Explore how the latest technologies are shaping our world, from groundbreaking discoveries to transformative sustainability efforts. The NVIDIA AI Podcast shines a light on the stories and solutions behind the most innovative changes, helping to inspire and educate listeners. More information: https://ai-podcast.nvidia.com/
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:
00:00 – Introduction and the Connected Store vision
04:00 – Caper Cart: NVIDIA Jetson, sensor fusion, and edge AI
08:06 – How basket recognition and recommendations work
15:53 – Double-digit sales lift and what shoppers actually want
22:25 – Store ops, employees, and the real-time data flywheel
28:26 – AI agents, the grocery foundation model, and what's next
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.
🔬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 builds faster
09:34 – Mistral Forge: enterprise model customization in production
14:21 – What enterprise customers actually want from AI right now
18:46 – The hardest open problem: AI agent permissions and write access
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.
🔬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 – From open hardware modules to robotics and edge AI
05:00 – Why open source drives adoption and trust in robotics
09:00 – The $200 SOR arm: open source with Hugging Face
12:00 – Training robot arms like a dog: intuitive, hand‑guided learning
15:00 – OpenClaw on Jetson: text‑to‑robot control
20:00 – Isaac Sim and digital twins: bridging simulation and reality
27:00 – Modular design: heads, arms, wheels instead of humanoids
32:00 – Everyone can participate in physical AI: closing thoughts
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.
🔬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 use case mapping
06:32 – Estimating token demand: users, reasoning, and agentic multipliers
10:00 – Token supply and why cost per token is the right infrastructure metric
13:12 – NVIDIA Blackwell vs. Hopper: 50x more tokens, 35x lower cost
14:52 – Extreme co-design for lowest token cost and the NVIDIA Vera Rubin platform
21:10 – How software multiplies hardware performance (8x gains in six months)
23:56 – Token monetization: pricing and business models
26:52 – Jevons paradox and the future of GPU demand
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.
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 rewrites
The full business impact: 76% cost reduction, 62% fewer cores, 80% less memory, 120 TB of spill eliminated
How a three-way partnership between Snap, NVIDIA, and Google Cloud made it possible in just 8–9 months
Chapters:
0:00 Introduction and Snap overview
3:35 What is Snap’s experimentation platform?
4:05 Why experimentation, safety, and privacy are core at Snap
4:52 How A/B testing works at billion-user scale
8:14 Discovering NVIDIA cuDF plugin
9:06 Benchmarking results: join, union, and aggregation jobs
12:00 Reusing idle GPUs overnight via GKE
13:24 Building a bottom-up GPU data platform at Snap
17:48 Results: 76% cost reduction and partnership impact
20:56 Snap’s evolution and what’s next
Learn more:
NVIDIA cuDF: https://developer.nvidia.com/topics/ai/data-science/cuda-x-data-science-libraries/cudf#accel-apache
LangChain has surpassed 1 billion downloads—and the framework that started as a weekend project is now the harness powering the next generation of production-grade AI agents. In this episode, Harrison Chase, co-founder & CEO of LangChain, breaks down the architecture behind deep agents, explains why systems like Claude Code, Manus, and Deep Research all share the same foundational pattern, and lays out what it actually takes to deploy autonomous agents responsibly in the enterprise.
🔬Topics covered:
What is a "deep agent," and why does architecture matter more than ever?
How enterprises are (and aren't) embracing autonomous agents
LangSmith: observability, tracing, and evaluation-driven development
Mixing frontier and open models (NVIDIA Nemotron) in multi-agent systems
What's next: async subagents, proactive/always-on agents, agent memory, and agent identity
Chapters:
00:00 – LangChain origin story and the deep agent architecture
01:46 – What is a deep agent?
03:31 – Enterprise trust: risk, autonomy, and iteration
04:38 – LangSmith: observability and evaluation-driven development
13:30 – Frontier vs. open models and the Nemotron Coalition
18:10 – What's next: async subagents, agent memory, and agent identity
Generative AI can predict whether a plane takes off—but does it know why? Nicolas Cerisier, VP of 3DEXPERIENCE Platform R&D at Dassault Systèmes, explains how industrial world models go beyond pattern recognition to embed the actual laws of physics, chemistry, and engineering. In this episode of the NVIDIA AI Podcast, he also breaks down Dassault's three virtual companions (AURA, LEO, and MARIE), their 25-year collaboration with NVIDIA, and a stunning real-world use case: helping NIAR rebuild aircraft designs part by part, using AI.
