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Doesn't this literally not matter? We know that something Llama is being trained in about 3 months on Meta's current resources from their current datasets. If
by XorNot 2y ago
Doesn't this literally not matter? We know that something Llama is being trained in about 3 months on Meta's current resources from their current datasets.
If they had less GPU power available, it would take longer but not dramatically so. Building a "more powerful AI cluster" doesn't give you a more powerful AI currently. In fact none of the Transformer architecture's seem to, and their instantiations seem to all be targeted towards "single H100 executions" for inference.
So this really does seem like nothing but hype: buying a lot of commercially available GPUs isn't accomplishing anything.
- latentsea 2y agoRight, but that means Meta can train 4 models a year. So, 4 opportunities for feedback. They however, need to release those to the public in order to get feedback on the limitations of the model, so that might limit it to training and releasing 2 models a year. If you had more GPUs you could iterate faster...