Resumen del episodio
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. 🔬Topics covered: How Caper Carts use NVIDIA Jetson and sensor fusion to identify items in real time Why edge AI matters: hundreds-of-milliseconds response vs. seconds in the cloud Double-digit sales lift from personalized in-cart recommendations Building a grocery foundation model from 1.6B orders and live in-store data AI agents for store ops: proactive out-of-stock alerts and CPG shelf optimization Chapters:…
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. 🔬Topics covered: How Caper Carts use NVIDIA Jetson and sensor fusion to identify items in real time Why edge AI matters: hundreds-of-milliseconds response vs. seconds in the cloud Double-digit sales lift from personalized in-cart recommendations Building a grocery foundation model from 1.6B orders and live in-store data AI agents for store ops: proactive out-of-stock alerts and CPG shelf optimization Chapters:…
Episodios
Inside Instacart's AI-Powered Smart Shopping Cart | NVIDIA AI Podcast Ep. 302
EscuchadoInstacart 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. 🔬Topics covered: How Caper Carts use NVIDIA Jetson and sensor fusion to identify items in real time Why edge AI matters: hundreds-of-milliseconds response vs. seconds in the cloud Double-digit sales lift from personalized in-cart recommendations Building a grocery foundation model from 1.6B orders and live in-store data AI agents for store ops: proactive out-of-stock alerts and CPG shelf optimization Chapters:…
How Mistral Is Building Frontier AI for the Enterprise | NVIDIA AI Podcast Ep. 301
EscuchadoOpen-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. 🔬Topics covered: How open models and weights accelerate research Mistral Forge: bringing enterprise-grade model customization to production The Nemotron Coalition—what Mistral and NVIDIA are building together 2.5x training gains on GB200s for large sparse mixture-of-experts models Why AI agent permissions—especially write access—is important to solve Chapters: 00:00 – Introduction and Mistral’s origin story 04:05 – The case for open weights and why the community…
Everyone Can Build a Robot: Open Source Embodied AI With Seeed Studio | NVIDIA AI Podcast Ep. 300
EscuchadoSeeed 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. 🔬Topics covered: Why open source is the fastest path to accessible robotics How the $200 SOR arm (with Hugging Face) lowers the barrier to embodied AI Training robot arms like a dog: from months of coding to intuitive hand‑guided learning OpenClaw on Jetson: turning natural‑language commands into robot skills Using NVIDIA Isaac Sim and digital twins to bridge simulation and real‑world deployment Building modular robot parts (heads, arms, wheels) instead of monolithic humanoids Chapters: 00:00 – Welcome and introductions 02:00…
Inside AI Tokenomics: How to Profitably Turn Tokens Into Business Value | NVIDIA AI Podcast Ep. 299
EscuchadoAs 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. 🔬Topics covered: The four pillars of tokenomics: utility, supply, demand, and monetization Why cost per token beats FLOPS per dollar as an infrastructure metric NVIDIA Blackwell vs. Hopper: 50x more tokens per watt, 35x lower token cost How extreme co-design turns spec-sheet numbers into real-world output Jevons paradox: why lower token cost always drives more GPU demand, not less The four business models for turning tokens into revenue Chapters: 00:00 – Introduction and the four pillars of tokenomics 02:09 – Token value: intelligence, interactivity, and…
Snap’s Secret to Processing 10 Petabytes a Day: GPU-Accelerated Spark | NVIDIA AI Podcast Ep. 298
EscuchadoSnap 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. Prudhvi Vatala, head of engineering platforms at Snap, joins the NVIDIA AI Podcast to break down how he and his team completely modernized data infrastructure for a social platform serving nearly a billion monthly active users—using NVIDIA cuDF plugin (formerly referred to as NVIDIA RAPIDS plugin) for Apache Spark on Google Kubernetes Engine, with zero application code changes. 🔬Topics covered: How Snap runs A/B tests at planetary scale using rigorous statistical methods like heterogeneous treatment effect detection and variance reduction Why Snap reuses idle inference GPUs between 1–5 a.m. for batch data processing—and how it built a Kubernetes-based platform to do it How NVIDIA cuDF delivered 3x+ speedups on join-heavy Spark jobs with no code…