJ discusses whether AI will erode the value of software, and what truly constitutes a “moat” in the age of generative AI. CJ also talks about why AI adoption with Fortune 500-sized companies is still lagging, the importance of customer relationships, and why the “bear thesis” on SaaS may be overblown.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @cj_mongodb | @MongoDB Chapters: 00:00 – Cold Open 00:58 – CJ Desai Introduction 01:38 – The AI Stack and the Future of Software 04:18 – Why Platforms, Not Products, Are Sticky 09:59 – Vibe Coding and the Threat of On-Demand Apps 12:15 – Paths to Success for Software Vendor Incumbents 14:24 – How CJ Chose MongoDB 18:55 – Debunking the SaaS Bear Thesis 22:07 – Fortune 500 Perspectives on AI Value 24:24 – Can AI Native Startups Replace Systems of Record? 28:10 – The Importance of Customer Relationships 31:46 – Managing Through Massive Technology Transitions 36:37 – Conclusion

Today’s arms race looks a little different from those of the past. Under the Trump administration, the US Department of War (DoW) is deploying generative AI to millions of employees in order to maintain a strategic edge over our global adversaries. Sarah Guo and Elad Gil sit down with Emil Michael, the Under Secretary of War for Research and Engineering of the United States, to discuss the radical technological transformation of the US military. Emil outlines the architecture and launch of GenAI.mil, a DoW internal AI platform powered by Gemini and Grok that reached over one million unique users in its first 30 days. He also highlights critical technology priorities for national security, including hypersonics, direct energy, and autonomous drone swarms. Together, they also explore the urgent need to rebuild the American defense industrial base and end dependency on foreign supply chains for critical materials, as well as how Emil is recruiting the next generation of “fixer-builder” workers to serve their country in government.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @USWREMichael | @DoWCTO Chapters: 00:00 – Cold Open 00:00 – Emil Michael Introduction 00:58 – Emil’s Role at the Department of War 05:22 – Innovation Priorities for the DoW 08:27 – Shift Toward Autonomous Defense Technologies 10:41 – Identifying Common Needs Across the DoW 12:02 – Architecting GenAI.mil 13:48 – Applied AI Initiatives at the DoW 15:57 – The Future of Warfare 17:55 – Recruiting for DoW 19:33 – Arsenal of Freedom Tour 22:25 – Opportunities for Entrepreneurs at DoW 25:49 – Speeding Up and Scaling DoW Initiatives 28:37 – Innovation in Defense Tech 30:00 – Change Management in Government 32:09 – Rebuilding the Defense Industrial Base 37:27 – Initiatives and Opportunities at the Office of Strategic Capital 41:41 – Lessons from Emil’s Government Experience 44:30 – Conclusion

Even if ChatGPT never existed, the tech giant NVIDIA would still be winning. The end of Moore’s Law—says NVIDIA President, Founder, and CEO Jensen Huang—makes the shift to accelerated computing inevitable, regardless of any talk of an AI “bubble.” Sarah Guo and Elad Gil are joined by Jensen Huang for a wide-ranging discussion on the state of artificial intelligence as we begin 2026. Jensen reflects on the biggest surprises of 2025, including the rapid improvements in reasoning, as well as the profitability of inference tokens. He also talks about why AI will increase productivity without necessarily taking away jobs, and how physical AI and robotics can help to solve labor shortages. Finally, Jensen shares his 2026 outlook, including why he’s optimistic about US-China relations, why open source remains essential for keeping the US competitive, and which sectors are due for their “ChatGPT moment.”  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @nvidia Chapters: 00:00 – Jensen Huang Introduction 00:17 – Biggest AI Surprises of 2025 04:12 – AI and Jobs: New Infrastructure and Demand for Skilled Labor 09:03 – Task vs. Purpose Framework in Labor 12:31 – Solving Labor Shortages with Robotics 15:14 – The Layer Cake of AI Technology 18:39 – The Importance of Open Source 21:52 – The Myth of “God AI” and Monolithic Models 23:54 – Addressing the “Doomer” Narrative and Regulation 29:25 – The Plummeting Cost of Compute and Tokenomics 35:09 – The Return to Research 37:49 – Future of Coding and Software Engineering 43:20 – The Industries Due For Their “ChatGPT” Moments 46:00 – The Evolution of Self-Driving Cars and Robotics 54:06 – Energy Demand and Growth for AI 58:49 – 2026 Outlook: US-China Relations and Geopolitics 1:04:43 – Is There An AI Bubble? 1:16:20 – Conclusion

Pundits are screaming about the so-called “AI bubble.” But historically slow-to-adopt industries like medicine and law are actually embracing AI at an unprecedented speed. Sarah Guo and Elad Gil look ahead to 2026, breaking down the major trends that will define the next era of AI technologies. They explore the future of AI foundational models, predicting breakthroughs in solving complex scientific problems. They share competing views on the timeline for robotics and self-driving cars, debating whether startups have a chance for survival or if incumbents will dominate. Elad and Sarah also discuss the return of tech IPOs and M&As, forecast a new wave of AI consumer agent software, and explore why consumer product innovation has been slower than expected. Finally, the two offer bold non-AI predictions for the new year, including the acceleration of defense tech startups and the second-order underrated impacts of GLP-1 drugs on biohacking. Plus, stick around to hear predictions on what’s next for AI in 2026 from some of tech’s biggest names and industry leaders. We hear from Jensen Huang (Founder/CEO NVIDIA), Arvind Jain (Founder/CEO, Glean), Winston Weinberg (Founder/CEO, Harvey), Scott Wu (Founder/CEO, Cognition), Raiza Martin (Founder/CEO Huxe), Zach Ziegler (Founder/CTO, Open Evidence), Aaron Levie (Founder/CEO, Box), Misha Laskin (Founder/CEO, ReflectionAI), Noam Brown (Research Scientist, OpenAI), Joshua Meier (Founder/CEO Chai Discovery), Bryan Johnson (Living Man, Don't Die), Sholto Douglas (Member of the Technical Staff, Anthropic), Ben & Asher Spector (Stanford PhDs) and Dylan Patel (Founder/CEO SemiAnalysis). Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Introduction 02:43 – AI Predictions for 2026 04:40 – Adoption of AI in Professional Fields 07:17 – Robotics and Self-Driving Cars 08:25 – Robotics: Incumbents vs. Startups 13:59 – Future of IPOs and M&A in AI 16:42 – Challenges in Consumer AI Innovation 21:08 – Funding of Neo Labs, RL Research 26:28 – Predictions for 2026 Beyond AI 26:44 – The Future of Defense and Technology 28:23 – Biohacking and Peptide Therapies 30:37 – 2026 Prediction from AI Industry Leaders 40:46 – Conclusion

Imagine learning chess from a grand master, or negotiating tactics from an expert FBI hostage negotiator. ElevenLabs’ voice AI technology is making that unlock possible. Sarah Guo sits down with Mati Staniszewski, co-founder of ElevenLabs, to explore how the three-year old company is transforming how humans interact with technology through voice. Mati talks about the technical challenges of building foundational audio models, the strategic thinking between conducting research and deploying products in tandem, and why voice is the ultimate interface for everything from computers to robots to immersive media. They also discuss how the coming revolution of AI personal tutors will shift agentic AI from reactive to proactive support, break down language barriers globally, and even provide the framework for agentic government services. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @elevenlabsio |@matiii Chapters: 00:00 – Mati Staniszewski Introduction 00:46 – 11 Labs: Growth and Scale 02:46 – Voice Technology and Applications 06:52 – Research and Product Development 12:36 – Voice Quality and Customer Preferences 17:54 – Agent Platform and Use Cases 23:21 – Choosing the Right Technology Partner 26:43 – The Role of Foundation Models 29:58 – Open Source Models and Future Trends 32:37 – Research and Development Focus 36:53 – Future of AI Companions and Education 41:37 – Conclusion

In just over three years, Harvey has not only scaled to nearly one thousand customers, including Walmart, PwC, and other giants of the Fortune 500, but fundamentally transformed how legal work is delivered. Sarah Guo and Elad Gil are joined by Harvey’s co-founder and president Gabe Pereyra to discuss why the future of legal AI isn’t only about individual productivity, but also about putting together complex client matters to make law firms more profitable. They also talk about how Harvey analyzes complex tasks like fund formation or M&A and deploys agents to handle research and drafting, the strategic reasoning behind enabling law firms rather than competing with them, and why AI won’t replace partners but will change law firm leverage models and training for associates. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @gabepereyra | @Harvey Chapters: 00:00 – Gabe Pereyra Introduction 00:09 – Introduction to Harvey 02:04 – Expanding Harvey’s Reach 03:22 – Understanding Legal Workflows 06:20 – Agentic AI Applications in Law 09:06 – The Future Evolution of Law Firms 13:36 – RL in Law 19:46 – Deploying Harvey and Customization 23:46 – Adoption and Customer Success 25:28– Why Harvey Isn’t Building a Law Firm 27:25 – Challenges and Opportunities in Legal Tech 29:26 – Building a Company During the Rise of Gen AI 37:24 – Hiring at Harvey 40:19 – Future Predictions 44:17 – Conclusion 

The robotics industry is on the cusp of its own “GPT” moment, catalyzed by transformative research advances. Enter Memo, the first general-intelligence personal robot, focused on taking on your chores to give back your time. Sarah Guo sits down with Tony Zhao and Cheng Chi, co-founders of Sunday Robotics, to discuss the state of AI robotics. Tony and Cheng speak to the challenges they faced while developing their technology, the innovative glove system employed to scale real-world data collection, and the impact of diffusion policy and imitation learning. Plus, they talk about their 2026 in-home beta program and why personal robots are only a handful of years away from mass deployment. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tonyzzhao | @chichengcc | @sundayrobotics Chapters: 00:00 – Tony Zhao and Cheng Chi Introduction 00:56 – State of AI Robotics 02:11 – Deploying a Robot Pre-AI 03:13 – Impact of Diffusion Policy  04:29 – Role of ACT and ALOHA 07:02 – Imitation Learning - Enter UMI 10:38 – Introducing Sunday 11:57 – Sunday’s Robot Design Philosophy 15:05 – Sunday’s Shipping Timeline 19:02 – Scale of Sunday’s Training Data 23:58 – Importance of Data Quality at Scale 24:56 – Technical Challenges 27:59 – When Will People Have Home Robots? 30:48 – Failures of Past Demos 32:34 – Sunday’s Demos 36:53 – What Sunday’s Hiring For 39:10 – Conclusion

Bringing new drugs to market is a costly, time-consuming endeavor. On top of that, most medicines fail at some point in the research and development phase. Sarah Guo is joined by Sajith Wickramasekara, co-founder and CEO of Benchling, a company that has not only become the central system of record for biotech R&D, but uses AI agents to assist scientists to help fix this broken system. Sajith details the roadblocks that impede drug development and approval, the “dot com” bust occurring in biotech, and how AI agents and simulation can help scientists experiment faster. Plus, they talk about China’s competitive rise in the pharma space, and the unique challenges of building an interdisciplinary culture that merges the worlds of science and software.  Rebuild biotech for the AI era - Sajith Wickramasekara Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @sajithw | @benchling Chapters: 00:00 – Sajith Wickramasekara Introduction 00:38 – Origin and Mission of Benchling 02:08 – The Drug Development Process 03:49 – Current State of the Biotech industry  08:46 – AI’s Role in Biotech 16:14 – Benchling AI and Its Impact 18:36 – The Future of AI in Biotech  26:28 – Debunking AI Drug Discovery Myths 28:50 – Data’s Role in Biotech 29:35 – The Importance of Tools in Pharma 31:28 – AI’s Impact on Scientific Research 34:55 – Building a Biotech Company 40:18 – Interdisciplinary Collaboration in Biotech  43:06 – Tech and Biotech: Learning from Each Other 48:16 – Conclusion

Snowflake is moving beyond the data warehouse. Its new Snowflake Intelligence is an agentic platform for every employee, not just data teams. Sarah Guo sits down with Snowflake CEO Sridhar Ramaswamy to discuss his first 18 months at the helm, as well as the massive pivot to make the data giant AI-first. Sridhar talks about Snowflake Intelligence, the company's new AI agent platform, and its implications for enterprise data management. They also explore how Sridhar navigates partnerships with major tech companies, how he fosters a culture of continuous improvement within the organization, and how he envisions Snowflake’s future as an integral data-driven enterprise solution.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Snowflake Chapters: 00:00 – Sridhar Ramaswamy Introduction 00:42 – Snowflake’s Market Adaptation 03:14 – Snowflake’s Evolution and AI Integration 05:44 – Introducing Snowflake Intelligence 09:01 – Snowflake Intelligence User Experience 11:55 – Drawing the Line Between Data, Agent System, and App 13:30 – Leadership and Organizational Changes 16:19 – How Being an Investor, Entrepreneur Informed Sridhar’s Leadership 18:50 – Importance of Product-Market Fit 22:46 – Snowflake’s Strategic Positioning 27:10 – Snowflake’s Partnership Strategy 30:20 – How Sridhar Sees the ROI of AI 35:09 – How AI Changes the Ad Model 38:15 – Why LLMs Still Need Search 42:11 – Conclusion

2025 has thus far been a year of great leaps and advances in AI technology. And Sarah and Elad have spoken with some of the most enterprising founders and scientific minds in the field of AI today. So we’re revisiting a few of our favorite conversations on No Priors so far in 2025 – Winston Weinberg (Harvey), Dr. Fei-Fei Li (World Labs), Brendan Foody (Mercor), Dan Hendrycks (Center for AI Safety), Noubar Afeyan (Flagship Pioneering), Brandon McKinzie and Eric Mitchell (OpenAI o3), Isa Fulford (OpenAI), Arvind Jain (Glen), and Dr. Shiv Rao (Abridge).  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Episode Introduction 0:21 – Winston Weinberg on Leaning into New Capabilities 02:01 – Dr. Fei-Fei Li on Spatial Intelligence 04:13 – Brendan Foody on AI Disruption in the Workforce 06:10 – Dan Hendrycks on the Geopolitics of Superintelligence 08:06 – Noubar Afeyan on Entrepreneurship   10:38 – Brandon McKinzie and Eric Mitchell on Reasoning Models 12:41 – Isa Fulford on Training Deep Research 13:49 – Arvind Jain on Innovating Enterprise Search 16:21 – Dr. Shiv Rao on AI’s Human Impact 18:58 – Conclusion

For decades, the developer terminal has remained largely unchanged. But for Warp CEO and co-founder Zach Lloyd, reinventing this core tool is the key to unlocking AI agents for coding, debugging, and automating the entire development process. Zach joins Elad Gil to discuss how seeing this opportunity for innovation led to Warp’s agentic terminal for developers. Zach talks about the phases of software development, from coding by hand to the current "develop by prompt" era, and the coming age of fully automated development. Plus, Zach and Elad explore the deep philosophical questions around intelligence versus consciousness in AI models, and what it would take to believe a computer program is truly aware. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @zachlloydtweets | @warpdotdev Chapters: 00:00 – Zach Lloyd Introduction 00:32 – AI, Intelligence, and Consciousness 06:55 – What Warp Does 07:38 – Benefits of the Terminal as a Launchpoint  08:27 – Features Driving Warp’s Adoption 09:12 – Zach’s View of the Coding Market 10:27 – Evolution of Coding Development 12:45 – Importance of Senior Engineer Expertise 14:11 – Future of Security and Other Dev Tools 22:22 – Why Zach Focused on the Terminal 23:52 – The Future of the Model Layer  25:36 – What Zach’s Excited About in the AI Dev World 27:18 – Conclusion

With demand from AI for energy already exploding, our electric grid is facing a crisis. Base Power CEO and co-founder Zach Dell is ready to re-architect its future from the ground up. Zach sits down with Elad Gil to talk about Base Power’s recent $1 billion fundraise from major investors. Zach discusses the role of energy across industries, as well as Base Power's mission to lower electricity costs through vertical integration. Zach and Elad also explore the future of energy, the role of batteries in transforming the grid, and the regulatory challenges facing the energy industry. Plus, Zach pitches why top talent should make their careers in energy generation.   Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ZachBDell | @basepowerco Chapters: 00:00 – Zach Dell Introduction 00:50 – Base Power’s Vision 02:15 – Base Power’s Products and Services  04:00 – What Drew Zach to Working on Power 05:12 – Base Power’s Founding Team 06:58 – Base Power’s Hiring Needs 08:02 – How Zach Hired an Awesome Founding Team 09:51 – How Do We Meet Energy Demands? 12:58 – How Viable is Nuclear Energy? 17:04 – Global Energy Cost Dynamics 17:41 – Future of AI Training Centers 18:32 – What Will Drive Energy Buildout 20:38 – Drivers of Energy Transmission Cost 22:30 – Regulation and the Energy Industry  23:52 – What Zach is Optimistic About in Energy 24:42 – Cultivating Base Power’s Culture 27:26 – Zach’s Philosophy on Capitalization 30:00 – How Base Power Uses Scale 31:57 – Conclusion

The AI industry is obsessed with making models smarter. But what if they’re building the wrong kind of intelligence? In launching his new venture, humans&, Eric Zelikman sees an opportunity to shift the focus from pure IQ to building models with EQ. Sarah Guo is joined by Eric Zelikman, formerly of Stanford and xAI, who shares his journey from AI researcher to founder. Eric talks about the challenges of building human-centric AI, integrating long-term memory in models, and the importance of creating AI systems that work collaboratively with humans to unlock their full potential. Plus, Eric shares his views on abunance and what he’s looking for in talent for humans&. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ericzelikman Chapters: 00:00 – Eric Zelikman Introduction 00:29 – Eric’s Early Interest in AI 01:29 – Challenges in AI and Automation 02:25 – Research Contributions 06:14 – Q-STaR and Scaling Up AI 08:14 – Current State of AI Models 15:23 – Human-Centric AI and Future Directions 22:08 – Eric’s New Venture: humans& 35:33 – Recruitment Goals for humans& 36:57 – Conclusion

Between the future of search, the biggest threats in cybersecurity, and the jobs and platforms of tomorrow, Nikesh Arora sees one common thread connecting and transforming them all—AI. Sarah Guo and Elad Gil sit down with Nikesh Arora, CEO of cybersecurity giant Palo Alto Networks and former Chief Business Officer of Google, to talk about a wide array of topics from agentic AI to leadership. Nikesh dives into the future of search, the disruptive potential of AI agents for existing business models, and how AI has both compressed the timeline for cyberattacks as well as fundamentally shifted defense strategies in cybersecurity. Plus, Nikesh shares his leadership philosophy, and why he’s so optimistic about AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @nikesharora | @PaloAltoNtwks Chapters: 00:00 – Nikesh Arora Introduction 00:39 – Nikesh on the Future of Search 04:46 – Shifting to an Agentic Model of Search 08:12 – AI-as-a-Service 16:55 – State of Enterprise Adoption 20:15 – Gen AI and Cybersecurity 27:35 – New Problems in Cybersecurity in the AI Age 29:53 – Deepfakes, Spearfishing, and Other Attacks 32:56 – Expanding Products at Palo Alto 35:49 – AI Agents and Human Replaceability 44:28 – Nikesh’s Thoughts on Growth at Scale 46:52 – Nikesh’s Leadership Tips 51:14 – Nikesh on Ambition 54:18 – Nikesh’s Thoughts on AI 58:21 – Conclusion

What if kids could master their academics in just two hours a day and spend the rest of their time developing real-world skills they’re passionate about? Joe Liemandt, founder of the software company Trilogy, is doing just that. Sarah Guo and Elad Gil are joined by Joe Liemandt, principal of Alpha School, to discuss his AI-driven vision of reinventing K-12 education. Joe talks about the strategies that Alpha School employs: reducing the traditional six-hour school day to two, replacing teachers with “Guides,” using financial incentives as motivation, and dedicating the remainder of the school day to project-based workshops that reflect the students’ passions. Together, they also examine Joe’s plan to scale Alpha School, the youth mental health crisis, and why edtech so far has failed. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AlphaSchoolATX Chapters: 00:00 – Joe Liemandt Introduction 00:27 – From Trilogy to Alpha School 02:45 – How Joe Changed His Mind About Alpha School 04:16 – Reenvisioning the School Day 09:06 – An Example Day at Alpha School 20:13 – Educating Based on Motivations 22:56 – Incentives-Based Learning 24:40 – Standards for Guides 26:39 – Extrinsic vs. Intrinsic Motivators 35:12 – Tackling Learning Differences  39:13 – Alpha School Pricing Structure 43:08 – Education Tech at Alpha School 44:54 – Rebuilding Education in the AI Age 48:43 – Reforming Education Policy 56:25 – Ed Tech as a Product 58:58 – Fixing Gaps in Education 59:45 – Why Education is Joe’s Mission 01:01:49 – Conclusion

The traditional call center may soon be a thing of the past. Jessie Zhang is building AI agents designed to replace monotonous human labor and transform how consumers interact with brands. Elad Gil sits down with Jesse Zhang, co-founder and CEO of Decagon, an AI agent company at the forefront of AI customer service. Jesse talks about how Decagon secured large enterprise clients and the impact of its AI agents, his journey as a second-time founder, and Decagon’s company culture. Plus, they discuss what the future of agentic customer service may look like. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @thejessezhang | @DecagonAI  Chapters: 00:00 – Jesse Zhang Introduction 00:30 – Decagon’s Services 01:11 – Decagon’s Customers and Growth 02:41 – Productivity Gains with Decagon 03:33 – How Decagon Integrates in Customer Workflows 04:25 – Jesse’s Second Time Founder Story 05:41 – Jesse’s Hiring Philosophy 09:13 – Counter-intuitive Advice for Founders 11:19 – How Decagon Thinks About Talent 14:12 – Areas for Longer Term Planning 15:37 – Decagon’s Path to Customer Service 16:57 – Thoughts on Pushing Into the Application Layer 19:40 – What Decagon Does Uniquely  22:05 – Pricing Services in the AI Age 24:46 – How Decagon Sees Customer Service 25:53 – Defining Long-Term Success for Decagon 27:41 – Jesse’s Views on an Agentic Future 31:22 – Conclusion

