… Putting AI Through Its Paces: Policy Training Once the teaching materials — the datasets — are gathered, it’s time for the robot to learn new tasks. This starts with the robot brain, powered by reasoning VLAs such as GR00T. The VLA can be post-trained using data specific to its intended task. …
… NVIDIA is also expanding the research infrastructure behind physical AI with datasets for training, fine-tuning and evaluation. …
… NVIDIA is also releasing open-source datasets, training resources and blueprints to developers, including the dataset and training code for the Llama Embed Nemotron 8B model, featured on the MMTEB leaderboard . …
… The company is open sourcing its Sarvam-3 series of text and multimodal large language model variants, trained for 22 Indic languages, English math and code. Sarvam is using NeMo Curator to construct high-quality multilingual training data while adopting a subset of NVIDIA Nemotron datasets. …
… NVIDIA’s ability to support diverse AI workloads helps data centers use resources more efficiently. That’s why AI labs such as Black Forest Labs, Cohere, Mistral, OpenAI, Reflection and Thinking Machines Lab and are all training on the NVIDIA Blackwell platform. …
… For every new embodiment, the process typically needs to be repeated — requiring new training data, fine-tuning and validation. This constraint means most robotics companies pick a gripper, train for it and stick with it. …
… Think of it as replacing a single-lane road spanning a town with a cleverly laid-out street grid system paired with an on-the-fly traffic app, enabling drivers to reroute around slowdowns and road closures. “Deploying MRC in the Blackwell generation was very successful and was made possible by a st… …
… Toyota Research Institute customizes Cosmos WFMs for their own world model to achieve state-of-the-art results across dynamic view synthesis, state-of-the-art teleoperation data augmentation and navigation world models. https://blogs.nvidia.com/wp-content/uploads/2026/04/nvidia cosmos accelerates a… …
… In MLPerf Training v5.1 — the latest round in a long-running series of industry-standard tests of AI training performance — NVIDIA swept all seven tests, delivering the fastest time to train across large language models LLMs , image generation, recommender systems , computer vision and graph neural… …
… Powered by NVIDIA’s full AI stack — including NVIDIA Hopper GPUs , the NVIDIA cuDF library and NVIDIA Nemotron open models — running on Nebius cloud, a single foundation model outperforms strong task-specific models across domains like credit scoring, fraud detection and product recommendations whi… …