Safe autonomous vehicles require massive amounts of diverse training data to address edge cases, but real-world data is limited; developers use NVIDIA Omniverse and Cosmos to reconstruct the real world and generate realistic synthetic training data, which brings diversity to AV models and enables them to perceive their environment, predict future outcomes, and generate motion plans.
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AI Training: NVIDIA Omniverse & Cosmos for AV Data #NVIDIAAñadido:
It starts with training.
Safe AVs need massive amounts of diverse data to be able to address edge cases.
But real-world data is limited.
Developers use NVIDIA Omniverse and Cosmos to reconstruct [music] the real world and generate realistic synthetic training data to bring diversity to the AV model.
The model can perceive and reason about its environment, predict future outcomes, and generate a motion plan.
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