From negotiating with world leaders to partnering with top entrepreneurs, businessman and investor Jared Kushner has traveled the unique path of bringing private sector knowledge to government work and back again. Jared Kushner joins Sarah Guo and Elad Gil to cover a wide range of topics, from his founding of investment firm Affinity Partners, to his time in government, to his new AI venture BrainCo. Jared discusses Affinity Partners’ mission and strategy, how he has leveraged his government experience in business and investing, and the geopolitics of technological advancements like AI. Plus, he makes a case for why private sector talent should do “tours of duty” in government. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jaredkushner Chapters: 00:00 – Jared Kushner Introduction 00:30 – Starting Affinity Partners Post-Government 01:59 – Value of Global Perspective 03:34 – Ventures with Affinity 05:14 – Evaluating Investments Via Macro Trends 09:09 – Undervalued Countries 12:32 – Origins of BrainCo 16:50 – BrainCo Use Cases 23:49 – BrainCo’s Biggest Challenge 24:47 – Determining Customer Fit 26:39 – AI and Policy 30:03 – Middle East and AI 31:59 – Jared’s Experience in Middle East Diplomacy 40:16 – Brokering Peace Post-October 7th 43:52 – Making Deals with Middle Eastern Partners 47:14 – Jared and Ivanka’s Partnership 49:18 – Benefits of Joining Public Sector from the Private Sector 52:07 – Jared’s Pitch for Serving in Government 56:25 – Jared’s Leadership Style 58:24 – Conclusion

How does a new technology get adopted by 40% of American doctors in just 18 months? In an era where the golden age of biotechnology has also created a dark age of physician burnout, OpenEvidence found the answer by fundamentally changing how doctors access critical information. OpenEvidence founder Daniel Nadler sits down with Sarah Guo and Elad Gil to discuss how his company solved the semantic search problem in medicine. He talks about the strategy of treating doctors as consumers, striking the balance of keeping patients in the loop in medical conversations, and how technology will reshape both medicine and medical education. Plus, Daniel gives his thoughts on the roots of motivation, as well as his philosophy for recruitment.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EvidenceOpen  Chapters: 00:00 – Daniel Nadler Introduction 00:08 – OpenEvidence’s Success  01:54 – How OpenEvidence Works 06:35 – Dealing with Ambiguity 11:37 – Treating Knowledge Workers as Consumers 15:53 – Balancing Keeping Patients in the Loop 19:28 – How Technology May Shape the Future of Medicine 22:12 – How Technology Will Change Medical Education 30:40 – Examining Consumer Adoption of Preventative Health Measures 36:02 – Lessons for Other Fields 37:27 – Rationalism vs. Will 41:13 – Daniel’s Thoughts on Motivation 42:44 – Daniel’s Recruiting Philosophy 44:48 – Conclusion

AI doomers say that the technology will be the ultimate job-killer. But Jacob Helberg wants people to see AI as a tech that will boost, not replace, human workers and give them superpowers. Under Secretary of State for Economic Growth, Energy, and the Environment Jacob Helberg joins Sarah Guo and Elad Gil to talk about AI’s role in reshoring manufacturing in America, supply chain security, and transforming the US energy grid. He also discusses the CapEx revolution, why he sees opportunity for tech and energy partnerships in the Middle East, and the path to more nuclear energy for the US. Plus, the three explore what the “superintelligence century” could look like. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jacobhelberg  Chapters: 00:00 – Jacob Helberg Introduction 00:50 – Jacob’s Agenda for Capitol Hill 01:53 – Reshoring the American Supply Chain 04:38 – Areas of CapEx Growth 06:56 – Importance of Supply Chain Security 08:52 – Reshoring Rare Earth Minerals 11:12 – How AI Can Help America Reindustrialize  15:37 – AI and Productivity Gains 17:38 – The Superintelligence Century 22:56 – Creating an Open Source AI Ecosystem 24:41 – The Middle East and AI 26:24 – Growing Energy Resources in the US 28:28 – The Path to More Nuclear Energy in the US 35:50 – Essential Domains for Strategy and Security 38:20 – The Tech Industry and the Administration 40:29 – Conclusion

Andrew Ng has always been at the bleeding edge of fast-evolving AI technologies, founding companies and projects like Google Brain, AI Fund, and DeepLearning.AI. So he knows better than anyone that founders who operate the same way in 2025 as they did in 2022 are doing it wrong. Sarah Guo and Elad Gil sit down with Andrew Ng, the godfather of the AI revolution, to discuss the rise of agentic AI, and how the technology has changed everything from what makes a successful founder to the value of small teams. They talk about where future capability growth may come from, the potential for models to bootstrap themselves, and why Andrew doesn’t like the term “vibe coding.” Also, Andrew makes the case for why everybody in an organization—not just the engineers—should learn to code.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AndrewYNg Chapters: 00:00 – Andrew Ng Introduction 00:32 – The Next Frontier for Capability Growth 01:29 – Andrew’s Definition of Agentic AI 02:44 – Obstacles to Building True Agents 06:09 – The Bleeding Edge of Agentic AI 08:12 – Will Models Bootstrap Themselves? 09:05 – Vibe Coding vs. AI Assisted Coding 09:56 – Is Vibe Coding Changing the Nature of Startups? 11:35 – Speeding Up Project Management 12:55 – The Evolution of the Successful Founder Profile 19:23 – Finding Great Product People 21:14 – Building for One User Profile vs. Many 22:47 – Requisites for Leaders and Teams in the AI Age 28:21 – The Value of Keeping Teams Small 32:13 – The Next Industry Transformations 34:04 – Future of Automation in Investing Firms and Incubators 37:39 – Technical People as First Time Founders 41:08– Broad Impact of AI Over the Next 5 Years 41:49 – Conclusion

What would it take to challenge Nvidia? SemiAnalysis Founder and CEO Dylan Patel joins Sarah Guo to answer this and other topical questions around the current state of AI infrastructure. Together, they explore why Dylan loves Android products, predictions around OpenAI’s open source model, and what the landscape of neoclouds looks like. They also discuss Dylan’s thoughts on bottlenecks for expanding AI infrastructure and exporting American AI technologies. Plus, we find out what question Dylan would ask Mark Zuckerberg.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @dylan522p | @SemiAnalysis_ Chapters: 00:00 – Dylan Patel Introduction 00:31 – Dylan’s Love for Android Products 02:10 – Predictions About OpenAI’s Open Source Model 06:50 – Implications of an American Open Source Model for the Application Ecosystem 10:48 – Evolution of Neoclouds 17:26 – What It Would Take to Challenge Nvidia 27:43 – What Would an Nvidia Challenger Look Like? 28:18 – Understanding Operational and Power Constraints for Data Centers 34:48 – Dylan’s View on the American Stack 43:01 – What Dylan Would Ask Mark Zuckerberg 44:22 – Poker and AI Entrepreneurship 46:51 – Conclusion

Cloudflare has spent nearly fifteen years making the Internet faster, more reliable, and more secure. So now that AI systems are changing the way we interact with the Internet, Cloudflare wants to help level the playing field for content creators. Sarah Guo and Elad Gil sit down with Matthew Prince, co-founder and CEO of Cloudflare to discuss the evolution of the internet from search to AI, including Cloudflare’s role in facilitating that shift. Matthew talks about how AI assistants are changing the shape of the Internet, the problems Google created by making traffic the arbiter of content value, and how he sees Cloudflare’s part in facilitating the new content marketplace for the mutual benefit of creators and AI companies. Plus, a look towards how agentic infrastructure may unfold in the near future. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @eastdakota | @Cloudflare Chapters: 00:00 – Matthew Prince Introduction 00:37 – Cloudflare’s Role in Securing the Internet 02:08 – The Road to Cloudflare’s Dominance 03:20 – The Internet’s Shift from Search to AI 06:34 – Role of Agents and Content on the New Web 09:44 – Reshaping the Content Market Online 13:05 – De-emphasizing Traffic as a Proxy for Value 18:04 – Will We Run Out of Quality Human-Generated Content? 20:01 – Scaling the Value of Content in the AI Age 22:32 – Cloudflare’s Approach to Inference 24:55 – How Cloudflare Responds to Market Demand 26:04 – Open vs. Closed Models 27:21 – Path to the New Marketplace for Content 30:58 – Advice for Content Creators 32:47 – Exploring the Timeline for Running Models Locally 40:07 – The Future of Agentic Infrastructure 44:52 – Conclusion

Sriram Krishnan was never interested in policy. But after seeing a gap in AI knowledge at senior levels of government, he decided to lend his expertise to the tech-friendly Trump administration. Senior White House Policy Advisor on AI Sriram Krishnan joins Elad Gil and Sarah Guo to talk about America’s AI Action Plan, a recent executive order that outlines how America can win the AI race and maintain its AI supremacy. Sriram discusses why winning the AI race is important and what that looks like, as well as the core goals of the Action Plan that he helped to author. Together, they explore how AI is the latest iteration of American cultural exportation and soft power, the bottlenecks in upgrading America’s energy infrastructure, and the importance of America owning the “full stack” from GPUs and models to agents and software. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @skrishnan47 | @sriramk Chapters: 00:00 – Sriram Krishnan Introduction 01:00 – Sriram’s Role in Government 03:43 – Impetus for the America AI Action Plan 06:14 – What Winning the AI Race Looks Like 10:36 – Algorithms and Cultural Bias 12:26 – Main Tenets of the America AI Action Plan 19:13 – Infrastructure and Energy Needs for AI 22:56 – Manufacturing, Supply Chains, and AI 24:52 – Ensuring American Dominance in Robotics 26:30 – Translating Policy to Industry and the Economy 29:30 – Should the US Be a Technocracy? 32:33 – Understanding the Argument Against Open Source Models 36:07 – Conclusion

In the generative AI revolution, quality data is a valuable commodity. But not all data is created equally. Sarah Guo and Elad Gil sit down with SurgeAI founder and CEO Edwin Chen to discuss the meaning and importance of quality human data. Edwin talks about why he bootstrapped Surge instead of raising venture funds, the importance of scalable oversight in producing quality data, and the work Surge is doing to standardize human evals. Plus, we get Edwin’s take on what Meta’s investment into Scale AI means for Surge, as well as whether or not he thinks an underdog can catch up with OpenAI, Anthropic, and other dominant industry players. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @echen | @HelloSurgeAI Chapters: 00:00 – Edwin Chen Introduction 00:41 – Overview of SurgeAI 02:28 – Why SurgeAI Bootstrapped Instead of Raising Funds 07:59 – Explaining SurgeAI’s Product 09:39 – Differentiating SurgeAI from Competitors  11:27 – Measuring the Quality of SurgeAI’s Output 12:25 – Role of Scalable Oversight at SurgeAI 14:02 – Challenges of Building Rich RL Environments 16:39 – Predicting Future Needs for Training AI Models 17:29 – Role of Humans in Data Generation 21:27 – Importance of Human Evaluation for Quality Data 22:51 – SurgeAI’s Work Toward Standardization of Human Evals 23:37 – What the Meta/ScaleAI Deal Means for SurgeAI 24:35 – Edwin’s Underdog Pick to Catch Up to Big AI Companies 24:50 – The Future Frontier Model Landscape 26:25 – Future Directions for SurgeAI 29:29 – What Does High Quality Data Mean? 32:26 – Conclusion

Superintelligence, at least in an academic sense, has already been achieved. But Misha Laskin thinks that the next step towards artificial superintelligence, or ASI, should look both more user and problem-focused. ReflectionAI co-founder and CEO Misha Laskin joins Sarah Guo to introduce Asimov, their new code comprehension agent built on reinforcement learning (RL). Misha talks about creating tools and designing AI agents based on customer needs, and how that influences eval development and the scope of the agent’s memory. The two also discuss the challenges in solving scaling for RL, the future of ASI, and the implications for Google’s “non-acquisition” of Windsurf.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MishaLaskin | @reflection_ai Chapters: 00:00 – Misha Laskin Introduction 00:44 – Superintelligence vs. Super Intelligent Autonomous Systems 03:26 – Misha’s Journey from Physics to AI 07:48 – Asimov Product Release 11:52 – What Differentiates Asimov from Other Agents 16:15 – Asimov’s Eval Philosophy 21:52 – The Types of Queries Where Asimov Shines 24:35 – Designing a Team-Wide Memory for Asimov 28:38 – Leveraging Pre-Trained Models 32:47 – The Challenges of Solving Scaling in RL 37:21 – Training Agents in Copycat Software Environments 38:25 – When Will We See ASI?  44:27 – Thoughts on Windsurf’s Non-Acquisition 48:10 – Exploring Non-RL Datasets 55:12 – Tackling Problems Beyond Engineering and Coding 57:54 – Where We’re At in Deploying ASI in Different Fields 01:02:30 – Conclusion

As a three-time founder, Parker Conrad has one piece of advice for aspiring entrepreneurs—don’t do it. The Rippling co-founder and CEO joins Sarah Guo to talk about what he learned from the crash at Zenefits, why most advice to founders is wrong, and how building a real platform—not a point solution—is the only way to win in SaaS. The two get into founder psychology, the myth of learning from failure, and what true ownership looks like inside a company. He also shares why AI won’t shrink teams anytime soon, what people misunderstand about vertical software, and why ambition trumps efficiency with long-lasting companies. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @parkerconrad Chapters: 00:00 Introduction to Parker Conrad 00:33 Lessons from Zenefits to Rippling 01:54 The Psychology of Founding a Company 07:56 Rippling's Ambitious Vision 10:41 Building a Platform Company 15:05 Challenges and Strategies in Scaling 30:36 AI's Impact on Software Development 42:06 Public vs. Private: Rippling's Future 44:19 Conclusion 

AI has already fueled breakthroughs in biotechnology—but now, further advances in AI are poised to fuel pharmaceutical discoveries as well. Sarah Guo sits down with Joshua Meier and Jack Dent, co-founders of Chai Discovery, whose newly launched Chai-2 designs bespoke antibodies that bind to their targets at a jaw-dropping 20% rate. Jack and Joshua talk about the implications for Chai-2’s success rate at discovering antibodies for the pharmaceutical industry, how structure prediction is pivotal in making the model work, and future potential for using the model to optimize other molecular properties. Plus, they talk about what they believe bioscientists should be learning to best utilize Chai-2’s technology.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @_jackdent | @joshim5 Chapters: 00:00 – Joshua Meier and Jack Dent Introduction 01:09 – Genesis of Chai Discovery 06:12 – Chai-2 Model 10:13 – Criteria for Specifying Targets for Chai-2 13:12 – How the Chai-2 Model Works 16:12 – Emergent Vocabulary from Chai-2 18:15 – Hopes for Chai-2’s Impact 20:33 – Reception of the Chai-2 Model 22:16 – Future of Wet Lab Screening and Biotech 27:08 – Optimizing Other Molecule Properties 31:37 – Where Chai Invests From Here 36:20 – What Bioscientists Should Learn for Chai-2 40:23 – How Jack and Josh Oriented to the Biotech Space 43:38 – Platform Investment and Chai-2 46:53 – Scaling Chai Discovery 48:21 – Hiring at Chai Discovery 49:09 – Conclusion

Much of the scientific process involves searching. But rather than continue to rely on the luck of discovery, Google DeepMind has engineered a more efficient AI agent that mines complex spaces to facilitate scientific breakthroughs. Sarah Guo speaks with Pushmeet Kohli, VP of Science and Strategic Initiatives, and research scientist Matej Balog at Google DeepMind about AlphaEvolve, an autonomous coding agent they developed that finds new algorithms through evolutionary search. Pushmeet and Matej talk about how AlphaEvolve tackles the problem of matrix multiplication efficiency, scaling and iteration in problem solving, and whether or not this means we are at self-improving AI. Together, they also explore the implications AlphaEvolve has to other sciences beyond mathematics and computer science. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @pushmeet | @matejbalog Chapters: 00:00 Pushmeet Kohli and Matej Balog Introduction 0:48 Origin of AlphaEvolve 02:31 AlphaEvolve’s Progression from AlphaGo and AlphaTensor 08:02 The Open Problem of Matrix Multiplication Efficiency 11:18 How AlphaEvolve Evolves Code 14:43 Scaling and Predicting Iterations 16:52 Implications for Coding Agents 19:42 Overcoming Limits of Automated Evaluators 25:21 Are We At Self-Improving AI? 28:10 Effects on Scientific Discovery and Mathematics 31:50 Role of Human Scientists with AlphaEvolve 38:30 Making AlphaEvolve Broadly Accessible 40:18 Applying AlphaEvolve Within Google 41:39 Conclusion

When will fully autonomous vehicles see widespread adoption? According to Applied Intuition, that future is closer than you may think. Applied Intuition’s CEO, Qasar Younis, and CTO, Peter Ludwig, talk with Elad Gil about how now is the best time to both work on self-driving vehicle technology and monetize it. Qasar and Peter discuss the advantages of developing their own OS in-house for their autonomous applications, self-driving technology’s potential to drive re-shoring of vehicle manufacturing to the United States, and how best to gauge the bar for safety in autonomous systems. Plus, they explore how self-driving technology may reshape the designs of not only vehicles, but cities themselves. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @qasar | @AppliedInt Chapters: 00:00 Qasar Younis and Peter Ludwig Introduction 01:28 A Primer on Applied Intuition 11:08 Applied Intuition’s Customers 12:04 Impact of Chinese Vehicles Manufacturers 15:44 EV Policies in the European Market 20:49 Can Robotics and Automation Re-Shore Vehicle Manufacturing? 21:53 Training Models for Autonomous Vehicles 26:41 Gauging the Bar for Autonomous Vehicles Safety 32:03 Timeline for Large-Scale Autonomous Vehicle Adoption 36:28 Rethinking Urban Design for Autonomous Vehicles 38:47 How Applied Intuition Uses AI for Tooling and OS 42:09 Designing for User Experience 43:31 Applied Intuition’s Hiring Strategy 45:01 Conclusion

What happens when you give AI researchers unlimited compute and tell them to compete for the highest usage rates? Ben Mann, Co-Founder, from Anthropic sits down with Sarah Guo and Elad Gil to explain how Claude 4 went from "reward hacking" to efficiently completing tasks and how they're racing to solve AI safety before deploying computer-controlling agents. Ben talks about economic Turing tests, the future of general versus specialized AI models, Reinforcement Learning From AI Feedback (RLAIF), and Anthropic’s Model Context Protocol (MCP). Plus, Ben shares his thoughts on if we will have Superintelligence by 2028.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @8enmann Links:  ai-2027.com/  Chapters: 00:00 Ben Mann Introduction 00:33 Releasing Claude 4 02:05 Claude 4 Highlights and Improvements 03:42 Advanced Use Cases and Capabilities 06:42 Specialization and Future of AI Models 09:35 Anthropic's Approach to Model Development 18:08 Human Feedback and AI Self-Improvement 19:15 Principles and Correctness in Model Training 20:58 Challenges in Measuring Correctness 21:42 Human Feedback and Preference Models 23:38 Empiricism and Real-World Applications 27:02 AI Safety and Ethical Considerations 28:13 AI Alignment and High-Risk Research 30:01 Responsible Scaling and Safety Policies 35:08 Future of AI and Emerging Behaviors 38:35 Model Context Protocol (MCP) and Industry Standards 41:00 Conclusion

In this episode of No Priors, Sarah and Elad are joined by Dr. Fei-Fei Li, AI pioneer, co-director of Stanford’s Human-Centered AI Institute, and founder of World Labs. Fei-Fei shares why she’s building at the intersection of embodiment and intelligence, and what today’s AI systems are still missing. From the early days of ImageNet to her vision for the next generation of robotics, she unpacks the human and technical motivations behind World Labs. They also discuss the challenges of 3D world modeling, her approach to building exceptional teams, and the special qualities that have led her students like Andrej Karpathy to make major breakthroughs. Show Notes: 0:00 Why and what Dr. Fei-Fei Li is building 3:00 World models at World Labs 6:44 Missing gaps in the AI future 9:16 Robotics and physical intelligence 16:15 Greatest challenges of 3D 19:08 Fei-Fei’s work in PhD in ImageNet 23:05 Special moments in Dr. Li's career 29:33 Building teams 32:05 Human-centered AI

In this episode of No Priors, Sarah and Elad unpack the current state of the AI market - whether it’s consolidating, what’s enabling or blocking key mergers, and where the most promising untapped opportunities lie, particularly in biotech. They also explore the rise of world models and how AI’s novel methods for understanding complex systems may ultimately reshape how humans approach discovery and problem-solving.  Show Notes: 0:00 Is the AI market consolidating into clear winners? + the physics of the current landscape 7:01 Why more companies don’t merge (even when it makes sense)  10:09 Exploring biotech’s biggest commercial opportunities and the challenges founders face  17:14 Building world models  21:34 How AI is expanding the way humans reason, design, and evolve systems

Arvind Jain joins Sarah and Elad on this episode of No Priors. Arvind is the founder and CEO of Glean, an AI-powered enterprise search platform. He previously co-founded Rubrik and spent over a decade as an engineering leader at Google. In this episode, Arvind shares how LLMs are transforming enterprise search, why most tools in the space have failed, and the opportunity to build apps powered by internal knowledge. He discusses how much customization is still needed on top of foundation models, what made building Glean uniquely challenging compared to Arvind’s previous ventures, and what’s next for the company. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jainarvind Show Notes: 0:00 Introduction 0:58 How LLMs are changing search 2:05 Building out Glean’s platform 5:09 Why most search companies failed 8:41 Out of the box vs. bespoke models  10:26 Creating apps on top of internal knowledge 15:34 User behaviors & insights  19:11 Unique challenges of building Glean  21:51 Product-led growth vs. enterprise sales 25:00 Succeeding in traditionally bad markets  27:08 What Glean is excited to build next

On this episode of No Priors, Sarah talks to Luis von Ahn, founder and CEO of Duolingo, the world’s most popular education app with over 116 million monthly users and a market cap of approximately $17 billion. Controversially, it has recently committed to being “AI-first.” They discuss why motivation is the biggest challenge in education, how Duolingo harnesses game mechanics and behavioral insights to keep learners engaged, and the company’s efforts to leverage AI to personalize education at scale. Luis also shares thoughts on the Duolingo brand, courses beyond language (chess and math), and the broader impact of AI on content creation. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LuisvonAhn Links: Duolingo is now AI-First: http://bit.ly/3RQzny3 Show Notes: 0:00 Introduction 4:01  Optimizing learning behavior through tech 11:20 Adopting AI at Duolingo 17:25 AI’s threat to content companies 18:34 An unhinged corporate brand 21:28 How do people learn? 25:16 What people misunderstand about Duolingo? 26:24 How AI is transforming learning at scale 30:28 Leveraging AI across the business

This week on No Priors, Elad and Sarah sit down with Eric Mitchell and Brandon McKinzie, two of the minds behind OpenAI’s O3 model. They discuss what makes O3 unique, including its focus on reasoning, the role of reinforcement learning, and how tool use enables more powerful interactions. The conversation explores the unification of model capabilities, what the next generation of human-AI interfaces could look like, and how models will continue to advance in the years ahead. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mckbrando | @ericmitchellai Show Notes: 0:00 What is o3? 3:21 Reinforcement learning in o3 4:44 Unification of models 8:56 Why tool use helps test time scaling 11:10 Deep research 16:00 Future ways to interact with models 22:03 General purpose vs specialized models 25:30 Simulating AI interacting with the world 29:36 How will models advance?

