Jul 11, 2026

Why AI Agents Don't Actually Understand You — Danielle Perszyk, Amazon AGI Lab

Daniel from Amazon AGI Lab details a cognitive science-driven vision for human-aligned AI, focusing on collective intelligence, real-time interaction, and redefining reliability through user mind modeling. He emphasizes aligning AI representations with human cognition to foster generalization, prevent reduced human agency, and revolutionize areas like education, advocating for diverse AI systems and frontier research over immediate productization.

May 23, 2026

Prompt to Pipeline: Building with Google's Gen Media Stack — Paige & Guillaume, Google DeepMind

A comprehensive overview of Google DeepMind's latest advancements, featuring Paige Bailey demonstrating Gemini 1.5 Flash's cost-effective video analysis and AI Studio's single-prompt app generation. Guillaume Vernade showcases a full generative media pipeline, turning a public domain book into an illustrated, animated, and scored project using Gemini, Nano Banana, VO, and LIA. Ian Valentine closes with the power of Gemma 4, demonstrating on-device, multi-agent code generation and debugging without cloud APIs.

May 01, 2026

Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy

Dmitri Dolgov, co-CEO of Waymo, discusses the 20-year journey from the DARPA challenge to full autonomy. He explains the Waymo Foundation Model—a multimodal world action model powering the driver, simulator, and critic—and how their "end-to-end plus" architecture enables superhuman safety and exponential scaling.

Apr 30, 2026

Robotics' End Game: Nvidia's Jim Fan

Jim Fan of Nvidia outlines the endgame for robotics, arguing it will mirror the successful playbook of Large Language Models. He introduces "The Great Parallel," a roadmap where World Models replace Language Models, and data collection shifts from limited teleoperation to scalable egocentric video, culminating in a future of physical APIs and automated research.

Apr 23, 2026

Why Most Robot Demos Are Fake

Changan Chen, co-founder of Rhoda AI, discusses their vision-first approach to building foundation models for robotics. The conversation covers their unique training pipeline, the distinction between policy and world models, and the path to deploying data-efficient, reliable robots in real-world industrial settings.

Apr 15, 2026

Why Uber, Nissan, and Mercedes Chose This Self-Driving Startup | Alex Kendall, Wayve

Wayve CEO Alex Kendall discusses their contrarian, AI-first approach to autonomous driving. He explains their journey from a garage prototype using reinforcement learning to developing a generalizable AI driver that has driven zero-shot in over 500 cities. Kendall emphasizes a strategy focused on licensing this embodied AI for mass-market consumer vehicles—a 100-million-unit-per-year opportunity—rather than building bespoke robotaxis, arguing that the future is an AI that can drive any car, anywhere.