What if one AI brain could run every robot on the planet—a humanoid, a warehouse arm, and a dog-like inspection bot—all at once?
That's not a thought experiment. That's what Skild AI is building right now.
Deepak Pathak (CEO and Co-Founder) and Abhinav Gupta (President and Co-Founder) of Skild AI join the pod to break down Skild Brain—a universal, general-purpose AI model designed to power robots of any form factor, tackling any task, from a single shared intelligence.
What happens when you combine AI with quantum computing? NVIDIA's Nic Harrigan joins the AI Podcast to break down the state of quantum, explain why error correction is the pivotal challenge, and reveal how NVIDIA Ising—the world's first open AI model family for quantum—is changing the game.
🔗 Resources mentioned:
► Read our NVIDIA Ising announcement
► Learn more about NVIDIA Ising
► Learn more about NVIDIA Quantum Computing
Chapters:
0:00 Intro
0:55 What is quantum computing?
4:00 Qubits, noise, and error correction
5:26 How AI helps quantum error correction
10:57 Applications: drug discovery and materials
15:33 NVIDIA Ising announcement
20:35 Scaling quantum hardware
27:31 Algorithm development with generative AI
Enterprises are moving from AI pilots to full‑scale AI factories that turn data into trusted digital intelligence. Red Hat CTO Chris Wright and NVIDIA’s Justin Boitano unpack the "five‑layer cake" AI factory stack, from accelerated hardware and hybrid cloud infrastructure to models, agents, and production‑grade governance.
AI is reshaping electricity demand. What does increased demand, and the shape of that demand, mean for the electric grid? Ben Sooter, Director of R&D at EPRI joins the podcast to explain why most of an AI model’s lifetime energy use comes from inference rather than training, and how micro data centers located near underutilized substations can help deliver low‑latency AI services while strengthening grid resilience.
Alibaba.com president Kuo Zhang discusses how AI agents like Accio are reshaping global trade. He shares insights on automating complex B2B sourcing, compressing weeks of work into minutes, lowering barriers for solo entrepreneurs and SMEs, and what AI-native commerce will mean for the next decade.
Transit agencies are using AI and edge computing to keep bus lanes and bus stops clear — boosting on‑time performance, accessibility, and safety for riders. AC Transit CTO Ahsan Baig and Hayden AI CEO Marty Beard explain how bus‑mounted cameras and NVIDIA-powered edge AI automatically detect vehicles blocking bus lanes and stops, protect rider privacy by design, and are helping change driver behavior in the San Francisco Bay Area.
Explore the next wave of AI innovation at NVIDIA GTC. Learn more.
How can AV teams stop drowning in petabytes of data and actually ship safer autonomy faster? Fortellix’s Rohan Bhasin and Voxel51’s Dan Gural explain how neural reconstruction, scenario-driven data curation, and NVIDIA-powered pipelines turn ordinary drive logs into high-fidelity simulations that close the last-mile gap in AV performance.
GTC is the premier global AI conference. Learn more at nvidia.com/gtc
How are real‑time 4K holograms that look, sound, and respond like people changing fan engagement? Jia Li, co‑founder, president, and chief AI officer of LiveX AI, shares how human‑like AI agents bridge the digital and physical worlds—from greeting travelers at airports to guiding fans through fan zones and supporting wayfinding at major sports events.
Join the world's premier AI conference: NVIDIA GTC
GiveDirectly president and CEO Nick Allardice explains how his team uses AI, mobile money, and satellite imagery to send cash directly to people living in poverty and crisis, often within days of a disaster. He describes how AI-powered tools help forecast floods in places like Nigeria, Bangladesh, and Mozambique, and how “anticipatory action” can get money to families before disaster strikes.
Learn more about the AI Podcast: ai-podcast.nvidia.com
Jason “Retailgeek” Goldberg, Chief Commerce Strategy Officer at Publicis Groupe, discusses how AI is optimizes retail operations and is rewriting the consumer shopping experience. Learn why AI acceleration is able to reimagine the retail pipeline — from supply chain to personalized robot shoppers that could streamline the flow of goods starting at the warehouse and ending on your doorstep.
