The AI hardware race is heating up, and NVIDIA is still far ahead. What will it take to close the gap?

In this episode, Dylan Patel (Founder & CEO, SemiAnalysis) joins Erin Price-Wright (General Partner, a16z), Guido Appenzeller (Partner, a16z), and host Erik Torenberg to break down the state of AI chips, data centers, and infrastructure strategy.

We discuss:

• Why simply copying NVIDIA won’t work, and what it takes to beat them
• How custom silicon from Google, Amazon, and Meta could reshape the market
• The economics of AI model launches and the shift toward cost efficiency
• Infrastructure bottlenecks: power, cooling, and the global supply chain
• The rise of AI silicon startups and the challenges they face
• Export controls, China’s AI ambitions, and geopolitics in the chip race
• Big tech’s next moves: advice for leaders like Jensen Huang, Sundar Pichai, Mark Zuckerberg, and Elon Musk

Resources:

Find Dylan on X: https://x.com/dylan522p

Find Erin on X: https://x.com/espricewright

Find Guido on X: https://x.com/appenz

Learn more about SemiAnalysis: https://semianalysis.com/dylan-patel/

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

Genie 3 can generate fully interactive, persistent worlds from just text, in real time.

In this episode, Google DeepMind’s Jack Parker-Holder (Research Scientist) and Shlomi Fruchter (Research Director) join Anjney Midha, Marco Mascorro, and Justine Moore of a16z, with host Erik Torenberg, to discuss how they built it, the breakthrough “special memory” feature, and the future of AI-powered gaming, robotics, and world models.

They share:

• How Genie 3 generates interactive environments in real time
• Why its “special memory” feature is such a breakthrough
• The evolution of generative models and emergent behaviors
• Instruction following, text adherence, and model comparisons
• Potential applications in gaming, robotics, simulation, and more
• What’s next: Genie 4, Genie 5, and the future of world models
  

This conversation offers a first-hand look at one of the most advanced world models ever created.

Timecodes:

0:00 Introduction & The Magic of Genie 3

0:41 Real-Time World Generation Breakthroughs

1:22 The Team’s Journey: From Genie 1 to Genie 3

5:03 Interactive Applications & Use Cases

8:03 Special Memory and World Consistency

12:29 Emergent Behaviors and Model Surprises

18:37 Instruction Following and Text Adherence

19:53 Comparing Genie 3 and Other Models

21:25 The Future of World Models & Modality Convergence

27:35 Downstream Applications and Open Questions

31:42 Robotics, Simulation, and Real-World Impact

39:33 Closing Thoughts & Philosophical Reflections

Resources:

Find Shlomi on X: https://x.com/shlomifruchter

Find Jack on X: https://x.com/jparkerholder

Find Anjney on X: https://x.com/anjneymidha

Find Justine on X: https://x.com/venturetwins

Find Marco on X: https://x.com/Mascobot

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Find a16z on LinkedIn: https://www.linkedin.com/company/a16z

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Follow our host: https://x.com/eriktorenberg

Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

a16z General Partners Martin Casado and Anjney Midha join Erik Torenberg to unpack one of the most dramatic shifts in tech policy in recent memory: the move from “pause AI” to “win the AI race.”

They trace the evolution of U.S. AI policy—from executive orders that chilled innovation, to the recent AI Action Plan that puts scientific progress and open source at the center. The discussion covers how technologists were caught off guard, why open source was wrongly equated to nuclear risk, and what changed the narrative—including China's rapid progress.

The conversation also explores:

• How and why the AI discourse got captured by doomerism
• What “marginal risk” really means—and why it matters
• Why open source AI is not just ideology, but business strategy
• How government, academia, and industry are realigning after a fractured few years
• The effect of bad legislation—and what comes next

Whether you're a founder, policymaker, or just trying to make sense of AI's regulatory future, this episode breaks it all down.

Timecodes:

0:00 Introduction & Setting the Stage

0:39 The Shift in AI Regulation Discourse

2:10 Historical Context: Tech Waves & Policy

6:39 The Open Source Debate

13:39 The Chilling Effect & Global Competition

15:00 Changing Sentiments on Open Source

21:06 Open Source as Business Strategy

28:50 The AI Action Plan: Reflections & Critique

32:45 Alignment, Marginal Risk, and Policy

41:30 The Future of AI Regulation & Closing Thoughts

Resources

Find Martin on X: https://x.com/martin_casado

Find Anjney on X: https://x.com/anjneymidha

Stay Updated:

Let us know what you think: https://ratethispodcast.com/a16z

Find a16z on Twitter: https://twitter.com/a16z

Find a16z on LinkedIn: https://www.linkedin.com/company/a16z

Subscribe on your favorite podcast app: https://a16z.simplecast.com/

Follow our host: https://x.com/eriktorenberg

Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.