No Priors: Artificial Intelligence | Technology | Startups

Can AI transform legacy incumbents rather than replacing them? Sequence Holdings co-founder and CEO Michael Lee joins Sarah Guo to discuss how holding company structures and engineering integrations are reshaping market leaders from the inside out. Michael details Sequence’s $7.7 billion take-private transaction of Baldwin alongside Dell Family Office (DFO), and shares his thesis on why traditional consulting models and software sales fall short for real enterprise AI transformations. They also talk about why permanent holding company structures are good for long-term compounding, real-world results from applying frontier engineering to BankSouth, and Michael’s lessons from his time in public investing, private equity, and operating at the intersection of market incumbents and AI. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @mjlee_2014 | @seqholdings Chapters: 00:34 – Michael Lee Introduction 01:03 – Sequence Holdings and Baldwin 01:54 – Idea for Sequence 04:36 – Incumbents in the AI Era 06:32 – Why a Holding Company 11:21 – Recruiting Top Engineers 13:08 – Investing in BankSouth 17:46 – Why an Insurance Brokerage 20:17 – Atlas Platform Explained 23:53 – Traditional Private Equity Limitations 27:23 – What Sequence Looks For in Management Teams 31:04 – Accomplishments at BankSouth 34:45 – Founder Lessons 36:08 – Story of Dell Partnership 37:10 – Career and Investment Approach 40:00 – Value of Exceptional People 42:23 – Conclusion

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

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

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

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