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NVIDIA Cosmos Reason 2: Advancing Physical AI with Enhanced Reasoning Capabilities

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Introduction to NVIDIA Cosmos Reason 2 NVIDIA Cosmos Reason 2 is a new development in artificial intelligence tools designed to enhance physical AI systems. It aims to bring advanced reasoning abilities to AI that interacts with the physical world. This advancement is expected to improve how AI understands and reacts to complex environments. Understanding Physical AI Physical AI refers to artificial intelligence systems that operate in or interact with real-world physical spaces. These systems require not only sensory input but also the ability to make decisions based on physical laws and real-time data. Examples include robotics, autonomous vehicles, and simulation environments. Role of Advanced Reasoning in AI Tools Reasoning in AI involves the ability to process information logically, draw conclusions, and make decisions. Advanced reasoning enables AI tools to interpret complex scenarios, predict outcomes, and adapt to new situations. For physical AI, this means better ha...

Key Advances in AI Models, Agents, and Infrastructure with NVIDIA in 2025

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Introduction to 2025 AI Developments In 2025, the field of artificial intelligence is experiencing notable advances driven by NVIDIA technologies. Researchers and developers are pushing the boundaries of AI models, agents, and infrastructure. These developments influence how intelligent systems are created, trained, and applied across various domains. Enhancements in Data Center Power and Compute Design Data centers are central to AI progress. This year, improvements in power efficiency and compute design have allowed for more powerful AI training and deployment platforms. These enhancements enable faster processing and support larger AI models, which are essential for complex tasks requiring significant computational resources. Evolution of AI Infrastructure AI infrastructure has become more sophisticated, supporting scalable and flexible AI workflows. New tools and frameworks focus on optimizing resource usage and simplifying model training. This infrastructure supports a ...