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How World Foundation Models Will Advance Physical AI With NVIDIA’s Ming-Yu Liu - Ep. 240

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Content provided by The AI Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The AI Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

As AI continues to evolve rapidly, it is becoming more important to create models that can effectively simulate and predict outcomes in real-world environments. World foundation models are powerful neural networks that can simulate physical environments, enabling teams to enhance AI workflows and development. Ming-Yu Liu, vice president of research at NVIDIA and an IEEE Fellow, joined the NVIDIA AI Podcast to talk about world foundation models and how it will impact various industries. https://blogs.nvidia.com/blog/world-foundation-models-advance-physical-ai/ https://www.nvidia.com/cosmos/

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271 episodes

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Manage episode 459836659 series 1413935
Content provided by The AI Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The AI Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

As AI continues to evolve rapidly, it is becoming more important to create models that can effectively simulate and predict outcomes in real-world environments. World foundation models are powerful neural networks that can simulate physical environments, enabling teams to enhance AI workflows and development. Ming-Yu Liu, vice president of research at NVIDIA and an IEEE Fellow, joined the NVIDIA AI Podcast to talk about world foundation models and how it will impact various industries. https://blogs.nvidia.com/blog/world-foundation-models-advance-physical-ai/ https://www.nvidia.com/cosmos/

  continue reading

271 episodes

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