More AI Podcast: ai-podcast.nvidia.com
Brandon Hootman, Vice President of Data and Artificial Intelligence at Caterpillar, joins the AI Podcast to discuss how the company uses NVIDIA’s AI Factory, Omniverse digital twins, and edge AI to streamline manufacturing, improve safety, and bring AI copilots into heavy equipment on real-world job sites.
Browse the full AI Podcast catalog
Discover how mixture‑of‑experts (MoE) architecture is enabling smarter AI models without a proportional increase in the required compute and cost. Using vivid analogies and real-world examples, NVIDIA’s Ian Buck breaks down MoE models, their hidden complexities, and why extreme co-design across compute, networking, and software is essential to realizing their full potential. Learn more: https://blogs.nvidia.com/blog/mixture-of-experts-frontier-models/
Empromptu CEO Shanea Leven shares how her company helps people without coding experience build meaningful, production-ready AI applications — fast and accurately. Powered by NVIDIA CUDA, Empromptu’s “AI that builds AI” platform is making cutting-edge technology accessible to all, enabling creators to turn bold ideas into real-world impact.
Listen to the full show archive at ai-podcast.nvidia.com
The year in AI began with agents and brought us creative superpowers, robots on farms and in operating rooms, and so much more. Look back on AI in 2025 through the voices of the people who created it in this recap episode.
Listen to every episode: ai-podcast.nvidia.com
Bringing GPUs to your data is a game changer for the modern enterprise. Jacob Liberman, Director of Enterprise Product Management at NVIDIA, details the AI Data Platform, a GPU-accelerated storage platform built for AI.
Browse the entire AI Podcast catalog: ai-podcast.nvidia.com
Mayor Matt Mahan and NVIDIA’s Jumbi Edulbehram reveal how AI is making San Jose smarter—optimizing transit, translating meetings in real time, upskilling city staff, and powering pioneering civic programs. Learn how AI is helping streamline services and create a more responsive city for everyone.
Browse the entire AI Podcast catalog: ai-podcast.nvidia.com
Coverage from keynote pregame show, GTC Live Washington D.C.
Chapter 5: AI for Robotics and Manufacturing
The boundary between digital intelligence and physical action is disappearing. Industry pioneers show how robotics and automation are turning insight into production.
Catch up with GTC DC on-demand: https://www.nvidia.com/en-us/on-demand/
Coverage from keynote pregame show, GTC Live Washington D.C.
Chapter 4: AI for Science
In laboratories and research centers, AI is becoming a core instrument of discovery. Scientists and technologists explore how computation is accelerating progress across fields.
Catch up with GTC DC on-demand: https://www.nvidia.com/en-us/on-demand/
Coverage from keynote pregame show, GTC Live Washington D.C.
Chapter 3: AI Infrastructure Ecosystem
Behind every breakthrough is an unseen network of data centers, power systems, and partners. Leaders across energy and infrastructure discuss how they’re building the backbone of the AI economy.
Catch up with GTC DC on-demand: https://www.nvidia.com/en-us/on-demand/
Coverage from keynote pregame show, GTC Live Washington D.C.
Chapter 2: Agentic AI for Every Industry
Intelligent systems are beginning to plan, reason, and act, reshaping how industries work. Builders share how these capabilities are moving from research into real-world impact.
Catch up with GTC DC on-demand: https://www.nvidia.com/en-us/on-demand/
Coverage from keynote pregame show, GTC Live Washington D.C.
Chapter 1: State of AI Innovation
A look at how new ideas, models, and open collaboration are shaping the direction of AI. Investors and founders trace where the next wave of durable innovation is coming from.
Catch up with GTC DC on-demand: https://www.nvidia.com/en-us/on-demand/
Dr. Seher Awan, president of Mission College, shares her inspiring journey from first-generation college student to higher education leader in the heart of Silicon Valley. Discover how Mission College is embracing AI to break barriers, close equity gaps, and empower underrepresented communities through accessible education and innovative student support.
Browse the AI Podcast catalog: ai-podcast.nvidia.com
Learn how NVIDIA's Nemotron family of open source models is redefining accelerated computing. NVIDIA’s Bryan Catanzaro and Jonathan Cohen discuss the breakthroughs in efficiency, openness, and collaboration — sharing how Nemotron empowers developers and enterprises to innovate, customize, and trust AI for every industry.
Browse the full AI Podcast archive: ai-podcast.nvidia.com
