Driving Safer AVs Faster with Smart Simulation, Neural Reconstruction, and Data-Centric Tools - Ep. 289

Instacart has 1.6 billion lifetime grocery orders—and is now using that data flywheel to digitize the physical store itself. In this episode, David McIntosh, Chief Connected Stores Officer at Instacart, explains how the Caper Cart—powered by an NVIDIA Jetson™ board and a sensor fusion system combining cameras, weight sensors, and location data—is bringing edge AI to the grocery aisle. He shares what's driving double-digit sales lift for retailers, how AI agents are beginning to automate store operations, and why in-store and online shopping will merge into a single unified experience within the decade.

Open-weight models are closing the gap with proprietary AI — and Timothée Lacroix, cofounder and CTO of Mistral, has been betting on that since day one. In this episode, he explains why open weights accelerate enterprise adoption, how Mistral is bringing model customization into production, and what a 2.5x training speed improvement on GB200s means for the next generation of large sparse mixture-of-experts models. He also shares the open problem keeping him up at night: getting AI agent permission systems right before write access becomes the norm.

Seeed Studio is a leader in open source robotics, delivering affordable NVIDIA Jetson‑powered arms that put embodied AI into the hands of millions of makers, students, and small businesses. In this episode, Seeed Studio CEO Eric Pan and Head of Robotics Elaine Wu explain how open hardware, the OpenClaw agentic framework, and NVIDIA Isaac Sim are turning robot arms into controllable, teachable agents—and what it takes to bring these physical AI tools into real‑world settings responsibly.

As AI factories scale and token costs become a defining competitive variable, the way businesses measure infrastructure ROI needs to change. In this episode, Shruti Koparkar from NVIDIA's Accelerated Computing team breaks down tokenomics—the four-pillar framework of token utility, supply, demand, and monetization—and reveals why NVIDIA Blackwell's architecture delivers 50x more tokens per watt than NVIDIA Hopper, translating to a 35x reduction in token cost.

Snap processes more than 10 petabytes of experimentation data every single morning—and with NVIDIA GPU-accelerated Apache Spark on Google Cloud, Snap cut job costs by 76%, reduced memory usage by 80%, and eliminated 120 terabytes of disk spill from its pipelines.