No Priors Ep. 125 | With Senior White House Policy Advisor on AI Sriram Krishnan

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 show@no-priors.com 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

Sarah GuohostElad GilhostSriram Krishnanguest

Jul 30, 202536mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

White House AI Advisor Outlines America’s Strategy To Win Global Race

Senior White House policy advisor on AI, Sriram Krishnan, outlines the new American AI Action Plan, positioning AI as a decisive economic, cultural, and military battleground—especially versus China. He argues the U.S. lead is small and fragile, using China’s DeepSeek as a wake-up call that triggered a more aggressive national AI strategy. The plan focuses on three pillars: building massive AI infrastructure and energy capacity, removing regulatory obstacles to innovation (especially for open source), and exporting an "American AI stack"—from GPUs to models—to allies worldwide. Krishnan also emphasizes fighting ideological bias in government AI systems and embedding technologists at the center of U.S. policymaking to move fast and compete effectively.

IDEAS WORTH REMEMBERING

5 ideas

America’s AI lead over China is narrow and cannot be assumed.

DeepSeek’s performance and technical innovations showed that Chinese labs can rapidly close the gap, forcing U.S. policymakers to treat AI as an urgent, close-run geopolitical competition rather than a comfortable lead.

Winning the AI race requires massive new infrastructure and energy build‑out.

Decades of low power‑demand growth left the U.S. grid, permitting regime, and generation capacity unprepared for AI-scale data centers, so the plan prioritizes “build, baby, build” reforms to speed data center siting, energy projects, and grid upgrades.

Federal policy will aim to preempt fragmented state regulation that could stifle AI.

Krishnan cites California’s near‑miss SB‑1047 as an example of state rules that could have effectively killed U.S. open‑source models; the strategy is to keep core AI rules at the federal level to avoid a patchwork that over‑constrains startups and open development.

Open source AI is framed as both an innovation engine and a security advantage.

The White House team argues that open models democratize access for startups and researchers, counter Chinese open models already being widely used, and—like open software historically—benefit from broader scrutiny that can make them safer and more robust.

The administration wants U.S. hardware, models, and apps to dominate global inference.

They think in terms of global “token market share”: maximizing the proportion of all AI inferences running on American GPUs, models, and applications, and are revisiting restrictive export rules (like the Biden Diffusion Rule) to push an American stack to allies.

WORDS WORTH SAVING

5 quotes

“DeepSeek told us that America doesn’t have a huge lead on AI. It actually has a very, very small lead.”

— Sriram Krishnan

“We think if America is going to win the race with China, we need to do three things: build infrastructure, unleash innovation, and make sure the world uses our stack.”

— Sriram Krishnan

“The Biden team really looked at AI as something to be centralized and controlled… We want to enable anybody to go build something amazing, not centralize power within a 10‑mile radius of D.C.”

— Sriram Krishnan

“By default, open source is just safer and more secure. More scrutiny you put your libraries through, the safer it becomes—and I think the same holds true for open source and open weights.”

— Sriram Krishnan

“Very simply, we want to win.”

— Sriram Krishnan

Geopolitical AI race between the United States and China, catalyzed by DeepSeekThe American AI Action Plan: goals, structure, and three main pillarsAI infrastructure, energy demand, and permitting/grid constraintsRegulation, federal vs. state authority, and cutting red tape for AI innovationOpen source and open weights models as strategic national assetsExporting an “American AI stack” and revising GPU export controlsCultural and ideological bias in AI models, including the “No Woke AI” executive order

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