Nvidia Becomes a Major Model Maker With Nemotron 3
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Nvidia Becomes a Major Model Maker With Nemotron 3
"Nvidia has made a fortune supplying chips to companies working on artificial intelligence, but today the chipmaker took a step toward becoming a more serious model maker itself by releasing a series of cutting-edge open models, along with data and tools to help engineers use them. The move, which comes at a moment when AI companies like OpenAI, Google, and Anthropic are developing increasingly capable chips of their own, could be a hedge against these firms veering away from Nvidia's technology over time."
"Open models are already a crucial part of the AI ecosystem with many researchers and startups using them to experiment, prototype, and build. While OpenAI and Google offer small open models, they do not update them as frequently as their rivals in China. For this reason and others, open models from Chinese companies are currently much more popular, according to data from Hugging Face, a hosting platform for open source projects."
"Nvidia's new Nemotron 3 models are among the best that can be downloaded, modified, and run on one's own hardware, according to benchmark scores shared by the company ahead of release. "Open innovation is the foundation of AI progress," CEO Jensen Huang said in a statement ahead of the news. "With Nemotron, we're transforming advanced AI into an open platform that gives developers the transparency and efficiency they need to build agentic systems at scale.""
Nvidia released Nemotron 3 open models together with the training data and developer tools to allow engineers to download, modify, and run models on their own hardware. The release positions open models as a strategic response to competing AI firms developing proprietary chips and aims to reduce long-term reliance on third-party hardware. The models feature a hybrid latent mixture-of-experts architecture optimized for building agentic systems and include libraries for reinforcement learning fine-tuning. Public release of data and customization tools increases transparency and targets faster adoption among researchers, startups, and developers.
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