How Open Models Are Driving AI Research
TL;DR
NVIDIA uses ICML 2026 to make a clear point: open models and open AI infrastructure have become part of daily AI research. The company says it had 74 accepted papers. According to NVIDIA, about 2,000 accepted ICML papers cite its GPUs, while 145 cite Nemotron, including open models and datasets used as research foundations. Beyond Nemotron, NVIDIA highlights Cosmos, Isaac GR00T and BioNeMo across robotics, autonomous vehicles, life sciences, video, agents and synthetic data generation.
Nauti's Take
Treat the numbers as NVIDIA’s own framing and verify first which parts are actually open, reproducible, and usable under their licenses. For small teams, the practical test is whether a paper can be rebuilt with the model, data recipe, and inference path intact, or whether the workflow still depends on proprietary GPU and tooling choices.
Briefingshow
Open models lower the barrier for research because teams can test, adapt and compare systems without pretraining everything from scratch. The bigger point is the stack: whoever ships open datasets, training recipes and inference tooling gets more influence over which experiments become fast and practical enough to run.
Video
Sources
