The future of AI may be decided in backyards. Data Centers—the sprawling facilities designed to support the massive computing required to train and run AI models—are being built across the country. One estimate sees more than $1 trillion dollars in capital spending on data centers in the next four years. And they use electricity—a lot of it. While data centers can bring construction jobs,  tax revenue, and economic development to their communities, they also bring complaints about power and water usage, noise pollution, and architectural blight.

Debates are raging from town halls to the halls of Congress. Yes, politicians want the US to lead the world in AI, but elected officials, particularly local ones, are hearing from constituents concerned about data centers, including the potential to raise electric bills. The decisions being made right now in places like Northern Virginia, Umatilla, Oregon, and Mount Pleasant, Wisconsin, will determine whether AI infrastructure is scaled quickly, or whether a backlash slows it down. If done right, data centers can bring world-class tech capabilities, lower electricity prices, energy abundance, and local tax revenue. Done poorly, we see working class Americans paying more for power, the electric grid struggling, and the potential for the American public to turn sour on data canters en masse.

So what do people need to know about data centers to make informed decisions? What really is the impact of data centers on water and electricity? What should policymakers in Washington do, if anything, about these debates? And are there ways to balance legitimate local concerns without hamstringing a strategic imperative?

Evan is joined by Asad Ramzanali, Director of Artificial Intelligence & Technology Policy at the Vanderbilt Policy Accelerator. He was previously Chief of Staff at the White House Office of Science and Tech Policy under President Biden and Legislative Director to former Rep. Anna Eshoo (D-CA). You can read his recent op-ed on data centers here. Evan is also joined by Daniel King, Research Fellow at FAI where he focuses on the energy and security dimensions of artificial intelligence. Daniel completed Master's studies in Statistics & Data Science at Yale University and earned a B.S. in Mechanical Engineering and Applied Mathematics from Brown University. Check out his substack on AI and energy, Policy Gradients.

For three decades, conservatives abandoned science policy. Now they have a chance to rebuild it.

That rebuilding effort comes with political challenges. Republicans' trust in science dropped thirty points over those decades. DOGE recently  slashed budgets at the National Science Foundation and National Institutes of Health. And HHS Sec RFK jr. is casting doubt on the efficacy of vaccines to the alarm of many Republicans in Congress. But beyond the politics, American science is also facing a competitive threat from China. The Middle Kingdom invests tens of billions in biotech and quantum computing, and outpaces the U.S. in PhD STEM grads.

Meanwhile, American research became a system that rewards process over results. Researchers spend 42% of their time on paperwork. Only 46% of cancer studies could be replicated. And our guest today argues that perverse incentives and bureaucracy led to decades wasted on Alzheimer’s research that turned out to be fraudulent—among other misfires.

Ian Banks is Director of Science Policy at the Foundation for American Innovation, which recently established the science program he leads at the organization. He and Evan discuss his vision for a renewed conservative approach to science—one that learns from diversified investment portfolios that maintain safe bets while also making room for moonshots. They get into the political challenges created by hot button issues like climate change and COVID response, how to properly fund science in the era of DOGE, and what the proper role for politics in science should be.

Previously, Banks served in research roles at the Conservative Coalition for Climate Solutions, the American Enterprise Institute and as a legislative aide to Rep. Bill Posey, where he focused on science, energy, and health policy. His Oxford master's thesis examined the replication crisis, and he brings firsthand experience navigating these questions during COVID from his time working on the Hill.

California governor Gavin Newsom recently signed into law the country’s first comprehensive regulatory framework for high-risk AI development. SB 53, or the Transparency in Frontier Artificial Intelligence Act, is aimed at the most powerful, “frontier” AI models that are trained with the highest computing and financial resources. The bill requires these developers to publish information on how they evaluate and mitigate risk, report catastrophic or critical safety incidents to state regulators, maintain protocols to prevent misuse of their models, and provide whistleblower protections to employees so they can report serious risks. SB 53 is significantly narrower in scope than the controversial SB 1047, which was vetoed by Newsom in 2024. Nonetheless, it is adding fuel to a burning debate over how to balance federal and state AI regulation. 

While California’s AI safety bill is targeted at the largest AI developers, advocates for startups and “Little Tech” worry that they will end up caught in the crosshairs anyway. Jai Ramaswamy and Matt Perault of a16z join today to argue that attempts to carve out Little Tech from the burdens of AI regulation fall flat, because they focus on the wrong metrics like the cost of training AI models and computing power. Rather than try and regulate the development of AI, policymakers should focus on how AI is used—in other words, regulate the misuse of AI, not the making of AI.

