No Priors: Artificial Intelligence | Technology | Startups

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. 

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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.” 

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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).

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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.

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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.

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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