What happens when artificial intelligence enters the most dangerous decision-making systems humans have ever built?

In this episode of AI-Curious, we talk with Ankit Panda and Andrew Reddie about the real risks of AI and nuclear weapons. Ankit is the Stanton Senior Fellow in the Nuclear Policy Program at the Carnegie Endowment for International Peace and author of The New Nuclear Age. Andrew is a professor at UC Berkeley’s Goldman School of Public Policy and faculty director of the Berkeley Risk and Security Lab.

This is not a conversation about Skynet or killer robots. Instead, we explore the more grounded, near-term ways AI is already intersecting with nuclear strategy, military decision-making, cyber risk, early warning systems, targeting, and command and control. We look at the full spectrum of risk, from AI helping edit policy memos to AI systems advising leaders during a possible nuclear crisis.

We also discuss why cybersecurity may be the most urgent near-term concern, how AI could affect nuclear deterrence and crisis stability, and why explainability, testing, and human judgment matter so much in high-stakes environments. Along the way, we revisit the famous Stanislav Petrov incident, explore dead hand systems and automation bias, and ask what it really means to keep humans in the loop when AI is moving faster than institutions can adapt.

Guests:
Ankit Panda — Stanton Senior Fellow, Nuclear Policy Program, Carnegie Endowment for International Peace

Andrew Reddie — Professor, Goldman School of Public Policy, UC Berkeley; Faculty Director, Berkeley Risk and Security Lab

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Can a 23-year-old video game help train the next generation of AI agents?

In this episode of AI-Curious, we talk with Hilmar Pétursson, CEO of Fenris Creations, the studio behind EVE Online, about why Google DeepMind has invested in the company and why EVE may be one of the hardest tests for artificial intelligence.

EVE Online is not just a space game. It is a persistent virtual civilization with player-run economies, alliances, corporations, spies, propaganda, logistics, years-long wars, and decades-old rivalries. That makes it a fascinating training ground for some of the biggest unsolved problems in AI: long-horizon planning, memory, continual learning, imperfect information, coordination, and agents that can operate inside messy real-world systems.

We explore why EVE is so much more complex than games like chess, Go, or StarCraft, and why Hilmar sees it as a possible “final boss” for AI in games. We also discuss how DeepMind could use EVE as a research environment, what an “AlphaEve” might eventually mean, and why virtual worlds may help AI systems learn in ways that resemble how humans and animals learn through play.

Along the way, we get into the business implications of AI agents, the parallels between EVE alliances and real-world companies, the idea of AI chief-of-staff agents, and the possibility of giving frontier AI labs like OpenAI, Anthropic, DeepMind, and xAI their own territories in EVE Frontier to see which AI best helps humans thrive. Hilmar also shares the story behind his conversations with Elon Musk, how EVE players are already using AI, and why he believes AI could help us unlock new versions of ourselves.

Guest:
Hilmar Pétursson — CEO, Fenris Creations

Check out:
Fenris Creations: https://fenris.com/
EVE Online: https://www.eveonline.com/

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What happens when AI stops being just a software story and starts showing up in towns, power grids, zoning fights, data centers, and business workflows?

In this episode of AI-Curious, we talk with Sharon Goldman, longtime AI journalist (most recently senior reporter at Fortune) who’s now the founder of Ground Level AI, which focuses on the real-world impact of the AI boom: infrastructure, data centers, cybersecurity, enterprise adoption, policy, geopolitics, and the communities affected by it all.

We dig into Sharon’s reporting on AI data centers across the United States, including communities in Arizona, Louisiana, Michigan, and Texas that are grappling with new development, construction chaos, zoning disputes, water and electricity concerns, noise, jobs, tax revenue, and a larger sense that AI is arriving faster than people expected. We also talk about why data centers have become a proxy for broader AI anxiety, and why the conversation often gets more complicated than a simple pro-AI or anti-AI split.

Then we turn to the fast-moving world of frontier models, cybersecurity, and enterprise AI. We discuss the Mythos and Fable saga, the tension between open and closed models, why companies are rethinking model lock-in, and why business leaders increasingly want choice, redundancy, and model-agnostic AI strategies. Sharon also shares how she thinks about covering AI as a journalist, what stories she believes are still underreported, and how she uses AI herself as a solo creator building a new media business.

Guest
Sharon Goldman — Journalist and Founder, Ground Level AI

Check out Sharon’s work

• Ground Level AI: https://www.groundlevel-ai.com/
• Sharon’s reporting on data centers in Texas: https://fortune.com/2026/06/16/ai-data-center-texas-lacy-lakeview-ross/

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For anyone interested in Jeff’s AI Workshops for their company:

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