NVIDIA has recently accelerated the development of physical AI systems through World Foundation Models (WFMs). WFMs are powerful neural networks used to simulate and predict real-world environments. These models are used to generate detailed videos based on text, images, and video input data, and to predict how a scene will evolve1[2] (https://blogs.nvidia.com/blog/world-foundation-models-advance-physical-ai/) .
- <strong>Real-world environmental simulations</strong>: WFMs help physical AI systems operate safely and efficiently by simulating real-world environments. This is essential for robots and autonomous vehicles to interact with the physical environment1[4] (https://www.nvidia.com/en-us/glossary/world-models/) ).
- <strong>Create synthetic data</strong>: WFMs generate large-scale synthetic data to enhance training of AI models. This contributes to reducing the difficulty and cost of collecting real-world data1[3](https://research.aimultiple.com/world-foundation-model/).
- <strong>Testing in a virtual environment</strong>: WFMs provide a virtual 3D environment, enabling safe and efficient testing of physical AI systems, which is less costly and less risky than testing in a real world1[3] (https://research.aimultiple.com/world-foundation-model/) .
WFMs can be used in a variety of industries:
- <strong>Autonomous vehicles</strong>: WFMs simulate autonomous vehicles in a variety of traffic and weather conditions to ensure safe and efficient performance1[3] (https://research.aimultiple.com/world-foundation-model/) .
- <strong>Robots</strong>: WFMs help robots operate safely and efficiently in a variety of environments. This is essential for robots to perform complex tasks1[3] (https://research.aimultiple.com/world-foundation-model/) .
- <strong>Medicare</strong>: WFMs are used in the training of surgical robots to enable precise work [3] (https://research.aimultiple.com/world-foundation-model/) .
NVIDIA is offering WFMs open-source through the NVIDIA Cosmos platform, which helps developers easily build large-scale models and fine-tune them to specific needs1[3] (https://research.aimultiple.com/world-foundation-model/) .
WFMs will accelerate the development of physical AI systems and bring about innovative changes in various industries. This will help AI systems operate more safely and efficiently, and contribute to reducing the cost and risk of testing in real-world environments. NVIDIA plans to further accelerate the development of physical AI through WFMs. Source: https://blogs.nvidia.com/blog/world-foundation-models-advance-physical-ai/
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