NVIDIA's Cosmos platform offers open-weight world models for developers and businesses.
Physical AI builders can leverage these pre-built models to tackle challenges in robotics and self-driving cars.
Choose between autoregressive (AR) and diffusion models based on project needs.
AR models, similar to GPT, offer speed and easy integration but may compromise accuracy due to tokenization.
Diffusion models generate coherent tokens, resulting in better quality but may be slower.
Consider speed versus accuracy when selecting a model.
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Transcript
Episode notes
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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