On this episode of No Priors, Sarah sits down with Isa Fulford, one of the masterminds behind deep research. They unpack how the initiative began, the role of human expert data, and what it takes to build agents with real-world capability and even taste. Isa shares the differences between deep research and OpenAI’s o3 model, the challenges around latency, and how she sees agent capabilities evolving. Plus, OpenAI has announced that deep research is free for all US users starting today. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @IsaFulf Show Notes: 0:00 Deep research’s inception & evolution 6:12 Data creation  7:20 Reinforcement fine-tuning 9:05 Why human expert data matters 11:23 Failure modes of agents 13:55 The roadmap ahead for Deep Research 18:32 How do agents develop taste?  19:29 Experience and path to building a broadly capable agent 22:03 Deep research vs. o3 25:55 Latency 27:56 Predictions for agent capabilities

This week on No Priors, Sarah and Elad are joined by Josh Goldman, cofounder and president of KoBold Metals. KoBold is using AI to transform how we discover critical minerals like lithium and cobalt, making the exploration process faster, more precise, and more scalable than traditional methods. In this episode, Josh explains how KoBold is rethinking the fundamentals of mineral exploration by combining unique datasets, scientific modeling, and predictive algorithms. They dive into the company’s driving philosophy and technical approach, how they validate underground hypotheses, and why regulatory knowledge and a localized approach are crucial. Josh also discusses what success looks like in exploration today and the scarcity of world-class deposits. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @KoBold_Metals Show Notes: 0:00 Introduction 0:29 KoBold Metals 3:14 Using unique datasets 6:20 Traditional methods of lithium exploration 8:38 Regulatory vs. rarity constraints 13:40 Technical approach 16:25 Validating hypotheses 23:56 Redefining success in mineral exploration 25:44 Scarcity of good projects and deposits 32:44 Philosophy behind prediction 36:46 KoBold’s origin story

On this episode of No Priors, Sarah and Elad sit down with Brendan Foody, CEO and cofounder of Mercor, to discuss the company’s rapid growth and their vision for the future of the labor market. They dive into how AI is reshaping the workforce in real, tangible ways and what skills are worth investing in today. Brendan shares insights on evaluating talent in an AI-driven world, including how models might identify outlier or 10x candidates and even assess “taste.” The conversation also touches on the evolving role of human data, the future of hiring in fast-scaling startups, and whether AI will act as an individual contributor or a data-centric manager. Show Notes: 0:00 Introduction 0:16 Building Mercor 3:00 Identifying outlier talent with AI 9:07 How AI is reshaping the workforce: job displacement & evolution 11:18 What skills should we invest in now? 12:18 Verifiability 13:36 Evaluating models 16:07 What should kids learn today? 17:05 Evaluating taste in talent assessments 18:45 Future of data collection 26:07 Humans’ role in the AI economy 28:53 AI as a contributor vs. a manager 33:03 Mercor’s goals  34:50 Evolution of labor markets  36:00 Hiring advice

In this episode of No Priors, Sarah and Elad examine the current state of AI. They break down the recent dip in public markets, how tariffs could impact the tech industry, and where opportunities remain in large language models. They highlight the opportunities in more specialized models, new approaches to model development, and how the market is beginning to standardize with integrations like the Model Context Protocol (MCP). The episode ends with a look at early consumer AI applications and what types of expertise will matter most in the coming years. Show Notes: 0:00 Improvements in image gen 4:42 Public markets  8:08 Effects of tariffs on tech 9:42 Today’s large model market 11:34 Opportunities in specialized models 16:30 Research advances in model approaches 21:10 What expertise will matter? 24:30 Anthropic’s Model Context Protocol  26:30 Consumer applications

In this episode of No Priors, Elad and Sarah chat with Shiv Rao, MD, founder and CEO of Abridge. They dive into how Abridge is reshaping healthcare by creating AI tools that enhance clinical documentation and improve doctor-patient interactions. Shiv shares his thoughts on building trust with established healthcare systems, giving agency and time back to clinicians, and what makes the healthcare AI opportunity different today. They also discuss Abridge’s approach to developing and launching AI products, along with Shiv’s journey in founding Abridge. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ShivdevRao Show Notes:  0:00 Introduction  0:35 Abridge’s Story and Vision  5:30 Strategy for Customer Choice  7:41 Healthcare AI Opportunities  11:24 Navigating Incumbent Partnerships  14:26 Doctor-Centric AI Solutions  19:54 Abridge’s Future Plans  22:13 AI’s Impact on Healthcare  28:43 Shipping and Iterating Products  32:50 Shiv’s Journey to Abridge

This week on No Priors, Elad speaks with Chelsea Finn, cofounder of Physical Intelligence and currently Associate Professor at Stanford, leading the Intelligence through Learning and Interaction Lab. They dive into how robots learn, the challenges of training AI models for the physical world, and the importance of diverse data in reaching generalizable intelligence. Chelsea explains the evolving landscape of open-source vs. closed-source robotics and where AI models are likely to have the biggest impact first. They also compare the development of robotics to self-driving cars, explore the future of humanoid and non-humanoid robots, and discuss what’s still missing for AI to function effectively in the real world. If you’re curious about the next phase of AI beyond the digital space, this episode is a must-listen. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ChelseaFinn Show Notes: 0:00 Introduction 0:31 Chelsea’s background in robotics 3:10 Physical Intelligence  5:13 Defining their approach and model architecture 7:39 Reaching generalizability and diversifying robot data 9:46 Open source vs. closed source 12:32 Where will PI’s models integrate first? 14:34 Humanoid as a form factor 16:28 Embodied intelligence 17:36 Key turning points in robotics progress 20:05 Hierarchical interactive robot and decision-making 22:21 Choosing data inputs 26:25 Self driving vs robotics market 28:37 Advice to robotics founders 29:24 Observational data and data generation 31:57 Future robotic forms

This week on No Priors, Sarah and Elad talk with GitHub CEO Thomas Dohmke about the rise of AI-powered software development and the success of Copilot. They discuss how Copilot is reshaping the developer workflow, GitHub’s new Agent Mode, and competition in the developer tooling market. They also explore how AI-driven coding impacts software pricing, the future of open source vs. proprietary APIs, and what Copilot’s success means for Microsoft. Plus, Thomas shares insights from his journey growing up in East Berlin and navigating rapidly changing worlds. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ThomasDohmke Show Notes: 0:00 Introduction 0:37 GitHub Copilot’s capabilities 4:12 Will agents replace developers? 6:04 Copilot’s development cycle 8:34 Winning the developer market 10:40 Agent mode 13:25 Where GitHub is headed 16:45 Building for the new challenges of AI 21:50 Dev tools market formation 29:56 Copilot’s broader impact 32:17 How AI changes software pricing 39:16 Open source vs. proprietary APIs 48:01 Growing up in East Berlin

This week on No Priors, Sarah is joined by Dan Hendrycks, director of the Center of AI Safety. Dan serves as an advisor to xAI and Scale AI. He is a longtime AI researcher, publisher of interesting AI evals such as "Humanity's Last Exam," and co-author of a new paper on National Security "Superintelligence Strategy" along with Scale founder-CEO Alex Wang and former Google CEO Eric Schmidt. They explore AI safety, geopolitical implications, the potential weaponization of AI, along with policy recommendations. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @DanHendrycks Show Notes: 0:00 Introduction 0:36 Dan’s path to focusing on AI Safety 1:25 Safety efforts in large labs 3:12 Distinguishing alignment and safety 4:48 AI’s impact on national security 9:59 How might AI be weaponized? 14:43 Immigration policies for AI talent 17:50 Mutually assured AI malfunction 22:54 Policy suggestions for current administration 25:34 Compute security 30:37 Current state of evals

This week on No Priors, Sarah sits down with Noubar Afeyan, Co-founder and CEO of Flagship Pioneering, the biotech firm behind groundbreaking companies like Moderna. They explore how Flagship creates the conditions for scientific breakthroughs, tackles regulatory uncertainty, and pushes the boundaries of discovery. Noubar shares insights on AI’s role in healthcare, the challenges of bringing new therapies to market, and lessons learned from past pandemics. He also discusses Flagship’s platform approach to biotech innovation and introduces the idea of polyintelligence. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @NoubarAfeyan Show Notes:  0:00 Introduction 0:48 Founding Flagship  5:51 Fostering environments for emergence 11:17 Expanding into new frontiers 14:26 Developing technology amid regulatory uncertainty and risk 19:12 How Flagship has evolved 22:47 AI applications in healthcare 27:30 Bottlenecks in bringing new therapies to market 32:20 Lessons for the next pandemic 34:11 Building a platform 38:10 Polyintelligence 

On this week’s episode of No Priors, Sarah Guo is joined by leading members of the teams at Vevo Therapeutics and the Arc Institute – Nima Alidoust, CEO/Co-Founder at Vevo Therapeutics; Johnny Yu, CSO/Co-Founder at Vevo Therapeutics; Patrick Hsu, CEO/Co-Founder at Arc Institute; Dave Burke, CTO at Arc Institute; and Hani Goodarzi, Core Investigator at Arc Institute. Predicting protein structure (AlphaFold 3, Chai-1, Evo 2) was a big AI/biology breakthrough. The next big leap is modeling entire human cells—how they behave in disease, or how they respond to new therapeutics. The same way LLMs needed enormous text corpora to become truly powerful, Virtual Cell Models need massive, high-quality cellular datasets to train on. In this episode, the teams discuss the groundbreaking release of the Tahoe-100M single cell dataset, Arc Atlas, and how these advancements could transform drug discovery. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @Nalidoust | @IAmJohnnyYu | @PDHsh | @Davey_Burke | @Genophoria Download the Tahoe Dataset Show Notes: 0:00 Introduction 1:40 Significance of Tahoe-100M dataset 4:22 Where we are with virtual cell models and protein language models 10:26 Significance of perturbational data 17:39 Challenges and innovations in data collection 24:42 Open sourcing and community collaboration 33:51 Predictive ability and importance of virtual cell models 35:27 Drug discovery and virtual cell models 44:27 Platform vs. single hypothesis companies 46:05 Rise of Chinese biotechs 51:36 AI in drug discovery

Kyle Vogt joins Sarah and Elad on this week’s episode of No Priors. A serial entrepreneur, Kyle co-founded Twitch, transforming live streaming, and later Cruise, the autonomous vehicle company acquired by GM for $1 billion. Now he’s taking on AI-powered home robotics with The Bot Company. In this episode, Kyle shares his journey building transformative tech companies, the challenges of scaling autonomous systems, and why he believes home robots are the next frontier. They also discuss the parallels between AVs and robotics, overcoming consumer skepticism, US vs. China manufacturing, and the policies needed to foster a competitive robotics industry. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @KVogt Show Notes:  0:00 Introduction 0:29 Founding Cruise  3:12 Tesla vs. Waymo approach 4:44 Scaling autonomous vehicles 10:03 The Bot Company  16:35 Deploying  robots in the home 17:56 Parallels between robots and AV markets 20:51 Personifying robots and overcoming consumer skepticism 25:00 Timeline on consumer robots 26:47 Chinese vs. US manufacturing  29:15 Fostering a competitive domestic robotics industry 34:00 Lessons from Cruise & personal philosophies

This week on No Priors, Sarah sits down with Harvey cofounder and CEO Winston Weinberg. Harvey is one of the leading application layer AI companies, building domain-specific AI for law firms, professional service providers, and the Fortune 500. They are already working with companies like Bridgewater, KKR, PWC, and O’Melveny with over $500M in funding from OpenAI, Sequoia, Kleiner, GV and Elad and Sarah. In this episode, Sarah and Winston cover AI product strategy, the future of professional services, company values, keeping up with research, and the law industry of the future.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @WinstonWeinberg Show Notes:  0:00 Introduction 2:39 Harvey’s founding story  3:46 Capability improvement 6:39 Building teams around AI capabilities 9:17 End to end task completion 12:37 Beginning with large industry leaders 17:21 Working with users skeptical of automation 20:40 Being a lawyer today and in the future 26:02 Adapting product for other domains 26:58 Hiring philosophy at Harvey 30:39 Lessons and mistakes as a founder 32:53 Personal drive 40:21 Advice to other founders 44:35 Prediction for next ChatGPT moment

This week on No Priors, Sarah and Elad celebrate the 100th episode! They dive into the biggest AI stories of 2025, breaking down DeepSeek—truth vs. hype, the rapid consumer adoption, and the real cost of training the models. They debate model commoditization and the value of being a frontier model provider vs. building on existing work. Plus, they unpack OpenAI’s new Deep Research release and the latest on Stargate. Finally, they share bold predictions for 2025, covering robots, autonomous vehicles, local AI models, emerging data-generation strategies, and reasoning breakthroughs. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  0:00 Introduction 0:19 DeepSeek  5:38 Are models commoditizing? 8:33 DeepSeek’s consumer adoption 9:16 OpenAI’s Deep Research release 13:30 Stargate 15:04 Elad & Sarah’s Predictions for 2025 

This week on No Priors, Elad sits down with Rick Caruso, LA real estate developer and runner-up in the 2022 mayoral race. With experience serving under three LA mayors, as well as on the police commission and the board of water and power, Rick offers a unique perspective on the systemic failures that contributed to the devastation of the January 2025 wildfires in communities like the Palisades and Altadena. He discusses the steps he took to build more resilient infrastructure in his properties and how California can rebuild smarter to better prepare for future disasters. They also explore the state’s water management, rising crime, and how to leverage California’s vast natural resources and budget to create a better future for all residents. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @RickCarusoLA Show Notes 0:00 Introduction 0:56 Caruso’s history in business and public service 3:36 Failures in fire prevention and response 5:58 How Caruso’s properties survived  8:26 Water shortages and infrastructure failures  9:47 Arson, looting, and crime in LA 15:03 Rebuilding  20:50 Allocating California’s resources effectively 26:15 Caruso’s future plans

This week on No Priors, Sarah and Elad sit down with Bill Clerico, founder of Convective Capital, an early stage venture fund focused on technology-driven solutions for wildfire mitigation and climate resilience. The wildfires in Los Angeles have caused unprecedented property damage and immense hardship for countless individuals and families. This episode is devoted to diving into understanding what happened and what we can do in the future. Bill shares his insights into the increasing severity of wildfires, the role of policy, and how infrastructure issues, like outdated building codes and underfunded utilities, are contributing to the crisis. They discuss the latest innovations in fire-fighting technology, from advanced detection to drones, and how these tools can help mitigate future damage. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @BillClerico Show Notes:  0:00 Introduction 1:02 Why are wildfires getting worse? 5:37 Policies and regulatory decisions 10:47 Housing: building codes and permitting 13:19 Key factors in response 16:20 Improving water supply and city infrastructure  19:10 Preventing wildfires 21:26 Underinvestment in California’s utilities 26:53  Innovative fire fighting technology 29:35 Accelerating Los Angeles’ recovery 34:29 Actions homeowners, insurance companies, and governments can take

Today on No Priors, co-founder and CEO of Decagon, Jesse Zhang, joins Elad to discuss the future of agentic customer support. Decagon provides AI-powered customer interactions for companies like Rippling, Notion, Duolingo, Classpass, Substack, Vanta, Eventbrite, and more. Jesse shares the thesis behind starting Decagon, why he sees customer support as the ideal entry point for agentic technology, and what areas of AI excite him most. They also discuss voice-based interfaces, issues with latency in current capabilities, and the connection between young math olympiad communities and today’s AI startups. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @TheJesseZhang Show Notes:  0:00 Introduction  0:30 Starting Decagon  3:15 Business impact of adopting agents for customer support and customer ops 8:00 AI infrastructure and models for customer success agents 12:05 Voice-based capabilities and text-to-speech engines  15:00 Combatting latency  16:25 Crossover of math and AI communities 21:12 Exciting areas of AI  25:29 Strengths and weaknesses of agents

Today on No Priors, Elad chats with Erik Bernhardsson, founder and CEO of Modal Labs, a platform simplifying ML workflows by providing a serverless infrastructure designed to streamline deployment, scaling, and development for AI engineers. Erik talks about his early work on Spotify’s ML algorithms, what Modal offers today, and his vision for building an end-to-end solution for AI engineers. They dive into GPU trends, cloud vs on-premise setups, and when to train custom models vs use off-the-shelf solutions. Erik also shares his thoughts on the evolving role of AI in fields like coding, physics, and music. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Bernhardsson Show Notes: 0:00 Introduction  0:22 Erik's early interest in ML infra 1:22 Founding Modal Labs  4:17 State of GPU use today and what’s to come 7:14 Modal's end-to-end vision  9:00 Differentiating amongst competition 10:20 Cloud vs on-premise  12:35 Popular AI models  13:20 Gaps in AI infrastructure 14:55 Insights on vector databases  16:48 Training models vs off-the-shelf models  17:47 AI’s impact on coding and physics 22:14 AI's impact on music

2024 has been a year of transformative technological progress, marked by conversations that have reshaped our understanding of AI's evolution and what lies ahead. Throughout the year, Sarah and Elad have had the privilege of speaking with some of the brightest minds in the field. As we look back on the past months, we’re excited to share highlights from some of our favorite No Priors podcast episodes. Featured guests include Jensen Huang (Nvidia), Andrej Karpathy (OpenAI, Tesla), Bret Taylor (Sierra), Aditya Ramesh, Tim Brooks, and Bill Peebles (OpenAI’s Sora Team), Dmitri Dolgov (Waymo), Dylan Field (Figma), and Alexandr Wang (Scale). Want to dive deeper? Listen to the full episodes here: NVIDIA's Jensen Huang on AI Chip Design, Scaling Data Centers, and his 10-Year Bet No Priors Ep. 89 | With NVIDIA CEO Jensen Huang  The Road to Autonomous Intelligence, With Andrej Karpathy from OpenAI and Tesla No Priors Ep. 80 | With Andrej Karpathy from OpenAI and Tesla Transforming Customer Service through Company Agents, with Sierra’s Bret Taylor No Priors Ep. 82 | With CEO of Sierra Bret Taylor OpenAI’s Sora team thinks we’ve only seen the "GPT-1 of video models" No Priors Ep.61 | OpenAI's Sora Leaders Aditya Ramesh, Tim Brooks and Bill Peebles Waymo’s Journey to Full Autonomy: AI Breakthroughs, Safety, and Scaling No Priors Ep. 87 | With Co-CEO of Waymo Dmitri Dolgov Designing the Future: Dylan Field on AI, Collaboration, and Independence No Priors Ep. 55 | With Figma CEO Dylan Field The Data Foundry for AI with Alexandr Wang from Scale No Priors Ep. 65 | With Scale AI CEO Alexandr Wang Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes: 0:00 Introduction  0:15 Jensen Huang on building at data-center scale  4:00 Andrej Karpathy on the AI exo-cortex, model control, and a shift to smaller models  7:14 Bret Taylor on the agentic future of business interactions  11:17 OpenAI’s Sora team on visual models and their role in AGI  15:53 Waymo’s Dmitri Dolgov on bridging the gap to full autonomy and the challenge of 100% accuracy  19:00 Figma’s Dylan Field on the future of interfaces and new modalities  23:29 Scale AI’s Alexandr Wang on the journey to AGI  26:29 Outro

