Today we’re joined by Sophia Sanborn, a postdoctoral scholar at the University of California, Santa Barbara. In our conversation with Sophia, we explore the concept of universality between neural representations and deep neural networks, and how these principles of efficiency provide an ability to find consistent features across networks and tasks. We also d ... Show More
Yesterday
From Voice Agents to AI Avatars with Alexander Smola - #777
Voice AI has gotten remarkably good, but natural conversation remains a high bar. Small delays, awkward interruptions, or the wrong tone can quickly break the illusion—and adding vision and visual presence only raises the stakes. In this episode, Alex Smola, co-founder and CEO of ... Show More
1h 4m
Sep 1
World Models and the Future of Spatial AI with Justin Johnson - #775
In this episode, Justin Johnson, co-founder of World Labs, joins us to discuss world models and the emerging field of spatial AI. We explore why many researchers see capabilities beyond language as an important frontier for AI, and what it means to build models that can understan ... Show More
1h 6m
Apr 2023
The Power of Graph Neural Networks: Understanding the Future of AI - Part 2/2 (Ep.224)
<p>In this episode of our podcast, we dive deep into the fascinating world of Graph Neural Networks.</p>
<p>First, we explore Hierarchical Networks, which allow for the efficient representation and analysis of complex graph structures by breaking them down into smaller, more mana ... Show More
35m 32s
