March 19, 2026

As artificial intelligence becomes a strategic capability for nations as well as companies, questions of governance, safety, and geopolitical competition are moving to the forefront. In this episode of TechSurge, host Sriram Viswanathan speaks with Helen Toner, Interim Executive Director of the Center for Security and Emerging Technology (CSET) at Georgetown and a former OpenAI board member, about the rise of sovereign AI stacks and the global implications of increasingly powerful AI systems.
Helen brings a rare vantage point from both inside the frontier AI ecosystem and the policy world. She reflects on lessons from her time on the OpenAI board, including the governance challenges that arise when nonprofit missions intersect with enormous commercial incentives and rapid technological progress. As AI capabilities accelerate, she argues that the industry is still grappling with deep uncertainty about how these systems work, how they will evolve, and what responsibilities companies and governments should carry.
The conversation explores the idea of sovereign AI; the growing push by countries to control key layers of the AI stack, including compute infrastructure, models, and data. Helen explains why governments increasingly view AI as a strategic national resource, comparable to past transformative technologies like electricity or the internet. At the same time, she cautions that full technological independence may be unrealistic for most nations, given the complexity and global interdependence of the AI supply chain.
Sriram and Helen also examine the evolving US–China AI competition, the role of export controls and semiconductor supply chains, and how different countries, from China to emerging AI hubs in the Middle East, are positioning themselves in the race to build advanced AI capabilities. Along the way, they discuss whether the industry should slow down development, how companies are experimenting with “safety frameworks” for frontier models, and why installing guardrails may be more realistic than attempting to halt progress altogether.
Ultimately, Helen argues that society is entering a period of profound uncertainty. AI is transitioning from a research discipline into a foundational system that will shape economies, security, and daily life. Navigating that transition will require not just technical breakthroughs, but new approaches to governance, transparency, and global cooperation.
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03:00 Lessons from the OpenAI Board: Governance in the Age of Frontier AI
05:00 The Big Unknowns in AI Development: Why Experts Still Disagree
12:05 Public Trust and the Risk of an AI Backlash
14:20 When AI Became Infrastructure: From Research Field to Societal System
16:00 Is AGI a Meaningless Term Now? Rethinking the Goalposts
19:05 AI’s True Scale: Internet-Level Impact or Something Bigger?
23:15 Why Frontier AI Labs Struggle to Slow Down
24:40 What “Sovereign AI” Actually Means for Nations
28:10 Mapping the AI Stack: Chips, Cloud, Models, and Applications
33:38 The US–China AI Competition: Who’s Ahead and Why
39:44 China’s Progress in AI: Compute Constraints and Fast Followers
44:03 US AI Policy: Export Controls, Regulation, and Federal Preemption
48:40 Frontier AI Safety Frameworks: How Labs Define Dangerous Capabilities
51:36 The Future of AI: Utopia, Industrialization, or Something Worse?
56:04 Rapid Fire: AI Misconceptions, Governance Reforms, and Regions to Watch
Connect with Helen: linkedin.com/in/helen-toner-4162439a
Learn more about CSET: https://cset.georgetown.edu/

Semiconductors have moved from the background of the technology stack to the center of the AI economy. What used to be a specialized industry discussed mostly by engineers and investors is now shaping the speed, cost, and strategic direction of modern computing.
In this episode of TechSurge, host Michael Marks speaks with Stacy Rasgon, Managing Director and Senior Analyst covering U.S. semiconductors and semiconductor capital equipment at Bernstein Research. Stacy has spent years analyzing the chip industry across cycles, but argues that the current moment feels different in scale: AI demand has created an unprecedented scramble for compute, memory pricing has surged, and companies across the stack are being forced to rethink capacity, architecture, and capital allocation.
The conversation explains the 4 different kinds of semiconductor cycles—supply, inventory, product, and demand — and why Stacy believes the industry is currently in a demand cycle of unusual magnitude. The discussion also unpacks the distinction between DRAM and NAND, why high-bandwidth memory is becoming strategically central to AI systems, and how the physical realities of wafer capacity and silicon area are constraining supply in ways the broader market often misses.
Stacy and Michael also discuss the hardware economics behind the current boom, with Michael pressing Stacy on why compute remains so scarce and how companies are improving performance through packaging and system design. Michael then moves the conversation beyond market headlines to the core business questions: who is actually paying for this compute, which use cases are generating real revenue, and whether AI spending is creating durable economic value or simply shifting costs elsewhere. Together, these questions highlight two of the episode's clearest insights: coding may be one of the earliest AI applications with meaningful willingness to pay, and inference, not training, is the real test of whether the current buildout becomes a lasting business or just another expensive wave of infrastructure.