Today on No Priors, Sarah sits down with Elias Torres, CEO and founder of Agency, an AI agent for customer success teams. Elias shares his journey from growing up in Nicaragua to founding several companies, leading engineering at HubSpot, and selling Drift for $1B. He also discusses his work consulting with OpenAI in 2022, which deepened his understanding of the business opportunity LLMs presented and inspired him to start Agency. In this episode, Elias offers a unique perspective on the future of AI and customer success, explaining how current software has fallen short and his vision for a new generation where customers have direct relationships, spend less time on tasks, and have software working invisibly on their behalf. They also discuss the evolving landscape of hiring as teams shrink, and Elias reveals his ambitious plan to reach $1B in revenue with fewer than 100 employees. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EliasT  Show notes: 0:00 Introduction 0:34 Elias’ journey to entrepreneurship 2:36 Growing HubSpot to IPO and founding Drift 6:19 Consulting with OpenAI, learning about LLMs, and diving into AI 9:35 Founding Agency to focus on customer success and AI-driven solutions 11:40 What will a customer experience look like in 5 years? 15:48 Company building in an era of AI, as a 5th time founder 18:32 Reducing headcount while raising the bar on hiring 20:35 Key challenges in building Agency and crafting a standout product 23:06 Addressing software flaws and transitioning to an era of intuitive, self-operating solutions 26:27 Timeline for the next-gen software revolution + the power of building from first principles

In this episode of No Priors, Sarah sits down with Felix Ejeckam and Ty Mitchell, founders of Akash Systems, a company pioneering diamond-based cooling technology for semiconductors used in space applications and large-scale AI data centers. Felix and Ty discuss how their backgrounds in materials science led them to tackle one of the most pressing challenges in tech today: thermal efficiency and heat management at scale. They explore how Akash is overcoming the limitations of traditional semiconductors and how their innovations could significantly boost AI performance. Felix and Ty also talk about their collaboration with India’s sovereign cloud provider, the importance of strengthening U.S. manufacturing in the AI chip market, and the role Akash Systems could play in advancing satellite technologies. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil |@AkashSystems | @FelixEjeckam Show Notes: 0:00 Introduction 0:30 What is Akash Systems? 2:12 Felix’s personal path to building Akash Systems 4:45 Ty’s approach to acquiring customers 6:40 Challenges of operating in space 7:54 Live demo on diamond’s conductivity 9:50 Heat issues in data centers 15:38 Heat as a fundamental limit to technological progress 20:44 Akash’s role in the semiconductor market 22:54 Growing diamonds 25:10 Collaborating with India’s sovereign cloud provider 28:15 Importance of American manufacturing for AI chips and outlook on current data capacity  29:45 The Chips Act 31:22 Future of national security lies in satellite and radar tech 32:46 Critical issues in the U.S. AI supply chain 36:34 Deep learning’s role in material science discovery 40:16 The future: AI expanding our possibilities

In this episode of No Priors, Sarah talks with Eric Simons, co-founder and CEO of StackBlitz. The company has experienced explosive growth since the launch 2 months ago of Bolt.new, an AI application that lets users prompt, run, edit, and deploy full-stack applications directly in the browser. Eric talks about the years-long journey that led to overnight success, why so many non-technical users are forming a community around Bolt, and the democratization of coding. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EricSimons40 Show Notes: 0:00 Introduction 0:36 Bolt.new 2:04 How Bolt stands out from other coding assistants 3:28 Building beyond ChatGPT wrappers 6:13 Driving growth through community 9:42 Evals 13:29 Eric’s favorite use cases and startups leveraging Bolt 17:10 Why engineers are embracing no- code tools 24:32 The years long journey of StackBlitz 31:50 Balancing an Ironman, a newborn, and a product launch 35:18 Predictions for developers and code generation tools

In this episode of No Priors, Sarah is joined by Aidan Gomez, cofounder and CEO of Cohere. Aidan reflects on his journey to co-authoring the groundbreaking 2017 paper, “Attention is All You Need,” during his internship, and shares his motivations for building Cohere, which delivers AI-powered language models and solutions for businesses. The discussion explores the current state of enterprise AI adoption and Aidan’s advice for companies navigating the build vs. buy decision for AI tools. They also examine the drivers behind the flattening of model improvements and discuss where large language models (LLMs) fall short for predictive tasks. The conversation explores what the market has yet to account for in the rapidly evolving AI ecosystem, as well as Aidan’s personal perspectives on AGI—what it might look like and when it could arrive. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AidanGomez Show Notes: 0:00 Introduction 0:36 Co-authoring “Attention is all you need” 2:27 Leaving Google and founding Cohere 4:04 Cohere’s mission and models 6:15 Pitfalls of current AI  8:14 How enterprises are deploying AI today 10:58 Build vs. buy strategy for AI tools 14:37 Barriers to enterprise adoption  20:04 Which types of companies should pretrain models? 24:25 Addressing flaws in open-source models 25:12 Current and expected progress in scaling laws 29:54 Advances in multi-step problem solving and reasoning 32:29  Key drivers behind the flattening curve of model improvements  36:25 Exploring AGI 39:59 Limitations of LLMs 42:10 What the market has mispriced

In this week’s episode of No Priors, Sarah and Elad sit down with the Google DeepMind team behind AlphaProof, Laurent Sartran, Rishi Mehta, and Thomas Hubert. AlphaProof is a new reinforcement learning-based system for formal math reasoning that recently reached a silver-medal standard in solving International Mathematical Olympiad problems. They dive deep into AI and its role in solving complex mathematical problems, featuring insights into AlphaProof and its capabilities. They cover its functionality, unique strengths in reasoning, and the challenges it faces as it scales. The conversation also explores the motivations behind AI in math, practical applications, and how verifiability and human input come into play within a reinforcement learning approach. The DeepMind team shares advice and future perspectives on where math and AI are headed.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Rishicomplex | @LaurentSartran | @ThomasHubert Show Notes:  0:00 Personal introductions 2:19 Achieving silver medal in IMO competition 3:52 How AlphaProof works 5:56 AlphaProof’s strengths within mathematical reasoning 8:56 Challenges in scaling AlphaProof 13:40 Why solve math? 17:50 Pursuing knowledge versus practical applications 21:30 Insights on verifying correctness within reinforcement learning 28:27 How AI could foster more collaboration among mathematicians 30:28 Surprising insights from AI proof generation 34:17 Future of math and AI: advice for math enthusiasts and researchers

In this week’s episode of No Priors, Sarah and Elad sit down with Jensen Huang, CEO of NVIDIA, for the second time to reflect on the company’s extraordinary growth over the past year. Jensen discusses AI’s takeover of datacenters and NVIDIA’s rapid development of x.AI’s supercluster. The conversation also covers Nvidia’s decade-long infrastructure bets, software longevity, and innovations like NVLink. Jensen shares his views on the future of embodied AI, digital employees, and how AI is transforming scientific discovery. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Nvidia Show Notes:  00:00 Introduction 1:22 NVIDIA's 10-year bets 2:28 Outpacing Moore’s Law 3:42 Data centers and NVLink 7:16 Infrastructure flexibility for large-scale training and inference  10:40 Building and optimizing data centers  13:30 Maintaining software and architecture compatibility  15:00 X.AI’s supercluster  18:55 Challenges of super scaling data centers 20:39 AI’s role in chip design  22:23 NVIDIA's market cap surge and company evolution  27:03 Embodied AI 28:33 AI employees 31:25 Impact of AI on science and engineering  35:40 Jensen’s personal use of AI tools

In this week’s episode of No Priors, Sarah sits down with Tarek Mansour, CEO of Kalshi—the first CFTC-regulated prediction market exchange in the U.S. They dive into Kalshi’s recent victory to legalize election betting, explore ethical questions around trading on elections, and discuss whether prediction markets can offer more accuracy than traditional polls. Tarek shares insights on the history of futures markets, the line between gambling and financial trading, and the psychology behind betting. Plus, Sarah makes a live election bet, and Tarek reveals some of Kalshi’s most intriguing markets. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MansourTarek Show Notes:  0:00 Introduction 1:22 Sarah makes a live election bet on Kalshi 3:35 Getting approved and regulated by CFTC 5:48 Going up against the CFTC to legalize election betting 7:21 Debating the ethics of trading on elections 8:12 Gambling vs. trading  9:12 Context and purpose of futures markets 12:38 The human psychology behind speculating /Humans conditioned to risk taking 17:17 Building a healthy exchange and scaling liquidity  19:30 Introducing leverage and working with clearinghouses 22:29 Polls vs. prediction markets 24:59 Conditional markets 26:38 What makes Kalshi’s markets accurate 31:29 Tarek’s insights on the most interesting trades and markets on the platform

In this episode of No Priors, Dmitri Dolgov, Co-CEO of Waymo, joins Sarah and Elad to explore the evolution and advancements of Waymo's self-driving technology from its inception at Google to its current real-world deployment. Dmitri also shares insights into the technological breakthroughs and complexities of achieving full autonomy, the design innovations of Waymo’s sixth generation driverless cars, and the broader applications of Waymo’s advanced technology. They also discuss Waymo's strategic approach to scaling amidst regulation, deployment in cities like Phoenix and San Francisco, and the transformative potential of autonomous driving on car ownership and urban infrastructure. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Dmitri_Dolgov Shownotes: 00:00 Introduction 00:15 History of Self-Driving at Google  00:29 DARPA Challenges and Early Involvement  01:39 Formation of Waymo  01:53 Industry Lineage and Early Skepticism  03:05 Initial Goals and Milestones  4:33 Pivot to Full Autonomy  04:50 Scaling and Deployment  05:29 Generational Breakthroughs  06:59 Choosing Deployment Cities  09:26 Technological Advancements  11:01 Evaluating Safety  14:41 Regulatory Stance and Trust  16:52 Future of Autonomous Driving  23:19 Business Strategy and Partnerships  26:06 Changing Urban Mobility Trends  26:40 Challenges and Misconceptions in Self-Driving Timelines  28:43 The Role of Traditional OEMs in an Autonomous Future  30:54 Designing Cars for Autonomous Ride-Hailing  33:42 Scaling Responsibly  35:18 Generalizability and Future Applications of AI  37:10 The Complexity of Achieving Full Autonomy  42:58 The Importance of Data and Iteration in AI Development  46:13 Reflecting on the Journey and Future of Waymo

In this episode of No Priors, Sarah and Elad explore how AI is transforming consumer apps and entertainment, with a focus on potential integrations in gaming and dating that could shift traditional societal incentives. They reflect on AI researchers winning Nobel Prizes in Science and Chemistry for the first time, discussing what this trend means for scientific discovery. The episode also covers recent AI releases, including their thoughts on OpenAI’s O1 model and Google’s NotebookLM, and examines which companies and job functions are most at risk—or resilient—in the face of AI advancements. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Introduction (0:47) Google releases NotebookLM  (5:20) Integrating AI into consumer apps and gaming (9:11) Future of AI companionship and procreation (14:45) OpenAI o1 model improves on iterative reasoning (18:06) Sarah and Elad reflect on Nobel Prizes going to AI researchers (21:23) Jobs and businesses at risk of disruption (27:18) AI-durable companies

Today on No Priors, Elad is joined by Ankur Goyal, founder and CEO of Braintrust. Braintrust enables companies like Notion, Airtable, Instacart, Zapier, and Vercel to deploy AI solutions at scale by efficiently evaluating and managing complex, non-deterministic AI applications. Ankur shares his insights into emerging trends in the use of AI tooling and coding languages, the rise of open-source, and the future of data infrastructure. Ankur also reflects on building resilient AI products, his philosophy on coding as a CEO, and the importance of a startup’s initial customer base.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Ankrgyl Show Notes:  (0:00) Introduction (0:38) Ankur’s path to Braintrust (3:05) Braintrust’s solution (5:46) AI tooling trends  (7:58) Instruction tuning vs. fine-tuning (8:57) Open-source AI adoption  (10:42) Future of data infrastructure and synthetic data (14:45) Designing technical interviews (18:04) Rethinking agent-based approaches (19:34) Building out an AI team (23:35) Typescript as the language of AI (25:12) The shift away from using frameworks (26:02) Vendor consolidation among enterprises  (27:16) Coding as a CEO  (30:16) Collaborating with customers (33:00) Future of Braintrust and evals

Lina Khan’s FTC has been the most active in decades, notably challenging tech giants and adopting a more hands-on approach to regulating the digital age. On today’s episode of No Priors, Lina Khan joins Elad and Sarah to discuss her regulatory philosophy for tech markets and what the industry can expect for future M&A deals. She shares her approach to overseeing emerging technology sectors, including AI at the model layer, and her work to ban non-competes on a federal level. Khan also offers insights into the realities of leading a government agency, the scarcity of young leaders in power, and how she measures the FTC’s impact. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LinaKhanFTC Show Notes:  (0:00) Introduction (0:56) Lina Khan’s background and path to the FTC (2:35) Amazon’s Antitrust Paradox (4:20) Frameworks for regulating M&A in young markets (8:50) Khan’s perspective on AI acquisitions (12:18) What founders can expect from Khan’s M&A environment  (14:55) Promoting competition at the large model layer (17:01) Creating fair AI regulation (18:40) FTC’s work to ban non-competes (20:31) Why so few young people hold power in government today (22:18) The realities of running a government agency (24:20) Measuring the impact of FTC

In this episode of No Priors, Sarah and Elad sit down with Matt MacInnis, COO of Rippling, to discuss the company’s unique product strategy and the advantages of being a compound startup. Matt introduces Talent Signal, Rippling’s AI-powered employee performance tool, and explains how early adopters are using it to gain a competitive edge. They explore Rippling’s approach to choosing which AI products to build and how they plan to leverage their rich data sources. The conversation also delves into how AI shapes real-world decision-making and how to realistically integrate these tools into organizational workflows. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Stanine Show Notes:  0:00 Introduction 0:32 Rippling’s mission and product offerings 2:13 Compound startups 3:53 Evaluating human performance with Talent Signal  13:19 Incorporating AI evaluations into decision-making at Rippling 14:56 Leveraging work outputs as inputs for models 18:23 How Rippling chose which AI product to build first 20:53 Building out bundled products 23:26 Merging and scaling diverse data sources 25:16 Early adopters and integrating AI into decision-making processes

Bret Taylor, Cofounder of Sierra, Chairman of the board at OpenAI, and former co-CEO of Salesforce and CTO of Facebook, joins Sarah and Elad in this week’s episode of No Priors. Bret discusses building company-branded AI agents with unique personalities, goals, and guardrails at Sierra, and their potential to revolutionize customer engagement while cutting costs. The conversation explores the next sectors for enterprise AI adoption, building resilient AI products, and the parallels between today’s AI market and the evolution of the cloud industry. Bret also shares his unique insights on future business models and upcoming technology shifts. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Btaylor Show Notes: (0:00) Intro (0:42) Defining agentic systems and types of agents (3:55) Customer-facing company agents (5:43) Sierra AI (8:11) Transforming customer service and reducing costs (9:57) Challenges in implementing LLMs for company agents (14:45) Drawing parallels between AI and the cloud market’s evolution (17:50) Future of the AI landscape (19:15) Building durable AI products (24:39) Outcome-based business models and tangible ROI in AI solutions (29:22) Next wave of AI sectors for enterprise adoption (31:15) Customizing goals and guardrails with customers (35:55) Creating distinct personalities for Sierra's agents (41:05) Bret’s insights on upcoming technology and hardware shifts (46:50) How AI software could enhance human agency

In this episode of No Priors, Sarah and Elad go deep into what's on everyone’s mind. They break down new partnerships and consolidation in the LLM market, specialization of AI models, and AMD’s strategic moves. Plus, Elad is looking for a humanoid robot.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes: (0:00) Introduction (0:24) LLM market consolidation  (2:18) Competition and decreasing API costs (3:58) Innovation in LLM productization  (8:20) Comparing  the LLM and social network market (11:40) Increasing competition in image generation (13:21) Trend in smaller models with higher performance (14:43) Areas of innovation (17:33) Legacy of AirBnB and Uber pushing boundaries (24:19) AMD Acquires ZT  (25:49) Elad’s looking for a Robot

Andrej Karpathy joins Sarah and Elad in this week of No Priors. Andrej, who was a founding team member of OpenAI and former Senior Director of AI at Tesla, needs no introduction. In this episode, Andrej discusses the evolution of self-driving cars, comparing Tesla and Waymo’s approaches, and the technical challenges ahead. They also cover Tesla’s Optimus humanoid robot, the bottlenecks of AI development today, and  how AI capabilities could be further integrated with human cognition.  Andrej shares more about his new company Eureka Labs and his insights into AI-driven education, peer networks, and what young people should study to prepare for the reality ahead. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Karpathy Show Notes:  (0:00) Introduction (0:33) Evolution of self-driving cars (2:23) The Tesla  vs. Waymo approach to self-driving  (6:32) Training Optimus  with automotive models (10:26) Reasoning behind the humanoid form factor (13:22) Existing challenges in robotics (16:12) Bottlenecks of AI progress  (20:27) Parallels between human cognition and AI models (22:12) Merging human cognition with AI capabilities (27:10) Building high performance small models (30:33) Andrej’s current work in AI-enabled education (36:17) How AI-driven education reshapes knowledge networks and status (41:26) Eureka Labs (42:25) What young people study to prepare for the future

Today on No Priors, Sarah Guo and Elad Gil are joined by Eric Steinberger, the co-founder and CEO of Magic.dev. His team is developing a software engineer co-pilot that will act more like a colleague than a tool. They discussed what makes Magic stand out from the crowd of AI co-pilots, the evaluation bar for a truly great AI assistant, and their predictions on what a post-AGI world could look like if the transition is managed with care.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EricSteinb Show Notes:  (0:00) Introduction (0:45) Eric’s journey to founding Magic.dev (4:01) Long context windows for more accurate outcomes (10:53) Building a path toward AGI (15:18) Defining what is enough compute for AGI (17:34) Achieving Magic’s final UX (20:03) What makes a good AI assistant (22:09) Hiring at Magic (27:10) Impact of AGI (32:44) Eric’s north star for Magic (36:09) How Magic will interact in other tools

In this episode of No Priors, hosts Sarah and Elad are joined by Matt Garman, the CEO of Amazon Web Services. They talk about the evolution of Amazon Web Services (AWS) from its inception to its current position as a major player in cloud computing and AI infrastructure. In this episode they touch on AI commuting hardware,  partnerships with AI startups, and the challenges of scaling for AI workloads. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (00:00) Introduction  (00:23) Matt’s early days at Amazon (02:53) Early conception of AWS (06:36) Understanding the full opportunity of cloud compute (12:21) Blockers to cloud migration (14:19) AWS reaction to Gen AI (18:04) First-party models at hyperscalers (20:18) AWS point of view on open source (22:46) Grounding and knowledge bases (26:07) Semiconductors and data center capacity for AI workloads (31:15) Infrastructure investment for AI startups (33:18) Value creation in the AI ecosystem (36:22) Enterprise adoption  (38:48) Near-future predictions for AWS usage (41:25) AWS’s role for startups

In this episode of No Priors, hosts Sarah and Elad are joined by Jared Quincy Davis, former DeepMind researcher and the Founder and CEO of Foundry, a new AI cloud computing service provider. They discuss the research problems that led him to starting Foundry, the current state of GPU cloud utilization, and Foundry's approach to improving cloud economics for AI workloads. Jared also touches on his predictions for the GPU market and the thinking behind his recent paper on designing compound AI systems. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jaredq_ Show Notes:  (00:00) Introduction  (02:42) Foundry background (03:57) GPU utilization for large models (07:29) Systems to run a large model (09:54) Historical value proposition of the cloud (14:45) Sharing cloud compute to increase efficiency  (19:17) Foundry’s new releases (23:54) The current state of GPU capacity (29:50) GPU market dynamics (36:28) Compound systems design (40:27) Improving open-ended tasks

In this episode of No Priors, hosts Sarah and Elad are joined by Ramp co-founders Eric Glyman and Karim Atiyeh of Ramp. The pair has been working to build one of the fastest growing fintechs since they were teenagers. This conversation focuses on how Ramp engineers have been building new systems to help every team from sales and marketing to product. They’re building best-in-class SaaS solutions just for internal use to make sure their company remains competitive. They also get into how AI will augment marketing and creative fields, the challenges of selling productivity, and how they’re using LLMs to create internal podcasts using sales calls to share what customers are saying with the whole team.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @eglyman l @karimatiyeh Show Notes:  (0:00) Introduction to Ramp (3:17) Working with startups (8:13) Ramp’s implementation of AI (14:10) Resourcing and staffing (17:20) Deciding when to build vs buy (21:20) Selling productivity (25:01) Risk mitigation when using AI (28:48) What the AI stack is missing (30:50) Marketing with AI (37:26) Designing a modern marketing team (40:00) Giving creative freedom to marketing teams (42:12) Augmenting bookkeeping (47:00) AI-generated podcasts 

Hunting down receipts and manually filling out invoices kills productivity. This week on No Priors, Sarah Guo and Elad Gil sit down with Pedro Franceschi, co-founder and CEO of Brex. Pedro discusses how Brex is harnessing AI to optimize spend management and automate tedious accounting and compliance tasks for teams. The conversation covers the reliability challenges in AI today, Pedro’s insights on the future of fintech in an AI-driven world, and the major transitions Brex has navigated in recent years. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Pedroh96 Show Notes:  (0:00) Introduction (0:32) Brex’s business and transitioning to solo CEO (3:04) Building AI into Brex  (7:09) Solving for risk and reliability in AI-enabled financial products (11:41) Allocating resources toward AI investment (14:00) Innovating data use in marketing  (20:00) Building durable businesses in the face of AI (25:36) AI’s impact on finance (29:15) Brex’s decision to focus on startups and enterprises

