Networking Optimizations for Multi-Node Deep ...

In this episode, Sebastian Raschka, independent LLM researcher and author, joins us to break down how the LLM landscape has changed over the past year and what is likely to matter most in 2026. We discuss the shift from raw model scaling to reasoning-focused post-training, infere ...  Show more

Today, we're joined by Yejin Choi, professor and senior fellow at Stanford University in the Computer Science Department and the Institute for Human-Centered AI (HAI). In this conversation, we explore Yejin’s recent work on making small language models reason more effectively. We ...  Show more

The world is hitting a data tipping point where vast connectivity requires massive network capacity. In this episode of Smart Talks, Malcolm Gladwell talks to David Shacochis, Vice President for Enterprise Technology and Field CTO at Lumen, and Howard Boville, Head of IBM Cloud P ...  Show more

<span style= "font-weight: 400;">Stephanie Wong</span> <span style= "font-weight: 400;">and</span> <span style= "font-weight: 400;">Carter Morgan</span> <span style= "font-weight: 4 ...

Today’s episode is a conversation about four big trends in the tech world. Any one of these trends would be notable on its own, but we cover all four in this hallway-style chat, as a16z General Partner Chris Dixon talks with Sep Kamvar (professor of Media Arts and Sciences at MIT ...  Show more

Autonomous vehicles are one of the most complex AI challenges of our time. The networks running in the car must act as an intricate symphony, requiring intensive training, testing and validation on massive amounts of data to operate safely in the real world. Clément Farabet is th ...  Show more