this post was submitted on 29 Jan 2025
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[–] [email protected] 20 points 4 months ago* (last edited 4 months ago) (5 children)

In one story they're using PTX on Nvidia H800s. In another they're on Huawei chips.

Which is it? Are we all just hypothesising?

[–] [email protected] 26 points 4 months ago* (last edited 4 months ago) (4 children)

Not the best on AI/LLM terms, but I assume that training the models was done on Nvidia, while inference (using the model/getting the data from the model) is done on Huawei chips

To add: Training the model is a huge single-cost expense, while inference is a continuous expense.

[–] [email protected] 5 points 4 months ago (3 children)

Wait, so after you train, you don't need all those fancy Nvidia chips?

They should make one place where there is an overabundance of geo thermal energy and train all models there...

[–] [email protected] 7 points 4 months ago

Yes, so R&D and finalizing the model weight is done on NVIDIA GPUs (I guess you need an excessive amount of VRAM).

Inference is probably gonna be offloaded to consumers in the end where the NPU is taking care of the inference cost (See Apple, Qualcomm etc)

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