In this episode of No Priors, hosts Sarah and Elad are joined by Oriol Vinyals, VP of Research, Deep Learning Team Lead, at Google DeepMind and Technical Co-lead of the Gemini project. Oriol shares insights from his career in machine learning, including leading the AlphaStar team and building competitive StarCraft agents. We talk about Google DeepMind, forming the Gemini project, and integrating AI technology throughout Google products. Oriol also discusses the advancements and challenges in long context LLMs, reasoning capabilities of models, and the future direction of AI research and applications. The episode concludes with a reflection on AGI timelines, the importance of specialized research, and advice for future generations in navigating the evolving landscape of AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @oriolvinyalsml Show Notes:  (00:00) Introduction to Oriol Vinyals (00:55) The Gemini Project and Its Impact (02:04) AI in Google Search and Chat Models (08:29) Infinite Context Length and Its Applications (14:42) Scaling AI and Reward Functions (31:55) The Future of General Models and Specialization (38:14) Reflections on AGI and Personal Insights (43:09) Will the Next Generation Study Computer Science? (45:37) Closing thoughts

This week on No Priors, Sarah Guo and Elad Gil are joined by Howie Liu, the co-founder and CEO of Airtable. Howie discusses their Cobuilder launch, the evolution of Airtable from a simple productivity tool to an enterprise app platform with integrated AI capabilities. They talk about why the conventional wisdom of “app not platform” can be wrong,  why there’s a future for low-code in the age of AI and code generation, and where enterprises need help adopting AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Howietl Show Notes:  (00:00) Introduction (00:29) The Origin and Evolution of Airtable (02:31) Challenges and Successes in Building Airtable (06:09) Airtable's Transition to Enterprise Solutions (09:44) Insights on Product Management (16:23) Integrating AI into Airtable (21:55) The Future of No Code and AI (30:30) Workshops and Training for AI Adoption (36:28) The Role of Code Generation in No Code Platforms

This week on No Priors, we have a host-only episode. Sarah and Elad catch up to discuss how tech history may be repeating itself. Much like in the early days of the internet, every company is clamoring to incorporate AI into their products or operations while some legacy players are skeptical that investment in AI will pay off. They also get into new opportunities and capabilities that AI is opening up, whether or not incubators are actually effective, and what companies are poised to stand the test of time in the changing tech landscape. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes:  (0:00) Introduction (0:16) Old school operators AI misunderstandings (5:10) Tech history is repeating itself with slow AI adoption (6:09) New AI Markets (8:48) AI-backed buyouts (13:03) AI incubation (17:18) Exciting incubating applications (18:26) AI and the public markets (22:20) Staffing AI companies  (25:14) Competition and shrinking head count

Believe or not, we’re almost halfway through 2024. Sarah and Elad have spent the first of this year talking with some of the most innovative minds in the AI industry, so we’re taking a look at some of our favorite No Priors conversations so far featuring Dylan Field (Figma); Emily Glassberg-Sands (Stripe); Brett Adcock (Figure AI); Aditya Ramesh, Tim Brooks and Bill Peebles (OpenAI’s Sora Team); Scott Wu (Cognition); and Alexandr Wang (Scale). Watch or listen to the full episodes here: Build AI products at on-AI companies with Emily Glassberg Sands from Stripe Designing the Future: Dylan Field on AI, Collaboration, and Independence The argument for humanoid robots with Brett Adcock from Figure OpenAI’s Sora team thinks we’ve only seen the "GPT-1 of video models" Cognition’s Scott Wu on how Devin, the AI software engineer, will work for you The Data Foundry for AI with Alexandr Wang from Scale Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Introduction (0:46) Emily Glassberg Sands on the Future of AI and Fintech (4:23 Dylan Field on AI and Human Creative Potential (9:03) Brett Adcock on Running Figure AI’s Hardware and Software Processes (12:43) OpenAI’s Sora Team on Artists’ Creative Experiences with their Model (17:43) Scott Wu Gives Advice for Human Engineers Co-Working with AI (21:06) Alexandr Wang on How Quality Data Builds Confidence in AI Systems

This week on No Priors, Sarah Guo and Elad Gil sit down with Karan Goel and Albert Gu from Cartesia. Karan and Albert first met as Stanford AI Lab PhDs, where their lab invented Space Models or SSMs, a fundamental new primitive for training large-scale foundation models. In 2023, they Founded Cartesia to build real-time intelligence for every device. One year later, Cartesia released Sonic which generates high quality and lifelike speech with a model latency of 135ms—the fastest for a model of this class. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @krandiash | @_albertgu Show Notes:  (0:00) Introduction (0:28) Use Cases for Cartesia and Sonic  (1:32) Karan Goel & Albert Gu’s professional backgrounds (5:06) State Space Models (SSMs) versus Transformer Based Architectures  (11:51) Domain Applications for Hybrid Approaches  (13:10) Text to Speech and Voice (17:29) Data, Size of Models and Efficiency  (20:34) Recent Launch of Text to Speech Product (25:01) Multimodality & Building Blocks (25:54) What’s Next at Cartesia?  (28:28) Latency in Text to Speech (29:30) Choosing Research Problems Based on Aesthetic  (31:23) Product Demo (32:48) Cartesia Team & Hiring

 AI video generation models still have a long way to go when it comes to making compelling and complex videos but the HeyGen team are well on their way to streamlining the video creation process by using a combination of language, video, and voice models to create videos featuring personalized avatars, b-roll, and dialogue. This week on No Priors, Joshua Xu the co-founder and CEO of HeyGen,  joins Sarah and Elad to discuss how the HeyGen team broke down the elements of a video and built or found models to use for each one, the commercial applications for these AI videos, and how they’re safeguarding against deep fakes.  Links from episode: HeyGen McDonald’s commercial Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil |  @joshua_xu_ Show Notes:  (0:00) Introduction (3:08) Applications of AI content creation (5:49) Best use cases for Hey Gen (7:34) Building for quality in AI video generation (11:17) The models powering HeyGen (14:49) Research approach (16:39) Safeguarding against deep fakes (18:31) How AI video generation will change video creation (24:02) Challenges in building the model (26:29) HeyGen team and company

The first step in achieving AGI is nailing down a concise definition and Mike Knoop, the co-founder and Head of AI at Zapier, believes François Chollet got it right when he defined general intelligence as a system that can efficiently acquire new skills. This week on No Priors, Miked joins Elad to discuss ARC Prize which is a multi-million dollar non-profit public challenge that is looking for someone to beat the Abstraction and Reasoning Corpus (ARC) evaluation. In this episode, they also get into why Mike thinks LLMs will not get us to AGI, how Zapier is incorporating AI into their products and the power of agents, and why it’s dangerous to regulate AGI before discovering its full potential.  Show Links: About the Abstraction and Reasoning Corpus Zapier Central ARC Prize Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mikeknoop Show Notes:  (0:00) Introduction (1:10) Redefining AGI (2:16) Introducing ARC Prize (3:08) Definition of AGI (5:14) LLMs and AGI (8:20) Promising techniques to developing AGI (11:0) Sentience and intelligence (13:51) Prize model vs investing (16:28) Zapier AI innovations (19:08) Economic value of agents (21:48) Open source to achieve AGI (24:20) Regulating AI and AGI

After Tengyu Ma spent years at Stanford researching AI optimization, embedding models, and transformers, he took a break from academia to start Voyage AI which allows enterprise customers to have the most accurate retrieval possible through the most useful foundational data. Tengyu joins Sarah on this week’s episode of No priors to discuss why RAG systems are winning as the dominant architecture in enterprise and the evolution of foundational data that has allowed RAG to flourish. And while fine-tuning is still in the conversation, Tengyu argues that RAG will continue to evolve as the cheapest, quickest, and most accurate system for data retrieval.  They also discuss methods for growing context windows and managing latency budgets, how Tengyu’s research has informed his work at Voyage, and the role academia should play as AI grows as an industry.  Show Links: Voyage AI Stanford Assistant Professor of Computer Science Tengyu Ma Key Research Papers: Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training Non-convex optimization for machine learning: design, analysis, and understanding Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss Larger language models do in-context learning differently, 2023 Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning On the Optimization Landscape of Tensor Decompositions Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tengyuma Show Notes:  (0:00) Introduction (1:59) Key points of Tengyu’s research (4:28) Academia compared to industry (6:46) Voyage AI overview (9:44) Enterprise RAG use cases (15:23) LLM long-term memory and token limitations (18:03) Agent chaining and data management (22:01) Improving enterprise RAG  (25:44) Latency budgets (27:48) Advice for building RAG systems (31:06) Learnings as an AI founder (32:55) The role of academia in AI

Garry Tan is a notorious founder-turned-investor who is now running one of the most prestigious accelerators in the world, Y Combinator. As the president and CEO of YC, Garry has been credited with reinvigorating the program. On this week’s episode of No Priors, Sarah, Elad, and Garry discuss the shifting demographics of YC founders and how AI is encouraging younger founders to launch companies, predicting which early stage startups will have longevity, and making YC a beacon for innovation in AI companies. They also discussed the importance of building companies in person and if San Francisco is, in fact, back.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @garrytan Show Notes:  (0:00) Introduction (0:53) Transitioning from founder to investing (5:10) Early social media startups (7:50) Trend predicting at YC (10:03) Selecting YC founders (12:06) AI trends emerging in YC batch (18:34) Motivating culture at YC (20:39) Choosing the startups with longevity (24:01) Shifting YC found demographics (29:24) Building in San Francisco  (31:01) Making YC a beacon for creators (33:17) Garry Tan is bringing San Francisco back

Alexandr Wang was 19 when he realized that gathering data will be crucial as AI becomes more prevalent, so he dropped out of MIT and started Scale AI. This week on No Priors, Alexandr joins Sarah and Elad to discuss how Scale is providing infrastructure and building a robust data foundry that is crucial to the future of AI. While the company started working with autonomous vehicles, they’ve expanded by partnering with research labs and even the U.S. government.   In this episode, they get into the importance of data quality in building trust in AI systems and a possible future where we can build better self-improvement loops, AI in the enterprise, and where human and AI intelligence will work together to produce better outcomes.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alexandr_wang (0:00) Introduction (3:01) Data infrastructure for autonomous vehicles (5:51) Data abundance and organization (12:06)  Data quality and collection (15:34) The role of human expertise (20:18) Building trust in AI systems (23:28) Evaluating AI models (29:59) AI and government contracts (32:21) Multi-modality and scaling challenges

Mikey Shulman, the CEO and co-founder of Suno, can see a future where the Venn diagram of music creators and consumers becomes one big circle. The AI music generation tool trying to democratize music has been making waves in the AI community ever since they came out of stealth mode last year. Suno users can make a song complete with lyrics, just by entering a text prompt, for example, “koto boom bap lofi intricate beats.” You can hear it in action as Mikey, Sarah, and Elad create a song live in this episode.  In this episode, Elad, Sarah, And Mikey talk about how the Suno team took their experience making at transcription tool and applied it to music generation, how the Suno team evaluates aesthetics and taste because there is no standardized test you can give an AI model for music, and why Mikey doesn’t think AI-generated music will affect people’s consumption of human made music.  Listen to the full songs played and created in this episode: Whispers of Sakura Stone  Statistical Paradise Statistical Paradise 2 Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MikeyShulman Show Notes:  (0:00) Mikey’s background (3:48) Bark and music generation (5:33) Architecture for music generation AI (6:57) Assessing music quality (8:20) Mikey’s music background as an asset (10:02) Challenges in generative music AI (11:30) Business model (14:38) Surprising use cases of Suno (18:43) Creating a song on Suno live (21:44) Ratio of creators to consumers (25:00) The digitization of music (27:20) Mikey’s favorite song on Suno (29:35) Suno is hiring

This week on No Priors hosts, Sarah and Elad are catching up on the latest AI news. They discuss the recent developments in AI like Meta’s new AI assistant and the latest in music generation, and if you’re interested in generative AI music, stay tuned for next week’s interview! Sarah and Elad also get into device-resident models, AI hardware, and ask just how smart smaller models can really get. These hardware constraints were compared to the hurdles AI platforms are continuing to face including computing constraints, energy consumption, context windows, and how to best integrate these products in apps that users are familiar with. Have a question for our next host-only episode or feedback for our team? Reach out to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Intro (1:25) Music AI generation (4:02) Apple’s LLM (11:39) The role of AI-specific hardware (15:25) AI platform updates (18:01) Forward thinking in investing in AI (20:33) Unlimited context (23:03) Energy constraints

Scott Wu loves code. He grew up competing in the International Olympiad in Informatics (IOI) and is a world class coder, and now he's building an AI agent designed to create more, not fewer, human engineers. This week on No Priors, Sarah and Elad talk to Scott, the co-founder and CEO of Cognition, an AI lab focusing on reasoning. Recently, the Cognition team released a demo of Devin, an AI software engineer that can increasingly handle entire tasks end to end. In this episode, they talk about why the team built Devin with a UI that mimics looking over another engineer’s shoulder as they work and how this transparency makes for a better result. Scott discusses why he thinks Devin will make it possible for there to be more human engineers in the world, and what will be important for software engineers to focus on as these roles evolve. They also get into how Scott thinks about building the Cognition team and that they’re just getting started.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ScottWu46 Show Notes:  (0:00) Introduction (1:12) IOI training and community (6:39) Cognition’s founding team (8:20) Meet Devin (9:17) The discourse around Devin (12:14) Building Devin’s UI (14:28) Devin’s strengths and weakness  (18:44) The evolution of coding agents (22:43) Tips for human engineers (26:48) Hiring at Cognition

AI-generated videos are not just leveled-up image generators. But rather, they could be a big step forward on the path to AGI. This week on No Priors, the team from Sora is here to discuss OpenAI’s recently announced generative video model, which can take a text prompt and create realistic, visually coherent, high-definition clips that are up to a minute long. Sora team leads, Aditya Ramesh, Tim Brooks, and Bill Peebles join Elad and Sarah to talk about developing Sora. The generative video model isn’t yet available for public use but the examples of its work are very impressive. However, they believe we’re still in the GPT-1 era of AI video models and are focused on a slow rollout to ensure the model is in the best place possible to offer value to the user and more importantly they’ve applied all the safety measures possible to avoid deep fakes and misinformation. They also discuss what they’re learning from implementing diffusion transformers, why they believe video generation is taking us one step closer to AGI, and why entertainment may not be the main use case for this tool in the future.  Show Links: Bling Zoo video Man eating a burger video Tokyo Walk video Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @_tim_brooks l @billpeeb l @model_mechanic Show Notes:  (0:00) Sora team Introduction (1:05) Simulating the world with Sora (2:25) Building the most valuable consumer product (5:50) Alternative use cases and simulation capabilities (8:41) Diffusion transformers explanation (10:15) Scaling laws for video (13:08) Applying end-to-end deep learning to video (15:30) Tuning the visual aesthetic of Sora (17:08) The road to “desktop Pixar” for everyone (20:12) Safety for visual models (22:34) Limitations of Sora (25:04) Learning from how Sora is learning (29:32) The biggest misconceptions about video models

Multimodal models are making it possible to create AI art and augment creativity across artistic mediums. This week on No Priors, Sarah and Elad talk with Suhail Doshi, the founder of Playground AI, an image generator and editor. Playground AI has been open-sourcing foundation diffusion models, most recently releasing Playground V2.5.  In this episode, Suhail talks with Sarah and Elad about how the integration of language and vision models enhances the multimodal capabilities, how the Playground team thought about creating a user-friendly interface to make AI-generated content more accessible, and the future of AI-powered image generation and editing. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Suhail Show Notes:  (0:00) Introduction (0:52) Focusing on image generation (3:01) Differentiating from other AI creative tools (5:58) Training a Stable Diffusion model (8:31) Long term vision for Playground AI (15:00) Evolution of AI architecture (17:21) Capabilities of multimodal models (22:30) Parallels between audio AI tools and image-generation

This week on a host-only episode of No Priors, Sarah and Elad discuss the AI wave as compared to the internet wave, the current state of AI investing, the foundation model landscape, voice and video AI, advances in agentic systems, prosumer applications, and the Microsoft/Inflection deal. Have a question for our next host-only episode or feedback for our team? Reach out to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Intro (0:32) How to think about scaling in 2024 (3:21) Microsoft/Inflection deal (5:28) Voice cloning (7:02) Investing climate (12:50) Whitespace in AI (16:36) AI video landscape (19:54) Agentic user experiences (22:21) Prosumer as the first wave of application AI

Humans are always doing work that is dull or dangerous. Brett Adcock, the founder and CEO of Figure AI, wants to build a fleet of robots that can do everything from work in a factory or warehouse to folding your laundry in the home. Today on No Priors, Sarah got the chance to talk with Brett about how a company that is only 21 months old has already built humanoid robots that not only walk the walk by performing tasks like item retrieval and making a cup of coffee but they also talk the talk through speech to speech reasoning.  In this episode, Brett and Sarah discuss why right now is the correct time to build a fleet of AI robots and how implementation in industrial settings will be a stepping stone into AI robots coming into the home. They also get into how Brett built a team of world class engineers, commercial partnerships with BMW and OpenAI that are accelerating their growth, and the plan to achieve social acceptance for AI robots.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @adcock_brett Show Notes:  (0:00) Brett’s background (3:09) Figure AI Thesis (5:51) The argument for humanoid robots (7:36) Figure AI public demos (12:38) Mitigating risk factors (15:20) Designing the org chart and finding the team (16:38) Deployment timeline (20:41) Build vs buy and vertical integration (23:04) Product management at Figure (28:37) Corporate partnerships (31:58) Humans at home (33:38) Social acceptance  (35:41) AGI vs the robots

Companies are employing AI agents and co-pilots to help their teams increase efficiency and accuracy, but developing apps that are trained properly can require a skill set many enterprise teams don’t have. This week on No Priors, Sarah and Elad are joined by Harrison Chase, the CEO and co-founder of LangChain, an open-source framework and developer toolkit that helps developers build LLM applications. In this conversation they talk about the gaps in open source app development, what it will take to keep up with private companies, the importance of creating prompts that can be compatible with many API models, and why memory is so undeveloped in this space.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil |@hwchase17 Show Notes:  (0:00) Introduction to LangChain (1:45) Managing an open source environment (4:30) Developing useful AI agents (10:03) Sophistication and limitations of AI app development (14:17) Switching between model APIs (17:10) Context windows, fine-tuning and functionality (21:37) Evolution of AI open source environment (23:53) The next big breakthroughs

At a time when users are being asked to wait unthinkable seconds for AI products to generate art and answers, speed is what will win the battle heating up in AI computing. At least according to today’s guest, Tuhin Srivastava, the CEO and co-founder of Baseten which gives customers scalable AI infrastructures starting with interference. In this episode of No Priors, Sarah, Elad, and Tuhin discuss why efficient code solutions are more desirable than no code, the most surprising use cases for Baseten, and why all of their jobs are very defensible from AI.  Show Links: Baseten Benchmarking fast Mistral 7B inference Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @tuhinone Show Notes:  (0:00) Introduction (1:19) Capabilities of efficient code enabled development (4:11) Difference in training inference workloads (6:12) AI product acceleration (8:48) Leading on inference benchmarks at Baseten (12:08) Optimizations for different types of models (16:11) Internal vs open source models (19:01) timeline for enterprise scale (21:53) Rethinking investment in compute spend (27:50) Defensibility in AI industries (31:30) Hardware and the chip shortage (35:47) Speed is the way to win in this industry (38:26) Wrap

Figma has had a banner year and the formidable team isn’t slowing down—even after regulatory issues blocked the merger with Adobe. Today on No Priors, Sarah and Elad are joined by Dylan Field the CEO and founder of Figma, the design collaboration tool that is closing the gap between imagination and reality. They discuss what’s next for an independent Figma, how AI can augment design and speed up the iteration loop, and how Figma is expanding beyond design with products that help the entire product team’s workflow. Show Links: https://www.figma.com/ Figma and Adobe are abandoning our proposed merger Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @zoink Show Notes:  (0:00) Introduction (2:01) No more Adobe acquisition  (4:20) What’s next for Figma (7:16) FigJam, digital collaboration, and expanding beyond design (10:50) Figma DevMode (13:06) Incorporating AI at Figma (15:03) How AI will change design (19:19) Creativity augmentation and the iterative loop (22:44) Automating repetitive design tasks (25:35) The future of AI UI (29:44) Investing philosophy (31:28) Leadership evolution

Host-only episode discussing NVIDIA, Meta and Google earnings, Gemini and Mistral model launches, the open-vs-closed source debate, domain specific foundation models, if we’ll see real competition in chips, and the state of AI ROI and adoption. Don’t miss our episodes with: Mistral NVIDIA AMD Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes:  (0:00) Introduction (0:27) Model news and product launches (5:01) Google enters the competitive space with Gemini 1.5 (8:23) Biology and robotics using LLMs (10:22) Agent-centric companies (14:22) NVIDIA earnings (17:29) ROI in AI (20:43) Impact from AI (25:45) Building effective AI tools in house (29:09) What would it take to compete with NVIDIA (33:23) The architectural approach to compute (35:42) the roadblocks to chip production in the US (38:30) The virtuous tech cycles in AI