Matt Perault is the Head of Artificial Intelligence Policy at Andreessen Horowitz, where he oversees the firm's policy strategy on AI and helps portfolio companies navigate the AI policy landscape. Jai Ramaswamy oversees the legal, compliance, and government affairs functions at Andreessen Horowitz as Chief Legal Officer. They’ve written extensively on AI regulation for Little Tech.

FCC Chairman Brendan Carr just announced "Space Month" at the agency. Speaking from Apex's new satellite manufacturing facility in El Segundo, California, Carr laid out an ambitious plan to transform the FCC into what he calls a "license assembly line." The goal? Move from a "default no" to a "default yes" mindset, slash regulatory backlogs, and help American companies manufacture satellites at the speed and scale needed to compete with China's growing orbital ambitions. We're talking thousands of small satellites, direct-to-cell connectivity, and a fundamental reimagining of how government keeps pace with private sector innovation.

This episode takes you inside the El Segundo space ecosystem—the neighborhood that helped win the first space race and is now being reindustrialized to win the second one. FAI's Josh Levine hosts a panel with space industry leaders from Apex, Northwood Space, and Varta Space, who discuss everything from supply chain bottlenecks to the challenges of attracting talent in Southern California's red-hot aerospace scene. These aren't legacy defense contractors slowly building massive satellites—they're startups manufacturing dozens of platforms per month, treating satellites more like software products than bespoke engineering projects.

In the second half, Digital First Project’s Nathan Leamer sits down with Chairman Carr and Apex CEO Ian Cinnamon for a wide-ranging conversation about the geopolitical implications of space dominance, the unfair advantages China's state-backed companies enjoy, and why changing the terminology from "satellite bus" to "satellite platform" actually matters. Plus: why Starlink on airplanes is a productivity game-changer, how direct-to-cell technology could transform connectivity, and what it means when the same warehouses that built Apollo-era technology are now cranking out satellites for the 21st century.

In President Trump’s second term, federal agencies are navigating uncharted territory. Two Supreme Court cases from June 2024 fundamentally changed how agencies can operate: Loper Bright ended Chevron deference—meaning courts no longer automatically defer to agencies' interpretations of ambiguous laws—and Jarkesy limited agencies' ability to impose civil penalties without jury trials.

At the same time, President Trump is consolidating control over agencies that were traditionally seen as independent from the executive branch. He's fired commissioners from the FTC, NLRB, and other agencies as part of his push for a "unitary executive." Former FTC Commissioner Rebecca Slaughter is fighting her dismissal, and the Supreme Court recently allowed the firing to stand while it reviews the case.

The fundamental tension? Courts are stripping power from agencies just as Trump is trying to bring those agencies under tighter presidential control. Will Loper Bright and Jarkesy make these agencies less useful tools for implementing Trump's agenda, even if he wins the fight to end their independence? And how will these cases impact the FCC’s authority looks to reform its broadband subsidy programs while fighting illegal robocalls?

Evan is joined by Tom Johnson, former general counsel of the FCC under Chairman Pai and now a partner at Wiley Rein. He is the author of a new paper for Digital Progress Institute on ways to reform the Universal Service Fund.

In this follow-up to his interview with Senator Joni Ernst, Evan dives into the legislative weeds of government efficiency reform with FAI scholars Dan Lips and Lars Schönander. While DOGE grabbed headlines with federal worker layoffs and chainsaw imagery, the real lasting impact may come from less flashy but more fundamental fixes: stopping the Treasury Department from sending checks to dead people, preventing Chinese-linked companies from exploiting small business research programs, and codifying anti-fraud measures that could save tens of billions annually.

The conversation reveals how Ernst's decade-long crusade against government waste has created a legislative roadmap for the Trump administration's efficiency agenda. From strengthening the Treasury's "Do Not Pay" database to reforming the compromised Small Business Innovation Research program, these aren't partisan talking points but bipartisan solutions with Obama-era origins that have been stalled by bureaucratic inertia and special interests. With Ernst's retirement creating a 15-month window and SBIR authorization expiring next week, the episode captures a pivotal moment when policy wonk proposals might finally become permanent law—or get lost in the political shuffle once again.

For over a decade, Senator Joni Ernst (R-IA) has been a persistent voice against government waste, issuing "squeal awards" that exposed bureaucratic excess when few were paying attention. What began as a somewhat thankless crusade has now become the intellectual foundation for one of the Trump administration's signature initiatives. As Chair of the Department of Government Efficiency (DOGE) Caucus, Ernst finds herself in the position of watching her longstanding concerns become White House priorities—from fraudulent payments to foreign exploitation of small business research programs. She’s working to implement solutions she's spent years developing, including a blueprint for $2 trillion in potential taxpayer savings.

