But it is in their interest that their customers can use their models as a base for post-training and LoRAs.
replyThey don’t necessarily need their own models for that
replyThey have models for that. That's what the Nemotron series is. Not just open weights but open training data too and full tutorials on how to use them to fine tune or train your own models.
replyThey exist to keep people using and advancing the tools on their hardware.
Why not? Commoditize your complement, and all that.
replyAnd if they get too good, they risk harming or otherwise killing their golden geese (their customers), who they are heavily invested in.
replyHow? Imagine an open-weight model comes out that is somehow better than proprietary solutions. Now the marginal cost for the consumer is just the cost of renting the inference hardware, without having to pay the overhead of the owner of a proprietary model. And because it is cheaper, more customers want to use it, and Nvidia will sell the providers the inference hardware that they need.
reply1. No open ai and anthropic means no buying gpus to train. Now nvidia spends money on hardware training their own models. Opportunity cost plus expense.
reply2. Any open models created from this will not necessarily need their silicon, see apple mlx.
1. I don’t think that’s a very strong argument. OpenAI and Anthropic don’t buy the vast majority of GPUs they use they rent capacity.
replyNvidia could just the same rent those GPUs out for inference and actually have way better margins than they do right now. Antitrust and putting all your eggs in one basket are why they don’t, similar to TSMC.
2. Neither do AI labs. See Anthropic buying TPUs, deploying with AMD. OpenAI on Maia, Cerebras, their own wafers.