
Hosted by Radical Ventures · EN

Aaron Rosenberg and Rich Kotite, Partners at Radical Ventures, join Molly Welch to discuss "The Rise of NeoLabs," their report mapping the researcher-led AI startups raising massive capital. Drawing on Radical's track record backing companies like World Labs and Inherent, they dig into the research paradigms attracting top talent, how investors evaluate these early-stage teams, and what it takes to build a category-defining lab.

Yvonne Likomanova, Senior Director of Talent at Radical Ventures, digs into what's really driving the AI talent flows. Drawing on a career that spans Stripe, Cruise, Applied Intuition, Yvonne shares where the world's best researchers and engineers are setting their sights. The conversation covers why elite talent is leaving frontier labs for a new class of research-first institutions, what candidates are really optimizing for beyond compensation, and what founders need to get right today to compete for the people who will define their company's trajectory.

Michael Rubenstein, Co-Founder & Co-CEO of Firsthand, joins Radical's Molly Welch to dig into what's broken in digital advertising — a trillion-dollar-plus industry that AI isn't just improving, it's replacing entirely. Drawing on a career that spans DoubleClick, AppNexus, and now Firsthand, Michael makes the case for why the future belongs to brand agents, not ads. The conversation covers how Firsthand's infrastructure meets consumers at the moment of intent, why the real bottleneck is structural rather than technical, and what has to be true for this new model to go mainstream without leaving brands behind.

Varun Sivaram, Founder & CEO of Emerald AI, joins Radical Partners Molly Welch and Rob Toews to explore what's actually holding back AI infrastructure. While the conversation around AI bottlenecks tends to focus on chips and models, Varun explains why the binding constraint is power, from grid capacity limits and interconnection backlogs to the widening gap between compute demand and energy supply. Drawing on his path from senior energy official in the Biden White House to CTO of India's largest solar company to founding Emerald AI, the discussion unpacks why the fix is software, not just more generation, how Emerald's Conductor platform turns data centers into flexible, grid-responsive assets, and what has to be true for AI infrastructure to scale without breaking the grid.

When Ori Eldarov started Offdeal, he wasn't thinking about AI as a productivity hack. He was thinking about what it would take for a small team to compete with firms that had been doing this for decades. Thirteen people. Nearly $10 million in their first full year. This founder-first take was recorded during our October AI Founders Masterclass, before agentic workflows entered the mainstream conversation. The technology has moved fast but the principles remain the same.

Arsham Ghahramani, CEO and Co-Founder of Ribbon, joins Radical Partner Sanjana Basu to unpack fundraising from the founder’s side of the table. With a PhD in AI focused on cancer research and early experience scaling recommendation systems at Amazon, Arsham brings both technical depth and operating perspective to the conversation. Now he leads Ribbon, an AI hiring platform that has conducted over one million interviews and raised $8M+ to date. They break down what actually drives venture conviction, how founders should think about fund theses and stages, and why investor relationships start long before a formal raise. From the reality of two-seconds-per-slide pitch reviews to navigating process opacity with clarity, this episode offers a pragmatic look at how to approach capital with strategy and confidence.

Jim Fan, Director and Distinguished Research Scientist at NVIDIA, joins Radical Partner Molly Welch to explore what's holding back embodied AI and robotics. While large language models have advanced rapidly, Jim explains why progress in the physical world depends less on ever-larger models and more on solving fundamental problems: exploration-driven learning, scalable data pipelines, and synthetic simulation. Drawing on his journey from OpenAI to leading NVIDIA's Project GR00T, they discuss the robotics data bottleneck, why foundation models matter, and what must happen before robotics reaches its "GPT-4 moment."

John Maslin, CEO and Co-Founder of Vulcan Elements, joins Radical Partner Molly Welch to unpack the overlooked physical infrastructure behind AI. While chips dominate most conversations, John explains why rare earth magnets are a foundational dependency across data centers, semiconductor manufacturing, robotics, EVs, and defense systems, and why today’s globally concentrated supply chain poses real economic and national security risk. Drawing on his work rebuilding domestic magnet manufacturing, the discussion explores what it takes to reshore critical industrial capacity, why execution matters more than policy alone, and how physical constraints will increasingly shape AI at scale.

Databricks Chief AI Scientist Jonathan Frankle joins Radical Partner Vin Sachidananda for a special conversation from Radical Ventures’ AI Masterclass Series. Together, they explore what it takes to move AI from academic insight to real-world, enterprise-scale deployment. Drawing on Jonathan’s experience co-founding Mosaic ML and now leading research at Databricks, the discussion covers why early efficiency gains feel “quaint,” how open-source serves as scientific proof, and why evaluation remains the missing infrastructure for enterprise AI adoption. A practical conversation for founders and technical leaders building AI systems that need to perform in production.

The story of modern AI cannot be told without Geoffrey Hinton and Jeff Dean. In this special episode of Radical Talks, recorded live at NeurIPS, the longtime collaborators and friends join Radical Ventures Co-Founder Jordan Jacobs to explore how bold ideas finally met the infrastructure required to scale them. From early breakthroughs at Google to the choices shaping today’s systems, they reflect on the leadership decisions, risks, and responsibilities that will define what comes next for AI.