Ernst recently announced that she won’t be seeking reelection, creating a 15-month timeline for her to put her stamp on the U.S. Congress. The convergence of her institutional knowledge and Trump's reform mandate, with her lame-duck freedom to take risks, positions her as a unique figure in determining whether and how DOGE leaves a lasting impact on the federal government. The question isn't just what she hopes to accomplish in her remaining tenure, but what the government efficiency movement may look like without its most dedicated practitioner. Senator Ernst joins Evan to discuss her legislative efforts to root out government waste and what she hopes to accomplish before she leaves the Senate.

Not too long ago, NVIDIA was a niche tech company known for the graphics cards that powered computer gaming. Thanks to skyrocketing growth over the past few years, today, it’s a $4 trillion behemoth that designs cutting-edge chips necessary for frontier AI development. It’s an American company based in Santa Clara, CA. But, like so many other companies, it relies on foreign firms to manufacture its designs—primarily Taiwan Semiconductor Manufacturing Company.

Intel is the only major American company that manufactures its own advanced semiconductors, or chips, but the once iconic firm is on an opposite trajectory. In the 1990s and early 2000s, Intel’s microprocessors powered over 90% of PCs and the company was one of the world’s most valuable. But intel missed the boat on two major tech developments—smartphones and AI—leaving the company a shell of its former glory.

NVIDIA soared while Intel declined, but the two share in common a rollercoaster relationship with Washington and the Trump Administration over their ties to China.  After moving to ban NVIDIA from exporting its H20 chip to China, President Trump reversed the ban in exchange for NVIDIA giving a 15% cut of the sales to the US government. Last month, Intel CEO Lip-Bu Tan came under fire for his ties to and investments in Chinese companies, leading Trump to call for his immediate resignation. A few weeks later, Trump announced that the US government would take a 10% stake in Intel for about $10 billion in outstanding CHIPS Act grants, and Trump praised Tan for his affirmed commitments to US interests.

The two companies are at the heart of the most significant tech policy debates in the world—from industrial policy to how to balance a desire to export American technology with the need to safeguard trade secrets and AI advantages. Evan is joined by Oren Cass, founder and chief economist of American Compass. Oren has been a staunch supporter of the CHIPS Act and industrial policies that he believes are necessary to restore high-tech American manufacturing, particularly in semiconductors. He’s also been highly critical of the Administration’s recent moves to allow NVIDIA to export more of its chips to China. 

Read his op-ed in The Washington Post on NVIDIA’s H20 and his newsletter on the topic, as well as his recent op-ed in Commonplace on NVIDIA’s potential antitrust problems. See his newsletter here for more on his reaction to the U.S. government’s equity stake in Intel.

This week, we're crossposting this episode where our own Evan Swarztrauber joined American Moment CEO Nick Solheim on the Moment of Truth podcast to discuss the evolving politics of Big Tech on both left and right.

Evan draws on his FCC experience during the net neutrality debates to explore how conservative thinking on tech regulation has shifted. He and Nick discuss key moments like the Parler de-platforming and examine whether recent conservative support for antitrust enforcement represents a genuine policy evolution or short-term political expediency.

From Google's search dominance to content moderation battles, they unpack the tension between free market principles and concerns about corporate power over speech. The discussion offers insights into how tech policy debates are reshaping both ideology and regulatory approaches. 

When Stanford students Elsa Johnson and Garret Molloy began investigating Chinese intelligence operations on their campus for the Stanford Review, they uncovered something far more extensive than expected: a systematic intelligence network that has transformed thousands of Chinese students into assets for Beijing's technology collection efforts. Their investigation revealed that between 20,000 and 50,000 Chinese students studying in America receive funding from Beijing's China Scholarship Council, with many maintaining contact with "handlers" who expect regular intelligence reports.

This discovery exposes a fundamental asymmetry in how China and America approach academic exchange. Beijing leverages our relatively open research environment through "nontraditional collection"—crowdsourced intelligence gathering through students and researchers—while maintaining strict control over their own institutions. China wants access to our openness while preserving their own secrecy.

But America's response threatens to undermine the very qualities that make our universities innovative. The trade-off seems impossible: remain vulnerable to systematic exploitation or adopt surveillance methods that mirror authoritarian systems. Can universities maintain their innovative edge while protecting sensitive research? Johnson and Molloy's investigation reveals how these questions will shape the future of American higher education in an age of great power competition.

Note: The Stanford Review was erroneously referred to as the "Stanford Economic Review" once in this episode.