Compute is the fuel for the AI revolution, and customers want more chip vendors. AMD CTO Mark Papermaster joins Sarah and Elad on No Priors to discuss AMD’s strategy, their newest GPUs, where inference workloads will live, the chip software stack, how they are thinking about supply chain issues, and what we can expect from AMD in 2024.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes:  (0:00) Introduction and Mark’s background (2:35) AMD background and current markets (4:40) AMD shifting to AI space (8:54) AI applications coming out of AMD (10:57) Software investment (15:15) The benefits of open-source stacks (16:58) Evolving GPU market (20:21) Constraints on GPU production (24:11) Innovations in chip technology (27:57) Chip supply chain (30:18) Future of innovative hardware products (35:42) What’s next for AMD

Accurate, customizable search is one of the most immediate AI use cases for companies and general users. Today on No Priors, Elad and Sarah are joined by Pinecone CEO, Edo Liberty, to talk about how RAG architecture is improving syntax search and making LLMs more available. By using a RAG model Pinecone makes it possible for companies to vectorize their data and query it for the most accurate responses.  In this episode, they talk about how Pinecone’s Canopy product is making search more accurate by using larger data sets in a way that is more efficient and cost effective—which was almost impossible before there were serverless options. They also get into how RAG architecture uniformly increases accuracy across the board, how these models can increase “operational sanity” in the dataset  for their customers, and hybrid search models that are using keywords and embeds.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EdoLiberty Show Notes:  (0:00) Introduction to Edo and Pinecone (2:01) Use cases for Pinecone and RAG models (6:02) Corporate internal uses for syntax search (10:13) Removing the limits of RAG with Canopy (14:02) Hybrid search (16:51) Why keep Pinecone closed source (22:29) Infinite context (23:11) Embeddings and data leakage (25:35) Fine tuning the data set (27:33) What’s next for Pinecone  (28:58) Separating reasoning and knowledge in AI

Notion is a productivity app that has invested heavily in AI to create products that enable workers to access information instantly without having to search through their own countless notes. Today on No Priors, Sarah and Elad are joined by Ivan Zhao, the co-founder and CEO of Notion, to talk about Notions Q&A interface and calendar applications. They also get into how using RAG models means better retrieval, longer memory, and the user can be less organized and how Notion is leading the charge in this era of SaaS bundling products. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ivanhzhao Show Notes:  (0:00) Introduction (2:09) AI and Computing literacy (5:39) Building the Notion AI team (8:43) Notion as an application company (12:09) Prioritizing AI investment (14:53) The rapid evolution cycle of AI development (17:46) Notion Q&A (20:00) Workflow and AI for calendars (22:43) Moving past the need for organization (24:36) History of SaaS doesn’t repeat, it rhymes (30:14) Design at Notion (34:26) Notion office design (36:52) How RAG will change the future (38:30) Building our the software in the Notionscape

Many companies that are building AI products for their users are not primarily AI companies. Today on No Priors, Sarah and Elad are joined by Emily Glassberg Sands who is the Head of Information at Stripe. They talk about how Stripe prioritizes AI projects and builds these tools from the inside out. Stripe was an early adopter of utilizing LLMs to help their end user. Emily talks about how they decided it was time to meaningfully invest in AI given the trajectory of the industry and the wealth of information Stripe has access to. The company’s goal with utilizing AI is to empower non-technical users to code using natural language and for technical users to be able to work much quicker and in this episode she talks about how their Radar Assistant and Sigma Assistant achieve those goals.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @emilygsands Show Notes:  (0:00) Background (0:38) Emily’s role at Stripe (2:31) Adopting early gen AI models (4:44) Promoting internal usage of AI (8:17) Applied ML accelerator teams (10:36) Radar fraud assistant (13:30) Sigma assistant (14:32) How will AI affect Stripe in 3 years (17:00) Knowing when it’s time to invest more fully in AI (18:28) Deciding how to proliferate models (22:04) Whitespace for fintechs employing AI (25:41) Leveraging payments data for customers (27:51) Labor economics and data (30:10) Macro economic trends for strategic decisions (32:54) How will AI impact education (35:36) Unique needs of AI startups

Building an ecommerce business is hard – it requires merchants to have a wealth of skills: technical, logistics, marketing, pricing, vendor management, finance and analytics. That’s why Shopify is releasing new AI features that help merchants tackle things like product descriptions, marketing suggestions and search. Today on No Priors, Glen Coates, the VP of core product at Shopify (and former founder of b2b wholesale platform Handshake), joins Sarah and Elad. They talk about the releases from Shopify Editions, why they are deploying “copilot” rather than “autopilot,” AI innovation-at-scale, how to change the basement of a house while people are living in it, and building a leadership team of entrepreneurs. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @glencoates Shopify Editions | AI Section of Shopify Editions Show Notes:  (0:00) Background (2:22) Calling a “Code Red” at Shopify (4:04) Integrating acquisitions, entrepreneurial leaders (12:15) AI adoption (15:51) Deciding when to ship AI products, evaluations (17:33) Shopify’s risk orientation (18:50) Changing the core Shopify data model, enabling AI features (26:05) What’s missing from LLMs for merchants (28:47) Most interesting AI developments in the industry (33:22) What users want from LLMs and search (38:20) No Priors social

Building adaptive AI models that can learn and complete tasks in the physical world requires precision but these AI robots could completely change manufacturing and logistics processes. Peter Chen, the co-founder and CEO of Covariant, leads the team that is building robots that will increase manufacturing efficiency, safety, and create warehouses of the future.  Today on No Priors, Peter joins Sarah to talk about how the Covariant team is developing multimodal models that have precise grounding and understanding so they can adapt to solve problems in the physical world. They also discuss how they plan their roadmap at Covariant, what could be next for the company, and what use case will bring us to the Chat-GPT moment for AI robots. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @peterxichen Show Notes:  (0:00) Peter Chen Background (0:58) How robotics AI will drive AI forward (3:00) Moving from research to a commercial company (5:46) The argument for building incrementally  (8:13) Manufacturing robotics today (12:21) Put wall use case (15:45) What’s next for Covariant Brain (18:42) Covariant’s customers (19:50) Grounding concepts in Ai (25:47) How scaling laws apply to Covariant (29:21) Covariant’s driving thesis (32:54) the Chat-GPT moment for robotics (35:12) Manufacturing center of the future (37:02) Safety in AI robotics

Coding in collaboration with AI can reduce human toil in the software development process and lead to more accurate and less tedious work for coding teams. This week on No Priors, Sarah talked with Beyang Liu, the cofounder and CTO of Sourcegraph, which builds tools that help developers innovate faster. Their most recent launch was an AI coding assistant called Cody. Beyang has spent his entire career thinking about how humans can work in conjunction with AI to write better code. Sarah and Beyang talk about how Sourcegraph is thinking about augmenting the coding process in a way that ensures accuracy and efficiency starting with robust and high-quality context. They also think about what the future of software development could look like in a world where AI can generate high-quality code on its own and where that leaves humans in the coding process.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @beyang Show Notes:  (0:00) Beyang Liu’s experience (0:52) Sourcegraph premise (2:20) AI and finding flow (4:18) Developing LLMs in code (6:46) Cody explanation (7:56) Unlocking AI code generation (11:00) search architecture in LLMs (16:02) Quality-assurance in data set (18:03) Future of Cody (22:48) Constraints in AI code generation (30:28) Lessons from Beyang’s research days (33:17) Benefits of small models (35:49) Future of software development (42:14) What skills will be valued down the line

We’re looking back on 2023 and sharing a handful of our favorite conversations. Last year was full of insightful conversations that shaped the way we think about the most innovative movements in the AI space. Want to hear more? Check out the full episodes here: What is Digital Life? with OpenAI Co-Founder & Chief Scientist Ilya Sutskever  How AI can help small businesses with Former Square CEO Alyssa Henry Will Everyone Have a Personal AI? With Mustafa Suleyman, Founder of DeepMind and Inflection How will AI bring us the future of medicine? With Daphne Koller from Insitro The case for AI optimism with Reid Hoffman from Inflection AI Your AI Friends Have Awoken, With Noam Shazeer Mistral 7B and the Open Source Revolution With Arthur Mensch, CEO Mistral AI The Computing Platform Underlying AI with Jensen Huang, Founder and CEO NVIDIA Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @reidhoffman l @alyssahhenry l @ilyasut l @mustafasuleyman l @DaphneKoller l @arthurmensch l @MrJensenHuang Show Notes:  (0:00) Introduction (0:27) Ilya Sutskever on the governance structure of OpenAI (3:11) Alyssa Henry on how AI can small business owners (5:25) Mustafa Suleyman on defining intelligence (8:53) Reid Hoffman’s advice for co-working with AI (11:47) Daphne Koller on probabilistic graphical models (13:15) Noam Shazeer on the possibilities of LLMs (14:27) Arthur Mensch on keeping AI open (17:19) Jensen Huang on how Nvidia decides what to work on

AI doomerism and calls to regulate the emerging technology is at a fever pitch but today’s guest, Reid Hoffman is a vocal AI optimist who views slowing down innovation as anti-humanistic. Reid needs no introduction, he’s the co-founder of PayPal, Linkedin, and most recently Inflection AI which is building empathetic AI companions. He is also a board member at Microsoft and former board member at OpenAI. On this week’s episode, Reid joins Sarah and Elad to talk about the historical case for an optimistic outlook on emerging technology like AI, advice for workers who fear AI may replace them, and why it’s impossible to regulate before you innovate. Plus, some predictions. Aside from his storied experience in technology, Reid is an author, podcaster, and political activist. Most recently, he co-authors a book with GPT 4 called Impromptu: Amplifying Our Humanity Through AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alyssahhenry Show Notes:  (0:00) Reid Hoffman’s birdseye view on the state of AI (3:37) AI and human collaboration in workflows (5:23) What’s causing AI doomerism (12:28) Advice for whitecollar workers (16:45) Why Reid isn’t retiring (18:25) How Inflection started (22:06) Surprising ways people are using Inflection (25:34) Western bias and AI ethics (30:58) Structural challenges in governing AI (33:15) Most exciting whitespace in AI (35:00) GPT 5 and Innovations coming in the next two years (44:00) What future should we be building?

AI tools are helping small business owners manage their businesses, so they can stay focused on the aspects of their business they love to do. This week on No Priors, Sarah and Elad are joined by Alyssa Henry, an executive at some of the most impactful companies from Microsoft to Amazon. Most recently she was the CEO of Square. She led Square’s team as they were very early adopters of a consumer-facing product that used GPT-2 and have continued to incorporate AI into their offerings. On today’s episode, they talk about the whitespace within e-commerce for AI and lessons from the prior generation of infrastructure. Alyssa recently retired from being longtime CEO of Square, within Block. Before that she was a vice president of AWS running, amongst other things, the storage products, or the digital storage bucket for the world. And before AWS, she ran order management software at Amazon Retail and started her tech career at Microsoft. She remains on the boards of Intel, Confluent and was previously on the board of Unity.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alyssahhenry Show Notes:  (0:00) Alyssa’s experience and career trajectory (2:30) Transition from engineer to manager (4:09) AI implementation at Square (7:46) Small business AI applications  (12:14) Latent demand for content generation (15:04) The origin story of Square’s GPT-2 products (16:54) Consolidating ecommerce workflows (18:46) How will AI change cloud services (23:07) Hyperscaler foundation models and the AI land grab (25:16) Enterprise demand for open source models (28:08) Startups in the AI semiconductor space (31:02) Scale up architectures vs scaling out (34:32) What’s next for Alyssa (36:08) What Elad and Sarah are excited about in 2024

AI is the new UI for enterprise customers, according to Clara Shih, the CEO of Salesforce AI. Salesforce released Einstein, now called Einstein GPT, in 2016, making it an early example of how beneficial AI can be when embedded in enterprise software. This week on No Priors, Sarah and Elad talked with Clara about what the evolution of AI in enterprise looks like, how Salesforce is adoption AI across the organization, and the onboarding process for companies looking to integrate AI into their workflow, plus the challenges of pricing for AI services. Clara Shih is the Chief Executive Officer of Salesforce AI where she leads the AI efforts across Salesforce including AI co-pilot and agent platform, model development, go-to-market growth, adoption, partnerships, ecosystems, and secure responsible AI. Before that was the CEO of Salesforce Service Cloud She is also the co-founder and previous CEO of Hearsay Systems. She is also on the Board of Directors at Starbucks.  Show Links:  Clara’s Linkedin Ask more of AI podcast Salesforce AI Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @clarashih Show Notes:  (0:00) Clara’s Background (0:50) From cloud services to AI (3:25) Internal Model Development vs Open Source (5:20) The Co-Pilot Approach (8:50) Enterprise AI Adoption (10:54) The future of Enterprise AI (13:23) Cross-team collaboration (14:40) AI is the new UI (19:11) Structuring the Dataset (21:25) What’s next for generative AI in Enterprise (23:18) Pricing challenges in AI (26:30) Startups and AI (28:22) Collaboration in AI Industry

OpenAI’s leadership has taken us all on a rollercoaster so it’s great timing for another host-only episode. This week Sarah and Elad get into what has been going on at OpenAI and what the turbulent leadership changes tell us about the importance of good intent and good incentives when building these influential companies. They also talk about innovative products coming out of Pika Labs, why people are moving away from diffusion models to LLMs, and how, in AI investing, the ASP is the opportunity.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes:  (0:00) Recapping the OpenAI saga (9:56) AI video products (16:14) Moving from Diffusion Models to LLMs (19:47) The beneficial margins of AI investing

The future of tech is 25-person companies powered by AI agents that help us accomplish our larger goals. Imbue is working on building AI agents that reason, code and generally make our lives easier. Sarah Guo and Elad Gil sit down with co-founders Kanjun Qiu (CEO) and Josh Albrecht (CTO) to discuss how they define reasoning, the spectrum of specialized and generalized agents, and the path to improved agent performance. Plus, what’s behind their $200M Series B fundraise.  Kanjun Qiu is the CEO and co-founder of Imbue. Kanjun is also a partner at angel fund Outset Capital, where she invests in promising pre-seed companies. Previously, Kanjun was the co-founder and CEO of Sourceress, a machine learning recruiting startup backed by YC and DFJ. She was previously Chief of Staff to Drew Houston at Dropbox, where she helped scale the company from 300 employees to 1200. Josh Albrecht is the CTO and co-founder of Imbue. He also invests in other founders via his fund, Outset Capital. He has published machine learning papers as an academic researcher; founded an AI recruiting company that went through YC and a 3D injection molding software company that was acquired; helped build Addepar as an early engineer; and served as a Thiel Fellow mentor. He started programming as a kid and began working professionally as a software engineer in high school.  Show Links:  Kanjun’s LinkedIn | Website | Google Scholar Josh’s LinkedIn | Website | Google Scholar Imbue raises $200M to build AI systems that can reason and code Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Kanjun | @JoshAlbrecht Show Notes:  (00:00) - Introduction to Imbue (04:55) - The Spectrum of Agent Tasks (08:43) - Specialization and Generalization With Agents (13:03) - Code and Language in AI Agents

Open Source fuels the engine of innovation, according to Arthur Mensch, CEO and co-founder of Mistral AI. Mistral is a French AI company which recently made a splash with releasing Mistral 7B, the most powerful language model for its size to date, and outperforming much larger models. Sarah Guo and Elad Gil sit down with Arthur to discuss why open source could win the AI wars, their $100M+ seed financing, the true nature of scaling laws, why he started his company in France, and what Mistral is building next. Arthur Mensch is Chief Executive Officer and co-founder of Mistral AI. A graduate of École Polytechnique, Télécom Paris and holder of the Master Mathématiques Vision Apprentissage at Paris Saclay, he completed his thesis in machine learning for functional brain imaging at Inria (Parietal team). He spent two years as a post-doctoral fellow in the Applied Mathematics department at ENS Ulm, where he carried out work in mathematics for optimization and machine learning. In 2020, he joined DeepMind as a researcher, working on large language models, before leaving in 2023 to co-found Mistral AI with Guillaume Lample and Timothee Lacroix. Show Links:  Arthur’s Linkedin Mistral Mistral 7b Retro: Improving language models by retrieving from trillions of tokens Chinchilla: Training Compute-Optimal Large Language Models Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ArthurMensch Show Notes:  (0:00) - Why he co-founded Mistral (4:22) - Chinchilla and Proportionality  (6:16) - Mistral 7b (9:17) - Data and Annotations (10:33) - Open Source Ecosystem  (17:36) - Proposed Compute and Scale Limits (19:58) - Threat of Bioweapons  (23:08) - Guardrails and Safety  (29:46) - Mistral Platform (31:31) - French and European AI Startups

Each iteration of ChatGPT has demonstrated remarkable step function capabilities. But what’s next? Ilya Sutskever, Co-Founder & Chief Scientist at OpenAI, joins Sarah Guo and Elad Gil to discuss the origins of OpenAI as a capped profit company, early emergent behaviors of GPT models, the token scarcity issue, next frontiers of AI research, his argument for working on AI safety now, and the premise of Superalignment. Plus, how do we define digital life? Ilya Sutskever is Co-founder and Chief Scientist of OpenAI. He leads research at OpenAI and is one of the architects behind the GPT models. He co-leads OpenAI's new "Superalignment" project, which tries to solve the alignment of superintelligences in 4 years. Prior to OpenAI, Ilya was co-inventor of AlexNet and Sequence to Sequence Learning. He earned his Ph.D in Computer Science from the University of Toronto. Show Links: Ilya Sutskever | LinkedIn Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ilyasut Show Notes: (00:00) - Early Days of AI Research (06:51) - Origins of Open Ai & CapProfit Structure (13:46) - Emergent Behaviors of GPT Models (17:55) - Model Scale Over Time & Reliability (22:23) - Roles & Boundaries of Open-Source in the AI Ecosystem (28:22) - Comparing AI Systems to Biological & Human Intelligence (30:52) - Definition of Digital Life (32:59) - Super Alignment & Creating Pro Human AI (39:01) - Accelerating & Decelerating Forces 

Cyber Security is going to change significantly in the era of AI, according to Ryan Noon, cofounder of Material Security, a security company that makes cloud-based Google and Microsoft email a safe place for sensitive data. Elad Gil and Ryan talk about how Material Security started to use LLMs, potential security threats from AI hacks, and the role of the government in securing the Internet. Ryan also shares his advice for founders. Ryan co-founded Material Security in 2017 after seeing high profile email hacks in the 2016 Presidential election. Previously, he led various engineering teams at Dropbox after it acquired his first company, Parastructure. Prior to Parastructure, he led engineering at a data analysis company spun out of Stanford by DARPA. He holds both an MS in Computer Networks and Security and a BS in Computer Science from Stanford. Show Links:  Ryan Noon LinkedIn Material Security Website  The Market for Silver Bullets by Ian Grigg Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @InternetMeme Show Notes:  (00:00) - How 2016 Election Hacking Inspired Ryan to Start Material Security (05:00) - Generative AI Use Cases in Cyber Security & Fine Tuning (11:36) - Predictions on Effective Threat Levels from AI Hacks (14:45) - Democracy, the Department of Defence, DARPA and Cyber Security (20:14) - Is there room for startups in the Cyber Security industry? (26:40) - New Challenges On Horizon After 7 Years as Cofounder (32:30) - Advice to Founders

As the Lead for Generative AI in the Office of the CTO for Google Cloud, Kawal Gandhi has a unique vantage point on enterprise AI rollout. Sarah Guo and Elad Gil sit down with Gandhi this week to discuss his insights on how enterprises can effectively invest in AI development, the importance of TPUs, and Google’s internal AI applications. Plus, when will email get more intelligent?  Kawal Gandhi has worked at Google for nearly a decade in search and ad roles before focusing on the development and marketing of AI tools. Show Links:  Kawal Gandhi | LinkedIn Google Cloud    Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @geeztweets Show Notes:  (00:00) - Generative AI in Google Cloud (09:05) - AI Adoption in the Enterprise (13:31) - Multi-Modal AI Models (16:19) - AI Adoption, return-on-investment, anti-patterns (24:43) - Google's TPU and NVIDIA GPU shortage (31:00) - Data Marketplace and Model Training

Startups aren't the only companies racing to build the new world of AI. This week, Sarah Guo talks with Brian Halligan, the co-founder, longtime CEO and now executive chairperson of HubSpot, the fastest growing CRM. He talks about category creation, coining the term ‘inbound marketing,’ lessons in scaling from an app to a suite to a platform, staying innovative at scale, and how they're navigating the AI disruption. Brian also describes the life-threatening moment he decided to step back from the CEO role. Plus, what he’s up to at Propeller Ventures and why he’s banking on the ocean to save us from climate change. Brian coined the term "inbound marketing" and together with Dharmesh Shah built a movement around the concept, which included organizing the industry-leading INBOUND event and co-authoring the book Inbound Marketing. Now, as the founder of Propeller Ventures, Brian directs a $100 million climate tech venture fund, specializing in ocean investments. He also serves on the boards of Navier and Aquatic Labs. Brian developed MIT’s popular Scaling Entrepreneurial Ventures class, which he’s taught for over a decade. Show Links:  Brian Halligan | LinkedIn  Propeller VC WHOI Partnership HubSpot Culture Code Read his books: Inbound Marketing and Marketing Lessons From the Grateful Dead Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil |@BHalligan Show Notes:  (0:00:00) - HubSpot's Journey from Unlikely Startup to Industry Incumbent (0:05:32) - The End of Cold Calling (and the Birth of Inbound) (0:16:40) - Building a Multi-Product Company (0:22:07) - How to Stay Innovative and Hungry after Going Public (0:29:12) - AI Workflows in CRM and the Incumbent Data Advantage (0:36:09) - Creating a Culture Code for HubSpot (0:40:24) - Propeller Venture Fund, Ours Oceans and Climate Investing

