Can AI Fix Housing and Healthcare Affordability?

Do tariffs help rebuild American manufacturing or hold it back? In this episode, American Compass founder and chief economist Oren Cass sits down with commentator and author Noah Smith and a16z General Partner Erik Torenberg for a lively debate on the future of U.S. industry. They discuss the case for tariff-driven re-industrialization versus free-market approaches, the role of allies in trade policy, and what the numbers really show about manufacturing jobs, investment, and output. Along the way, they challenge each other’s assumptions and explore what it would take to actually bring more production back to American soil.

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

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.

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.

We’re sharing an episode from ChinaTalk that dives into one of the biggest recent reversals in U.S. tech policy. The U.S. banned Nvidia’s H20 AI chips to China in April. Now, just months later, they’re being sold—with a 15% export fee. What happened? Why the reversal? And what does it mean for the future of AI competition between the U.S. and China? Chris Miller—author of Chip War—and Lennart Heim from RAND join ChinaTalk host Jordan Schneider to unpack the policy flip-flop, why China is publicly downplaying interest in the H20, and why high-bandwidth memory and semiconductor manufacturing tools may be even more important than the Nvidia chips themselves.