NVIDIA is the world's largest publisher of open AI models, with families spanning reasoning (Nemotron), physical AI and robotics (Cosmos, Isaac GR00T), autonomous vehicles (Alpamayo), drug discovery (BioNeMo), quantum computing (Ising), and climate forecasting (Earth-2). Bryan Catanzaro, VP of Applied Deep Learning Research, explains the key architectural choices: a hybrid Mamba+Transformer design that handles million-token contexts efficiently, mixture-of-experts layers, and 4-bit (NVFP4) pretraining co-designed with Blackwell GPUs. Post-training uses supervised fine-tuning followed by large-scale reinforcement learning across diverse environments. A unified foundation strategy—reusing backbones like Cosmos Reason across robotics and AV teams—lets a small team ship many models quickly. NVIDIA's open approach goes beyond releasing weights: it publishes training datasets, RL environments, and recipes. The business rationale is that open models grow the AI ecosystem, which in turn drives GPU demand, while also keeping NVIDIA's researchers honest about where AI is heading.