Stacy explains the concentration of power among the major wafer fabrication equipment players, the rise of ASICs as a meaningful share of AI silicon, Broadcom's rapidly expanding AI opportunity, and the growing role of Chinese companies as new entrants, especially in memory and semiconductor equipment. Along the way, the conversation asks the defining question facing the sector: is this just another semiconductor upswing, or the first true supercycle the industry has seen? Stacy believes that this might be the biggest supercycle he has seen in his career.
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For most of human history, space has been a place we visited. The next chapter may be about building there.
For decades, space was the domain of governments, astronauts, and science fiction. Today, falling launch costs, reusable rockets, and a new generation of ambitious founders are turning orbit into something else entirely: a place to build. The question is no longer whether humanity can construct large-scale infrastructure in space, but what we should build first-and why.
In this episode of TechSurge, host Sriram Vishwanath speaks with Dr. Ariel Ekblaw, Founder and CEO of Aurelia Institute, Research Affiliate at MIT’s Space Exploration Initiative, and founder of Rendezvous Robotics. Ariel has spent her career exploring one of the most fundamental challenges of the emerging space economy: how to build structures in orbit that are far larger than anything that can fit inside a rocket.
Ariel explains the origins of TESSERAE, her pioneering work on autonomous self-assembling space architecture, and how ideas borrowed from biology, swarm intelligence, and modular construction could unlock a future of massive solar arrays, communications infrastructure, orbital laboratories, and eventually human habitats in space.
The conversation explores the rapidly emerging market for in-orbit infrastructure, including AI data centers in space, space-based solar power, and the technologies needed to support a permanent industrial presence beyond Earth. Ariel breaks down the engineering realities behind these ideas—why cooling data centers in space is harder than most people assume, how autonomous assembly could solve the scale problem, and why the future of orbital infrastructure may look more like a business park than a collection of standalone satellites.
Sriram and Ariel also discuss the broader implications of humanity’s return to space: the economics unlocked by reusable launch systems, the opportunities created by dramatically lower transportation costs, and the second-order innovations that may emerge from building an industrial ecosystem in orbit. Along the way, they examine space debris, stewardship of the orbital commons, artificial gravity, and what it will take to make long-term human habitation in space viable.
At the heart of the discussion is Ariel’s belief that space is not an escape from Earth’s problems, but a tool for solving them. Whether through advanced manufacturing, new energy systems, biotechnology research, or entirely new industries, she argues that the next era of space exploration should be focused on improving life here at home.
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For years, the United States told itself a reassuring story: China could manufacture and copy, but it couldn't innovate. That story is no longer credible. From DeepSeek's compute-efficient AI model to BYD's dominance of the global EV market, China is producing both volume and quality across sectors that matter. The question is no longer whether China can compete — it's whether the United States is playing its own hand well.
In this episode of TechSurge, host Michael Marks speaks with Vivek Chilukury, Senior Fellow at CNAS, where he focuses on U.S.–China technology competition, AI policy, and digital geopolitics. Vivek's path from counter-terrorism work at the State Department to tech policy in the Senate gives him an unusually grounded perspective on how government actually functions — and where it keeps failing itself.
Vivek and Michael work through the full competitive landscape: the wake-up moments that shifted Washington's focus from manufacturing to technology dominance, why the dual-use nature of advanced technology has pulled the national security community into conversations once left to industry, and what Made in China 2025 actually achieved — and where it fell short.
The conversation goes deep on America's policy toolkit: what the CHIPS Act accomplished and why it wasn't enough, how export controls on advanced semiconductors are working and what they're missing, and why Washington is far too weighted toward restriction at the expense of the "run faster" side of the equation. Vivek is also candid about what DeepSeek really tells us — not just about Chinese innovation, but about the gap between building a model and deploying AI at scale.
They also explore the global dimension: China's "easy button" approach to technology exports, what the U.S. AI exports program is trying to do in response, the rise of "AI sovereignty" movements from Brussels to Delhi, and why the talent and immigration decisions of the past year amount to a serious self-inflicted wound.
The United States still holds the best hand in the world for this competition. The question Vivek keeps returning to is whether we're playing it well — and right now, his honest answer is no.
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