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To help developers rapidly build world models, which help physical AI systems understand and simulate the real world, NVIDIA has expanded the Cosmos platform with new training tools, simulation checkpoints and Cosmos Data Factory…
Companies around the world are building on the NVIDIA DSX AI Factory Platform to plan, simulate and run the grid and the AI factory as one system, from the substation to the rack. Their…
European retailers are using open models and physical intelligence across use cases — from a commerce platform cutting inference costs by 90% to to a fulfillment center where collaboration of different robotic fleets is…
Weather forecasts shape more than daily plans; timely weather information is crucial for energy producers, insurers and transport operators to plan around changing conditions. A global forecast can show a storm taking shape, but…
Governments need modern solutions to serve the public while keeping sensitive information under their control. Open models provide a path forward, letting governments evaluate them, adapt them to local languages and public services, run…
Perplexity and NVIDIA introduced JOLT, a post-training method that trains one model as both teacher and student. On MATH it matched GRPO’s accuracy with 6.5x fewer processed training tokens. The post Perplexity and NVIDIA…
Explore a comprehensive coding guide benchmarking Cactus Compute's 16.9 MB speech model against Whisper base. Learn about word error rates, CPU speed, streaming latency, and speech-to-tool integration. The post A Coding Guide to Cactus…
arXiv:2610.28909v1 Announce Type: new Abstract: Deep research systems iteratively plan, gather evidence, synthesize, and revise, making end-to-end latency a key bottleneck for interactive use. Almost all production systems are built on autoregressive (AR) language…
arXiv:2604.18936v2 Announce Type: replace-cross Abstract: Despite the growing application of large language models (LLMs) to theoretical physics, there has been little academic exploration of how domain-specific physics reasoning ability develops during training. To investigate…
arXiv:2610.28905v1 Announce Type: new Abstract: Diffusion language models form answers through a sequence of revisable continuous states, but multi-agent systems usually discard those states and make agents communicate only after decoding text. We ask…
arXiv:2506.16590v2 Announce Type: replace-cross Abstract: Reinforcement learning remains sample inefficient, particularly when agents must adapt over time to related but distinct tasks, as in continual learning settings. Efficiency can be improved by transferring knowledge…
arXiv:2610.28891v1 Announce Type: new Abstract: Many social evaluations for multiagent systems study behaviors as they emerge from environments instead of systematically intervening in the environment to elicit such behaviors. We introduce Fig (Finding Interactions…