# How Dassault Systèmes Is Building AI That Understands Physics - Ep. 296 Page: https://stenobird.com/podcast/nvidia-ai-podcast/how-dassault-syst-mes-is-building-ai-that-understands-physics-ep-296 Text version: https://stenobird.com/podcast/nvidia-ai-podcast/how-dassault-syst-mes-is-building-ai-that-understands-physics-ep-296.md Podcast: [NVIDIA AI Podcast](https://stenobird.com/podcast/nvidia-ai-podcast) Published: 2026-04-29T15:45:00+00:00 Episode link: https://cohst.app/pdcst/9V4R8T/traffic.megaphone.fm/NVC4106910030.mp3?updated=1777908733 Audio file: https://cohst.app/pdcst/9V4R8T/traffic.megaphone.fm/NVC4106910030.mp3?updated=1777908733 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/nvidia-ai-podcast/episodes/how-dassault-syst-mes-is-building-ai-that-understands-physics-ep-296 Duration seconds: 1384 ## Resource 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. ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/nvidia-ai-podcast/episodes/how-dassault-syst-mes-is-building-ai-that-understands-physics-ep-296/transcription-requests` — Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/nvidia-ai-podcast/how-dassault-syst-mes-is-building-ai-that-understands-physics-ep-296.md` — Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.