What Does it Take to Improve by 10x or 100x? This week is another host-only episode. Sarah and Elad talk about the path to better model quality, the potential for fine tuning to different use cases, retrieval systems (RAG), feedback systems (RLHF, RLAIF) and Meta’s sponsorship of the open source model ecosystem. Plus Sarah and Elad ask if we’re finally at the beginning of a new set of consumer applications and social networks. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Notes: 0:03:00 - AI Models and Open AI Advances  0:08:59 - Addressing Hallucinations in AI Models  0:13:22 - Open Source Models in Consumer Engagement 0:16:23 - New Trends in Social Content Creation 0:21:53 - Balancing Ambition With Realistic Customer Expectations

Ginkgo Bioworks is using DNA as code to digitize the cell programming revolution. Ginkgo is using AI and synthetic biology to keep the next pandemic at bay, and accelerate our production capabilities for medicine, food, and agriculture. Ginkgo’s co-founder and CEO Jason Kelly joins hosts Sarah Guo and Elad Gil to discuss bioengineering protein as a foundational model, specialized data learning from an evolutionary perspective, what we need to prepare for a future pandemic, and more. Jason has served as a member of our board of directors since Ginkgo’s founding in 2008. He has also served as a director of CM Life Sciences II Inc. (Nasdaq: CMII), a special purpose acquisition company with a focus on the life sciences sector, since its initial public offering in February 2021. Jason holds a Ph.D. in Biological Engineering and a B.S. in Chemical Engineering and Biology from the Massachusetts Institute of Technology. Show Links:  Jason Kelly - Co-founder & CEO of Ginkgo Bioworks | LinkedIn   Ginkgo Bioworks The Plausibility of Life: Resolving Darwin's Dilemma Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jrkelly Show Notes:  (0:00:00) - The Difference Between Software Engineering and Biological Engineering (0:06:51) - Abstractions and Infrastructure in Synthetic Bio (0:09:23) - The Role of AI, Foundation Models that Speak Biology (0:13:17) - AWS for Cell Engineering (0:17:52) - Where are the AI-discovered Drugs? And Data at Gingko (0:19:12) - Pandemic Response and Biosecurity in the Age of AI (0:22:47) - The Likelihood of Existential AI Risk from Lone Actors Harnessing Viruses, and The Need for Defense-in-Depth (0:31:47) - Will Progress in AI Be Biologically Inspired? And Evolution

Replit’s develop-to-deploy platform and new AI tool, Ghostwriter, are breaking down the barriers to entry for beginner programmers. Replit’s CEO, co-founder, and head engineer Amjad Masad joins hosts Sarah Guo and Elad Gil to discuss how AI can change software engineering, the infrastructure we still need, open source foundation models, and what to expect from AI agents. Before co-founding Replit, Amjad Masad worked at Facebook as a software engineer, where he worked on infrastructure tooling. He was a founding engineer at CodeAcademy. Throughout his career, Masad has been an advocate for open-source software. Show Links:  Amjad Masad - CEO & Co-founder of Replit | LinkedIn   Replit Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @amasad Show Links:  Amjad Masad - CEO & Co-founder of Replit | LinkedIn   Replit Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @amasad Show Notes:  0:03:55 - Impact of AI on Code Generation  0:11:09 - Breaking Down Barriers to Entry in Development with Replit 0:14:35 - The Impact of Open Source Models, Meta/Llama 0:20:32 - Bounties, Agents who Make Money 0:24:26 - The Missing Data Spec-to-Code 0:32:29 - Building the Future of AI, Money as a Programmable Primitive

More than 25 million users are using NEAR-powered applications. Co-founder of NEAR protocol and Transformers author Illia Polosukhin joins hosts Sarah Guo and Elad Gil to discuss the intersections of crypto and AI technology, what we should expect from AI agents, decentralized data labeling, why AI’s alignment problem is really a human problem, and more.  Show Links:  Illia Polosukhin - Co-founder of NEAR | LinkedIn   NEAR Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ilblackdragon Show Notes:  (0:00:00) - Blockchain, AI, and Web3 Intersection (0:06:39) - How We Might Combine Blockchain and AI for Cancer Research (0:23:35) - Inference and Decentralized Data Labeling (0:30:13) - AI SaaS Strategic Challenges (0:38:18) - The Future of Hardware Accelerators

The GPU supply crunch is causing desperation amongst AI teams large and small. Cerebras Systems has an answer, and it’s a chip the size of a dinner plate. Andrew Feldman, CEO and Co-founder of Cerebras and previously SeaMicro, joins Sarah Guo and Elad Gil this week on No Priors. They discuss why there might be an alternative to Nvidia, localized models and predictions for the accelerator market. Show Links:  Andrew Feldman - Cerebras CEO & Co-founder | LinkedIn   Cerebras Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @andrewdfeldman Show Notes:  (0:00:00) - Cerebra Systems CEO Discusses AI Supercomputers (0:07:03) - AI Advancement in Architecture and Training (0:16:58) - Future of AI Accelerators and Chip Specialization (0:26:38) - Scaling Open Source Models and Fine-Tuning

Everything digital is increasingly intermediated through web user experiences, and now AI development can be frontend-first, too. Just ask Guillermo Rauch, the founder and CEO of Vercel, the company behind Next.js. In this episode of No Priors, hosts Sarah Guo and Elad Gil speak to Guillermo about their AI SDK and AI templates, and why Vercel is focused on making it easy for every frontend engineer to build with AI. They also discuss what applications Guillermo's most excited about, how to prepare for the world of bots, whether the winds are changing in web architectures, and why he believes in the AI-fueled 100X engineer. Prior to Vercel, Guillermo co-founded several startups and created the JavaScript library, Socket.io, which allows for real-time bi-directional communication between web clients and servers. Show Links: Guillermo Rauch - CEO & Founder of Vercel | LinkedIn  Vercel Vercel AI Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @rauchg Show Notes:  (0:00:00) - Vercel's AI Strategy and Future Plans (0:10:36) - AI Frameworks, Observability, and Bot Mitigation (0:17:24) - Crawling the Web and Architecture Changes (0:27:54) - AI's Impact on Web Personalization

"Biological Software" is the future of medicine. Jakob Uszkoreit, CEO and Co-founder of Inceptive, joins Sarah Guo and Elad Gil this week on No Priors, to discuss how deep learning is expanding the horizons of RNA and mRNA therapeutics. Jakob co-authored the revolutionary paper Attention is All You Need while at Google, and led early Google Translate and Google Assistant teams. Now at Inceptive, he's applying these same architectures and ideas to biological design, optimizing vaccine production, and magnitude-more efficient drug discovery. We also discuss Jakob's perspective on promising research directions, and his point of view that model architectures will actually get simpler from here, and be driven by hardware. Show Links:  Inceptive - CEO & Founder - Jakob Uszkoreit | LinkedIn   Inceptive Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @kyosu Show Notes:  (0:00:00) - Creating Biological Software (0:06:54) - The Hardware Drivers of Large-Scale Transformers (0:14:32) - Challenges in Optimizing Compute Allocation (0:23:25) - Deep Learning in Biology and RNA (0:32:49) - The Future of Drug Discovery (0:41:41) - Collaboration and Innovation at Inceptive

The future of education is right at your children’s fingertips. Sal Khan, CEO and Founder of Khan Academy, joins Sarah Guo and Elad Gil this week on No Priors. For over a decade, Sal Khan has been trying to reform education, beginning with tutoring his cousins in math.  He's the father of the YouTube "chalk talk" format, and has now served tens of millions of students through Khan Academy.  He guides us through how Khan Academy is using AI to personalize a student's educational experience, transporting students into immersive learning experiences that allow them to debate historical figures, to assisting teachers with lesson plans that address the learning gaps keeping students from reaching their full potential, to a Khanmigo, a tutor for every child.  Prior to founding Khan Academy, Sal worked as a hedge fund analyst. He holds an MS in business from Harvard University, as well as an MS in Engineering and a BS in Computer Science from MIT. Show Links:  Khan Academy - CEO & Founder - Khan Academy | LinkedIn   Khan Academy Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @salkhanacademy Show Notes:  [0:00:06] - Sal Khan's Journey [0:08:41] - Mastery Learning and AI in Education [0:19:53] - Future of AI Tutors in Education [0:23:10] - Education's Future With Generative AI [0:29:35] - Connecting Learning Through Tutoring and Collaboration [0:33:22] - Implications of GPT 4 on Education [0:40:42] - Future of Education and Job Skills [0:46:47] - Importance of Traditional Skills in Education

This week on the podcast, Sarah Guo and Elad Gil answer listener questions on the state of technology and artificial intelligence. Sarah and Elad also talk about the 2024 tech market, what type of companies may reach their highest valuation ever and the (former) unicorns that may go bust. Plus, how do Sarah and Elad define happiness? Hint: it’s a use case for a specialized AI agent.  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Show Links: Cerebras Systems signs $100 million AI supercomputer deal with UAE's G42 | Reuters  Our World in Data  Show Notes:  [0:00:37] - Impact of GPU Bottleneck in the near and long term [0:10:30] - Timeline for existing incumbent enterprises to use AI in products  [0:11:50] - Vertical versus broad applications for AI Agents   [0:19:33] - 2024 tech market predictions & how founders should think about valuations 

How are ML developer tools helping to advance our capabilities? Lukas Biewald, CEO of Weights & Biases, joins Sarah Guo and Elad Gil this week on No Priors. Lukas explores the impact of ML in various industries like gaming, AgTech, and fintech through his insightful perspective. He discusses the impact of LLMs, puts them in context of the evolution of ML engineering over the past decade and a half, and tells the backstory of Weights & Biases' success. He gives advice for aspiring AI company founders, placing emphasis on customer feedback and using insecurity as a vehicle for better customer discovery. Prior to founding Weights & Biases, Lukas attacked the problem of data collection for model training as the Founder of Figure Eight, which he sold in 2019. He holds an MS in Computer Science and a BS in Mathematics from Stanford University. Show Links:  Lukas Biewald - CEO & Co-founder - Weights & Biases | LinkedIn   Weights & Biases Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @l2k Show Notes:  [0:00:00] - Lucas Wald's Journey in AI [0:08:16] - Startup Evolution and Machine Learning [0:18:54] - Open Source Models Implications and Adoption [0:29:54] - ML Impact in Various Industries [0:40:27] - Advice for AI Company Founders

Can frontiers as high-stakes as next-generation, AI-enabled defense depend on something as mundane as data integration? Can "large language models" work in such mission critical applications? In this episode of No Priors, hosts Sarah Guo and Elad Gil are joined by Shyam Sankar, the Chief Technical Officer of Palantir Technologies and inventor of their famous Forward Deployed Engineering force. Early employee and longtime leader Shyam explains the evolution of technology at Palantir, from ontology and data integration to process visualization and now AI. He describes how a company of Palantir's scale has adopted foundation models and shares customer stories. They discuss the case for open source AI models fine-tuned on private, domain-specific data, and the challenges of anchoring AI models in reality. Show Links: Shyam Sankar - Chief Technical Officer - Palantir Technologies | LinkedIn   Palantir Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ssankar Show Notes:  [0:00:00] - Palantir's CTO Discusses Company's Background [0:10:17] - Apollo and AIP [0:20:25] - Future of UI and Application Integration [0:28:29] - Investment in Co-Pilot Models and Education [0:31:22] - Exploring AI Implementation in Various Industries [0:38:19] - Operational and Analytical Workflows in Context

Video dominates modern media consumption, but video creation is still expensive and difficult. AI-generated and edited video is a holy grail of democratized creative expression. This week on No Priors, Sarah Guo and Elad Gil sit down with Devi Parikh. She is a Research Director in Generative AI at Meta and an Associate Professor in the School of Interactive Computing at Georgia Tech. Her work focuses on multimodality and AI for images, audio and video. Recently, she worked on Make a Video 3D, also called MAV3D, which creates animations from text prompts. She is also a talented AI-generated and analog artist herself. Elad, Sarah and Devi talk about what’s exciting in computer vision, what’s blocking researchers from fully immersive Generative 4-D, and AI controllability. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Devi Parikh - Google Scholar  Text-To-4D Dynamic Scene Generation named MAV3D (Make-A-Video3D) Full Research Paper Website with examples of image to 4 D generation Devi’s Substack Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @DeviParikh Show Notes: (0:00:06) - Democratizing Creative Expression With AI-Generated Video (0:08:31) - Challenges in Video Generation Research (0:15:57) - Challenges and Implications of Video Processing (0:20:43) - Control and Multi-Modal Inputs in Video (0:25:50) - Audio's Role in Visual Content (0:39:00) - Don't Self-Select & Devi’s tips for young researchers

Frank Slootman, CEO of Snowflake Computing, joins Sarah Guo and Elad Gil this week on No Priors. Before scaling Snowflake to its blockbuster IPO and beyond, Frank was also the CEO from early to scale for landmark enterprise companies ServiceNow and Data Domain. Frank grew up in the Netherlands and is also the author of three books: Amp It Up, Rise of the Data Cloud, and Tape Sucks. In this episode, our hosts talk with Frank about the opportunity for generative AI in the enterprise, why Snowflake isn't really a data warehousing company, their acquisitions of Neeva and Streamlit, apps within Snowflake, and how AI relates to traditional analytics and BI. He also talks about his personal journey, why it's always a good time to do performance management, and why most leaders struggle to raise the bar for performance. ** No Priors is taking a summer break! The podcast will be back with new episodes in three weeks. Join us on July 20th for a conversation with Devi Parikh, Research Director in Generative AI at Meta. ** No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Forbes: How CEO-For-Hire Frank Slootman Turned Snowflake Into Software’s Biggest-Ever IPO Amp It Up: Leading for Hypergrowth by Raising Expectations, Increasing Urgency, and Elevating Intensity Rise of the Data Cloud (Audible Audio Edition): Frank Slootman, Steve Hamm, Zach Hoffman, Snowflake: Books TAPE SUCKS: Inside Data Domain, A Silicon Valley Growth Story eBook : Slootman, Frank: Kindle Store Frank Slootman’s LinkedIn Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @SnowflakeDB Show Notes: [00:06] - Frank’s Insights on Career Success as a three-time CEO [12:42] - The message of his book Amp It Up [25:01] - Future of Natural Language and Data [36:29] - Data Management and Industry Transformation Future [45:13] - Managing Resources in Changing Economic Environment [50:09] - Amping Up Energy and Intensity Amid Economic Headwinds

Fidji Simo, the CEO of Instacart and co-founder of Metrodora Institute, a medical center and research institute for neuroimmune axis disorders, shares her personal journey from growing up in France, to leading the Facebook app, to becoming a wartime CEO. Fidji talks about the future of Instacart, their AI strategy, how the current era of AI is different from prior ML waves, and the impact of LLMs in commerce, robotics and healthcare. She also shares how she earns followership from her teams. ** No Priors is taking a summer break! The podcast will be back with new episodes in three weeks. Join us on July 20th for a conversation with Devi Parikh, Research Director in Generative AI at Meta. ** No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: May 31, 2023: Instacart users can now plan meals using AI - Fast Company Profile May 13, 2023: Instacart CEO Fidji Simo makes groceries personal. Now she’s doing the same for women’s health December 2, 2021: Rapid Response: Re-founding Instacart, w/ first-time CEO Fidji Simo | Podcast: Masters of Scale with Reid Hoffman Metrodora Institute Fidji Simo’s LinkedIn Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Fidjissimo Show Notes: [00:01] - Leading With Impact and Authenticity [11:48] - Implementing AI [17:28] - Future of Grocery Shopping With AI [25:38] - AI in Advertising and Commerce [32:54] - Metrodora: AI in Biotech and Healthcare [34:18] - The positive impact of AI, mitigating harm & role of regulations

Olivier Pomel, co-founder and CEO of Datadog, the leading observability company, discusses the company’s founding story, early product sequencing, platform strategy, and acquisitions. Olivier also shares his thoughts on their more recent expansion into security, and why he’s bullish on the potential for AI in DevOps. ** No Priors is taking a summer break! The podcast will be back with new episodes in three weeks. Join us on July 20th for a conversation with Devi Parikh, Research Director in Generative AI at Meta. ** No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Nov 22, 2022: Product-led Growth: Founder 1-on-1 with Datadog and Aiven - Olivier Pomel & Oskari Saarenmaa May 25, 2022: Datadog, Inc. (DDOG) CEO Olivier Pomel Presents at J.P. Morgan's 50th Annual Global Technology, Media and Communications Conference Jan 6, 2021: Datadog CEO Olivier Pomel on the cloud computing outlook Datadog’s Official Website Olivier Pomel LinkedIn Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Oliveur Show Notes: [00:10] - DevOps and AI Potential [06:54] - Datadog and Generative AI [20:40] - Datadog's Acquisition and Expansion Strategy [31:46] - LLMs in Automation and Precision [42:35] - Datadog's Customer Value and Growth

This week on No Priors, Sarah and Elad do another hangout to answer listener questions. Topics include debunking common misconceptions about AI and its implications on the world, the analogy to nuclear power and nuclear safety, the impact of larger context windows, developer productivity, incumbent announcements of AI products, and some requests for (fat) startups. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @SchimpfBrian Show Notes: [00:21] - What Are People Getting Wrong About AI Right Now? / New Capabilities of NLP [04:35] - Nuclear Power and Safety Concerns [11:12] - Emerging AI Companies and Research [15:54] - China's Hardware Sanctions and Funding Ramp [20:34] - Innovation in Heterogeneous Compute Infrastructure [28:08] - Enterprise Stack and Decision Making [33:44] - Data's Impact on the World

Today on No Priors, we discuss defense technology, AI, drones, and autonomous vehicles (think giant submarine drones!) with Brian Schimpf, the co-founder and CEO of Anduril, a next-generation defense technology company. From his early days of coding at age 12 to working on self-driving cars, and finally founding Anduril, Brian's incredible journey led him to create innovative solutions for pressing defense problems. This episode covers the impact of AI, intelligent software, and other technologies to defense. We discuss the challenges of deploying and selling technology in the government spaceBrian shared his perspective on building general-purpose defense technology, the importance of a software-first approach, and how Anduril is working to solve urgent defense problems with speed and efficiency. As we wrapped up our conversation, we touched on the recent shift in the low cost of space launch, which has changed the way the US thinks about defense. We examined the proliferation of satellites, drones, and hypersonic missiles, and how these technologies can be applied, scaled, and built in a way that can fundamentally shift America's approach to defense. Don't miss this fascinating episode with Brian Schimpf as we uncover the cutting edge of defense technology and its implications for the future. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: May 16, 2023: AI in Military Operations and How We Can Prevent It From Outsized Effects May 9, 2023: CNBC Disruptor 50 - Anduril Industries Anduril Website Anduril Newsroom Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @SchimpfBrian Show Notes: [0:00:01] - Exploring AI in Defense Tech [0:05:15] - Lower Cost Defense With Intelligent Software [0:15:10] - Building General Purpose Defense Technology [0:20:41] - Autonomy in Defense Challenges [0:25:05] - Machine Learning in Defense & Intelligence [0:29:06] - Scaling a Defense Tech Company [0:37:08] - The Future of Defense Technology [0:46:53] - Allied Forces and Washington Engagement [0:51:47] - Discussion on Leadership Popularity

In this episode, Sarah and Elad speak with Microsoft CTO Kevin Scott about his unlikely journey from rural Virginia to becoming the driving force behind Microsoft's AI strategy.  Sarah and Elad discuss the partnership that Kevin helped forge between Microsoft and OpenAI and explore the vision both companies have for the future of AI. They also discuss yesterday’s announcement of “copilots” across the Microsoft product suite, Microsoft’s GPU computing budget, the potential impact of open source AI models in the tech industry, the future of AI in relation to jobs, why Kevin is bullish on creative and physical work, and predictions for progress in AI this year. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: May 23, 2023: The Verge - Microsoft CTO Kevin Scott Thinks Sydney Might Make a Comeback May 23, 2023: Microsoft Outlines Framework For Building AI Apps and Copilots January 10, 2023: A Conversation with Kevin Scott: What’s Next In AI Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @kevin_scott Show Notes: [00:00] - Kevin Scott's Journey to Microsoft CTO [12:44] - Microsoft and Open AI Partnership [21:18] - The Future of Open Source AI [32:12] - AI for Everyone [45:29] - AI and the Future of Jobs [51:44] - The Future of AI and Regulation [58:10] - Taking a Global Perspective

What if AI could revolutionize healthcare with advanced language learning models? Sarah and Elad welcome Karan Singhal, Staff Software Engineer at Google Research, who specializes in medical AI and the development of MedPaLM2. On this episode, Karan emphasizes the importance of safety in medical AI applications and how language models like MedPaLM2 have the potential to augment scientific workflows and transform the standard of care. Other topics include the best workflows for AI integration, the potential impact of AI on drug discoveries, how AI can serve as a physician's assistant, and how privacy-preserving machine learning and federated learning can protect patient data, while pushing the boundaries of medical innovation. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: May 10, 2023: PaLM 2 Announcement April 13, 2023: A Responsible Path to Generative AI in Healthcare March 31, 2023: Scientific American article on Med-PaLM February 28, 2023: The Economist article on Med-PaLM KaranSinghal.com Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @thekaransinghal Show Notes: [00:22] - Google's Medical AI Development [08:57] - Medical Language Model and MedPaLM 2 Improvements [18:18] - Safety, cost/benefit decisions, drug discovery, health information, AI applications, and AI as a physician's assistant. [24:51] - Privacy Concerns - HIPAA's implications, privacy-preserving machine learning, and advances in GPT-4 and MedPOM2. [37:43] - Large Language Models in Healthcare and short/long term use.

