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Physical AI

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Faster Chips That Don't Melt — Anima Anandkumar & Benedikt Jenik, Accelerated Understanding Sep 4, 2026 · 27:02 Accelerated Understanding is building a foundation model for the physical world, applying LLM universality to physics. They achieve unprecedented scale with neural operators and self-improvement via physical laws.

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Serving World Models: Latency vs Throughput with NVIDIA Cosmos 3 Super on Nebius | Cosmos Labs Sep 23, 2026 · 57:46 Dive into serving World Models with NVIDIA Cosmos 3 Super. Learn the critical trade-offs between latency and throughput when benchmarking video generation on HGX B200 and H200 systems. When Will AI Make Me Scrambled Eggs? I Went To NVIDIA To Find Out. Sep 24, 2026 · 46:27 NVIDIA's World Models (Cosmos 3) are redefining physical AI by moving beyond text-based LLMs. They fuse world understanding, simulation, and action into a single model, enabling policy verification for robotics and self-driving cars in simulated environments. I Gave an AI a Body — Cyrus Clarke, MIT Media Lab Sep 24, 2026 · 20:48 Clarke details how he gave an OpenClaw agent a body—a 900-pin shape display—to explore embodiment. By developing a closed-loop gesture system, the AI learned a body language that responds faster than language models, making physical AI feel welcoming.

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Stanford EE292R AI and Data for Science | Autumn 2026 | From World Models to World Agents Oct 22, 2026 · 54:31 World models are defined as real-time, action-conditioned, causal video generators. They represent a shift from traditional simulators to data-driven generative approaches, using diffusion models to create photorealistic video conditioned on text, context, and actions. Robots That Predict the Future: Dyna-2 & Physical AI — Jason Ma, Dyna Robotics Oct 13, 2026 · 1:21:06 Dyna Robotics uses the Dyna-2 world action model, trained on 1M+ hours of video, to guide physical robots. By combining Diffusion Transformers with agentic harnesses, they achieve general-purpose automation for complex, real-world workflows. From World Models to Working Machines: Physical AI in the Real World Oct 7, 2026 · 29:42 Physical AI is moving from the lab to industrial sites. Success requires a closed-loop data flywheel, combining multimodal data, advanced simulation, and edge computing to solve the sim-to-real gap.

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