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how do you justify the compute investment for something like nemotron ? especially if all the labs are willing to pay for those same GPU clusters for inference or training runs?


Nemotron has two reasons to exist, both of which are strategic to NVIDIA.

1. Help NVIDIA design future systems for AI by more deeply understanding what it takes to build AI.

2. Keep the AI ecosystem strong and diverse throughout the world by providing AI infrastructure that many companies can innovate on.

This is not a science project, nor is it for the joy of giving something away. Both of these reasons are core to NVIDIA.


Does Nvidia maintain it's own compute hardware expressly for model training? Otherwise, I'm not sure how you keep up with the SOTA model techniques.


Yes




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