Mustafa Suleyman, co-founder of DeepMind and now co-founder and CEO of Inflection AI, joins Sarah and Elad to discuss how his interests in counseling, conflict resolution, and intelligence led him to start an AI lab that pioneered deep reinforcement learning, lead applied AI and policy efforts at Google, and more recently found Inflection and launch Pi. Mustafa offers insights on the changing structure of the web, the pressure Google faces in the age of AI personalization, predictions for model architectures, how to measure emotional intelligence in AIs, and the thinking behind Pi: the AI companion that knows you, is aligned to your interests, and provides companionship. Sarah and Elad also discuss Mustafa’s upcoming book, The Coming Wave (release September 12, 2023), which examines the political ramifications of AI and digital biology revolutions. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Forbes - Startup From Reid Hoffman and Mustafa Suleyman Debuts ChatBot Inflection.ai Mustafa-Suleyman.ai Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mustafasuleymn Show Notes: [00:06] - From Conflict Resolution to AI Pioneering [10:36] - Defining Intelligence [15:32] - DeepMind's Journey and Breakthroughs [24:45] - The Future of Personal AI Companionship [33:22] - AI and the Future of Personalized Content [41:49] - The Launch of Pi [51:12] - Mustafa’s New Book The Coming Wave

How do you personalize AI models? A popular school of thought in AI is to just dump all the data you need into pre-training or fine tuning. But that may be less efficient and less controllable than alternatives — using AI models as a reasoning engine against external data sources. Kelvin Guu, Senior Staff Research Scientist at Google, joins Sarah and Elad this week to talk about retrieval, memory, training data attribution and model orchestration. At Google, he led some of the first efforts to leverage pre-trained LMs and neural retrievers, with >30 launches across multiple products. He has done some of the earliest work on retrieval-augmented language models (REALM) and training LLMs to follow instructions (FLAN). No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Kelvin Guu Website Google Scholar FLAN: Finetuned Language Models Are Zero-Shot Learners Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs ROME: Locating and Editing Factual Associations in GPT Branch-Train-Merge: Scaling Expert Language Models with Unsupervised Domain Discovery Large Language Models Struggle to Learn Long-Tail Knowledge  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Kelvin_Guu Show Notes: [1:44] - Kelvin’s background in math, statistics and natural language processing at Stanford [3:24] - The questions driving the REALM Paper [7:08] - Frameworks around retrieval augmentation & expert models [10:16] - Why is modularity important [11:36] - FLAN Paper and instruction following [13:28] - Updating model weights in real time and other continuous learning methods [15:08] - Simfluence Paper & explainability with large language models [18:11] - ROME paper, “Model Surgery” exciting research areas [19:51] - Personal opinions and thoughts on AI agents & research [24:59] - How the human brain compares to AGI regarding memory and emotions [28:08] - How models become more contextually available [30:45] - Accessibility of models [33:47] - Advice to future researchers

This week on No Priors, Sarah and Elad answer listener questions about tech and AI. Topics covered include the evolution of open-source models, Elon AI, regulating AI, areas of opportunity, and AI hype in the investing environment. Sarah and Elad also delve into the impact of AI on drug development and healthcare, and the balance between regulation and innovation. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes:  [0:00:06] - The March of Progress for Open Source Foundation Models  [0:06:00] - Should AI Be Regulated? [0:13:49] - Investing in AI and Exploring the AI Opportunity Landscape [0:23:28] - The Impact of Regulation on Innovation [0:31:55] - AI in Healthcare and Biotech

So much of the AI conversation today revolves around models and new applications. But this AI revolution would not be possible without one thing – GPUs, Nvidia GPUs. The Nvidia A100 is the workhorse of today’s AI ecosystem. This week on No Priors, Sarah Guo and Elad Gil sit down with Jensen Huang, the founder and CEO of NVIDIA, at their Santa Clara headquarters. Jensen co-founded the company in 1993 with a goal to create chips that accelerated graphics. Over the past thirty years, NVIDIA has gone far behind gaming and become a $674B behemoth. Jensen talks about the meaning of this broader platform shift for developers, making very long term bets in areas such as climate and biopharma, their next-gen Hopper chip, why and how NVIDIA chooses problems that are unsolvable today, and the source of his iconic leather jackets. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Jensen Huang | NVIDIA Nvidia's A100 is the $10,000 chip powering the race for A.I. | CNBC Nvidia CEO Jensen Huang: A.I. is at ‘inflection point’ | Fortune Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Nvidia Show Notes:  [1:26] - The early days when Jensen Co-founded NVIDIA [4:58] - Why NVIDIA started to expand its aperture to artificial intelligence use cases  [10:42] - The moment in 2012 Jensen realized AI was going to be huge [13:52] - How we’re in a broader platform shift in computer science [17:48] - His vision for NVIDIA’s future lines of business [18:09] - How NVIDIA has two motions: Shipping reliable chips and solving new use cases  [25:41] - Why no one should assume they’re right for the job of CEO and why not every company needs to be architected as the US military  [31:39] - What’s next for NVIDIA’s Hopper  [32:57] - Durability of Transformers  [35:08] - What Jensen is excited about in the future of AI & his advice for founders

Noam Shazeer played a key role in developing key foundations of modern AI - including co-inventing Transformers at Google, as well as pioneering AI chat pre-chatGPT. These are the foundations supporting today’s AI revolution. On this episode of No Priors, Noam discusses his work as an AI researcher, engineer, inventor, and now CEO.  Noam Shazeer is currently the CEO and Co-founder of Character AI, a service that allows users to design and interact with their own personal bots that take on the personalities of well-known individuals or archetypes. You could have a socratic conversation with Socrates. You could pretend you’re being interviewed by Oprah. Or you could work through a life decision with a therapist bot. Character recently raised $150M from A16Z, Elad Gil, and others. Noam talks about his early AI adventures at Google, why he started Character, and what he sees on the horizon of AI development. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Noam Shazeer - Google Scholar Noam Shazeer - Chief Executive Officer - Character.AI | LinkedIn  Character.AI Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Character_ai Show Notes:  [1:50] - Noam’s early AI projects at Google [7:13] - Noam’s focus on language models and AI applications [11:13] - Character’s co-founder Daniel de Freitas Adiwardana work on Google’s Lambda [13:53] - The origin story of Character.AI  [18:47] - How AI can express emotions [26:51] - What Noam looks for in new hires

If you have 30 dollars, a few hours, and one server, then you are ready to create a ChatGPT-like model that can do what’s known as instruction-following. Databricks’ latest launch, Dolly, foreshadows a potential move in the industry toward smaller and more accessible but extremely capable AIs. Plus, Dolly is open source, requires less computing power, and fewer data parameters than its counterparts. Matei Zaharia, Cofounder & Chief Technologist at Databricks, joins Sarah and Elad to talk about how big data sets actually need to be, why manual annotation is becoming less necessary to train some models, and how he went from a Berkeley PhD student with a little project called Spark to the founder of a company that is now critical data infrastructure that’s increasingly moving into AI. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Hello Dolly: Democratizing the magic of ChatGPT with open models Dolly Source Code on Github Matei Zaharia - Chief Technologist & Cofounder - Databricks | LinkedIn Matei Zaharia - Google Scholar Databricks debuts ChatGPT-like Dolly, a clone any enterprise can own | VentureBeat Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Databricks | @Matei_Zaharia Show Notes:  [01:29] - Origin of Databricks [4:30] - Work at Stanford Lab [5:29] - Dolly and Role of Open Source [12:30] - Industry focus on high parameter count, understanding reasoning at small model scale [18:42] - Enterprise applications for Dolly & chat bots [25:06] - Making bets as an academic turned CTO [36:23] - The early stages of AI and future predictions

Everyone talks about the future impact of AI, but there’s already an AI product that has revolutionized a profession. Alex Graveley was the principal engineer and Chief Architect behind Github Copilot, a sort of pair-programmer that auto-completes your code as you type. It has rapidly become a product that developers won’t live without, and the most leaned-upon analogy for every new AI startup – Copilot for Finance, Sales, Marketing, Support, Writing, Decision-Making. Alex is a longtime hacker and tinkerer, open source contributor, repeat founder, and creator of products that millions of people use, such as Dropbox Paper. He has a new project in stealth, Minion AI. In this episode, we talk about the uncertain process of shipping Copilot, how code improves chain of thought for LLMs, how they improved product, performance, how people are using it, AI agents that can do work for us, stress testing society's resilience to waves of new technology, and his new startup named Minion. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Alex Graveley - San Francisco, California, United States | Professional Profile | LinkedIn Minion AI Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alexgraveley | @ai_minion Show Notes: [1:50] - How Alex got started in technology  [2:28] - Alex’s earlier projects with Hack Pad and Dropbox Paper [07:32] - Why Alex always wanted to make bots that did stuff for people [11:56] - How Alex started working at Github and Copilot [27:11] - What is Minion AI [30:30] - What’s possible on the horizon of AI

With advances in machine learning, the way we search for information online will never be the same. This week on the No Priors podcast, we dive into a startup that aims to be the most trustworthy place to search for information online. Perplexity.ai is a search engine that provides answers to questions in a conversational way and hints at what the future of search might look like. Aravind Srinivas is a Co-founder and CEO of Perplexity. He is a former research scientist at Open AI and completed his PhD in computer science at University of California Berkeley. Denis Yarats is a Co-Founder and Perplexity’s CTO. He has a background in machine learning, having worked as a Research Scientist at Facebook AI Research and a machine learning engineer at Quora. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: Aravind Srinivas on Google Scholar Denis Yarats on Google Scholar Perplexity AI Perplexity AI Discord AI Chatbots Are Coming to Search Engines. Can You Trust Them? - Scientific American Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AravSrinivas | @denisyarats Show Notes:  [1:46] - How Perplexity AI iterates quickly and how the company has changed over time [5:46] - Approach to hiring and building a fast-paced team [10:43] - Why you don’t need AI pedigree to transition to work or research AI [14:01] - Challenges when transitioning from AI research to running a company as CEO & CTO [16:50] - Why Perplexity only shows answers it can cite [19:33] - How Perplexity approaches reinforcement learning [20:49] - Trustworthiness and if an answer engine needs a personality [23:05] - Why answer engines will become their own market segment [26:38] - Implications of “the era of fewer clicks” on publishers and advertisers [30:20] - Monetization strategy [33:20] - Advice for those deciding between academia or startups

For the first time in decades web search might be at risk for disruption. Bing is allied with OpenAI to integrate LLMs. Google has committed to launching new products. New startups are emerging. Sridhar Ramaswamy co-founded the challenger AI-powered, private search platform Neeva in 2019. He is a former 16-year Google veteran who most recently led the internet’s most profitable business as SVP in charge of Google Ads, Commerce and Privacy. Sridhar, Elad and Sarah talk about the challenge of building search, how LLMs have changed the landscape, and how chatbots and "answer services" will affect web publishers. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: LinkedIn Neeva Search Neeva Gist Poe by Quora Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @RamaswmySridhar Show Notes:  [1:32] - Why Sridhar started a private search engine after leaving Google [11:11] - Information Retrieval Problems, Mapping Search Queries and LLMs [15:25] - Google and Bing’s approach to search with LLMs [19:06] - Scale challenges when building a search engine startup [22:26] - Distribution challenges and why they release Neeva Gist [24:11] - Why Neeva is a privacy centric subscription service  [28:25] - The relationship between search and publishers/content creators [30:16] - Sridhar’s predictions on how AI will disrupt current ecosystems

When AI research is evolving at warp speed and takes significant capital and compute power, what is the role of academia? Dr. Percy Liang – Stanford computer science professor and director of the Stanford Center for Research on Foundation Models talks about training costs, distributed infrastructure, model evaluation, alignment, and societal impact. Sarah Guo and Elad Gil join Percy at his office to discuss the evolution of research in NLP, why AI developers should aim for superhuman levels of performance, the goals of the Center for Research on Foundation Models, and Together, a decentralized cloud for artificial intelligence. No Priors is now on YouTube! Subscribe to the channel on YouTube and like this episode. Show Links: See Percy’s Research on Google Scholar See Percy’s bio on Stanford’s website Percy on Stanford’s Blog: What to Expect in 2023 in AI Together, a decentralized cloud for artificial intelligence Foundation AI models GPT-3 and DALL-E need release standards - Protocol The Time Is Now to Develop Community Norms for the Release of Foundation Models - Stanford Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @PercyLiang Show Notes:  [1:44] - How Percy got into machine learning research and started the Center for Research and Foundation Models at Stanford [7:23] - The role of academia and academia’s competitive advantages [13:30] - Research on natural language processing and computational semantics [27:20] - Smaller scale architectures that are competitive with transformers [35:08] - Helm, holistic evaluation of language models, a project with the the goal is to evaluate language models [42:13] - Together, a decentralized cloud for artificial intelligence

Life-saving therapeutics continue to grow more costly to discover. At the same time, recent advances in using machine learning for the life sciences and medicine are extraordinary. Are we on the verge of a paradigm shift in biotech? This week on the podcast, a pioneer in AI, Daphne Koller, joins Sarah Guo and Elad Gil on the podcast to help us explore that question. Daphne is the CEO and founder of Insitro — a company that applies machine learning to pharma discovery and development, specifically by leveraging “induced pluripotent stem cells.” We explain Insitro’s approach, why they’re focused on generating their own data, why you can’t cure schizophrenia in mice, and how to design a culture that supports both research and engineering. Daphne was previously a computer science professor at Stanford, and co-founder and co-CEO of edutech company Coursera. Show Links:  Insitro - About  Video: AWS re:Invent 2019 – Daphne Koller of insitro Talks About Using AWS to Transform Drug Development  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @DaphneKoller Show Notes:  [1:49] - How Daphne combined her biology and tech interests and ran a bifurcated lab at Stanford [4:34] - Why Daphne resigned an endowed chair at Stanford to build Coursera  [14:14] - How insitro approaches target identification problems and training data  [18:33] - What are pluripotent stem cells and how insitro identifies individual neurons  [24:08 ] - How insitro operates as an engine for drug discovery and partners to create the drugs themselves [26:48] - Role of regulations, clinical trials and disease progression in drug delivery  [33:19] - Building a team and workplace culture that can bridge both bio and computer sciences  [39:50] - What Daphne is paying attention to in the so-called golden age of machine learning   [43:12] - Advice for leading a startup in edtech and healthtech

After starting as a talking emoji companion, Hugging Face is now an organizing force for the open source AI research ecosystem. Its models are used by companies such as Apple, Salesforce and Microsoft, and it's working to become the GitHub for ML. This week on the podcast, Sarah Guo and Elad Gil talk to Clem Delangue, co-founder and CEO of Hugging Face. Clem shares how they shifted away from their original product, why every employee at Hugging Face is responsible for community-building, the modalities he's most interested in, and what role open source has in the AI race. Show Links: Hugging Face website The $2 Billion Emoji: Hugging Face Wants To Be Launchpad For A Machine Learning Revolution - Forbes Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ClementDelangue Show Notes:  [01:53] - how Clem first became interested in ML, being shouted at by eBay sellers, and the foretelling of the end of barcode scanning [3:34] - early iterations of Hugging Face, trying to make a less boring AI tamagotchi, and switching directions towards open source tools [5:36] - advice for founders considering a change in direction, 30%+ experimentation [7:39] - 1st users, MLTwitter, approach to community [10:47] - enterprise ML maturity, days to production [12:54] - open source vs. proprietary models [15:56] - main model tasks, architectures and sizes [19:12] - decentralized infrastructure, data opt out [24:16] - Hugging Face’s business model, GitHub [28:09] - What Clem is excited about in AI

This is a special bonus episode from our Founder Stories series, where entrepreneurs share the story of their startup journey. A delivery with Zipline is the closest thing we have to teleportation. It sounds like science fiction, but Zipline delivers life saving medical supplies such as blood and vaccines to hospitals, doctors and people in need around the world with the world's largest autonomous drone network. This week on the podcast, Sarah Guo talks to Keller Rinaudo Cliffton, the co-founder and CEO of Zipline, about building a full-stack business that involves software, hardware and operations, how a culture of ruthless engineering practicality enabled them to do unlikely things, the state of autopilot in aircraft, their AI acoustic detect-and-avoid system, and why founders should build for users beyond the "golden billion." Show Links: Zipline's website Video: Drone Delivery Start-Up Zipline Beats Amazon, UPS And FedEx To The Punch | CNBC Keller Rinaudo: How we're using drones to deliver blood and save lives | TED Talk Meet Romotive: An Ambitious Startup That Blew Our Minds Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @KellerRinaudo Show Notes:  [2:07] - Keller’s earlier projects and early inspiration for Zipline and transforming logistics  [7:40] - Why Zipline focused on healthcare logistics and Zipline’s early near death experiences as a company  [15:32] - How Zipline iterated on the hardware while being ruthlessly practical with getting products in the customers’ hands  [21:52] - The difference between AI and Autopilot [25:51] - How Zipline developed AI acoustic-based detect and avoid system [31:30] - Zipline’s partnership with Rwanda’s public health system  [34:25] - Challenges in the business model 

AI-generated images have been everywhere over the past year, but one company has fueled an explosive developer ecosystem around large image models: Stability AI. Stability builds open AI tools with a mission to improve humanity. Stability AI is most known for Stable Diffusion, the AI model where a user puts in a natural language prompt and the AI generates images. But they're also engaged in progressing models in natural language, voice, video, and biology. This week on the podcast, Emad Mostaque joins Sarah Guo and Elad Gil to talk about how this barely one-year-old, London-based company has changed the AI landscape, scaling laws, progress in different modalities, frameworks for AI safety and why the future of AI is open. Show Links: Stability.AI Stable Diffusion V2 on Hugging Face  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EMostaque Show Notes:  [2:00] - Emad’s background as one of the largest investors in video games and artificial intelligence [7:24] - Open-source efforts in AI [13:09] - Stability.AI as the only independent multimodal AI company in the world [15:28] - Computational biology, medical information and medical models [23:29] - Pace of Adoption [26:31] - AGI versus intelligence augmentation [31:38] - Stability.AI’s business model [37:44] - AI Safety

For a long time, AI-generated images and video felt like a fun toy. Cool, but not something that would bring value to professional content creators. But now we are at the exciting moment where machine learning tools have the power to unlock more creative ideas. This week on the podcast, Sarah Guo and Elad Gil talk to Cristobal Valenzuela, a technologist, artist and software developer. He’s also the CEO and co-founder of Runway, a web-based tool that allows creatives to use machine learning to generate and edit video. You've probably already seen Runway's work in action on the Late Show with Stephen Colbert and in the feature film Everything Everywhere All at Once. Show Links: Watch Cris Valenzuela’s 2018 thesis presentation at New York University’s ITP program. Read how Runway is used on the Late Show and in Everything Everywhere All at Once on the Runway Blog. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @c_valenzuelab Show Notes:  [1:50] - Cris’s background and how he doesn’t see barriers between art and machine learning [6:46] - How Runway works as a tool [8:36] - The origins and early iterations of Runway [12:22] - Product sequencing and roadmapping in a fast growing space [15:43] - Runway as an applied research company [19:10] - Common pitfalls for founders to avoid [22:35] - How Runway structures teams for effective collaboration [24:22] - Learnings from how Runway built Greenscreen product [28:01] - Building a long-term and sustainable business [32:34] - Finding Product Market Fit [36:34] - The influence of AI tools in art as an artistic movement

AI is transforming our future, but what does that really mean? In ten years, will humans be forced to please our AGI overlords or will we have unlocked unlimited capacity for human potential? That's why Sarah Guo and Elad Gil started this new podcast, named No Priors. In each episode, Sarah and Elad talk with the leading engineers, researchers and founders in AI, across the stack. We'll talk about the technical state of the art, how that impacts business, and get them to predict what's next. Follow the podcast wherever you listen so you never miss an episode. We’ll see you next week with a new episode. Email feedback to [email protected]

AGI can beat top players in chess, poker, and, now, Diplomacy. In November 2022, a bot named Cicero demonstrated mastery in this game, which requires natural language negotiation and cooperation with humans. In short, Cicero can lie, scheme, build trust, pass as human, and ally with humans. So what does that mean for the future of AGI? This week’s guest is research scientist Noam Brown. He co-created Cicero on the Meta Fundamental AI Research Team, and is considered one of the smartest engineers and researchers working in AI today. Co-hosts Sarah Guo and Elad Gil talk to Noam about why all research should be high risk, high reward, the timeline until we have AGI agents negotiating with humans, why scaling isn’t the only path to breakthroughs in AI, and if the Turing Test is still relevant. Show Links: More about Noam Brown Read the research article about Cicero (diplomacy) published in Science.  Read the research article about Liberatus  (heads-up poker) published in Science.  Read the research article about Pluribus (multiplayer poker) published in Science.  Watch the AlphaGo Documentary. Read “How Smart Are the Robots Getting?” by New York Times reporter Cade Metz  Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Polynoamial Show Notes:  [01:43] - What sparked Noam’s interest in researching AI that could defeat games [6:00] - How the AlexaNET and AlphaGo changed the landscape of AI research [8:09] - Why Noam chose Diplomacy as the next game to work on after poker [9:51] - What Diplomacy is and why the game was so challenging for an AI bot [14:50] - Algorithmic breakthroughs and significance of AI bots that win in No-Limit Texas Hold'em poker [23:29] - The Nash Equilibrium and optimal play in poker [24:53] - How Cicero interacted with humans  [27:58] - The relevance and usefulness of the Turing Test [31:05] - The data set used to train Cicero [31:54] - Bottlenecks to AI researchers and challenges with scaling [40:10] - The next frontier in researching games for AI [42:55] - Domains that humans will still dominate and applications for AI bots in the real world [48:13] - Reasoning challenges with AI