3 ms·

inference compute is vastly different versus training, also it has to stay hot in vram which probably takes up most of it. There is limited use for THAT much co

inference compute is vastly different versus training, also it has to stay hot in vram which probably takes up most of it. There is limited use for THAT much compute as well, they are running things like claude code compiler and even then they're scratching the surface of the amount of compute they have. Training currently requires nvidia's latest and greatest for the best models (they also use google TPU's now which are also technically the latest and greatest? However, they're more of a dual purpose than anything afaik so that would be a correct assesment in that case) Inference can run on a hot potato if you really put your mind to it

eru 8mo ago
They can run any number of inference experiments. Like a lot of the alignment work they have going on. I am not saying this would be a great use of their compute, but idle is far from the only alternative. (Unless electricity is the binding constraint?)
- himata4113 8mo ago
  Electricity is charged whenever you use it or not, so very unlikely, but sure, they can find uses for it. Although they are not going to make that much money compared to claude code subscriptions.
  - eru 8mo ago
    > Electricity is charged whenever you use it or not, [...] Huh, what? You know you can turn off unused equipment, and at least my nvidia GPU can use more or less Watts even when turned on? Or does Anthropic have a flatline deal for electricity and cooling?
    - himata4113 8mo ago
      in datacenters power allocation is a fixed cost.
      - eru 8mo ago
        If you are big enough, you can and will negotiate.
        himata4113 8mo ago
        the datacenter has a fixed cost for power, industrial power is not consumer power especially at large scale. Scale really kicks in if you own your power plant (ex: hydro, wind, solar).
        eru 8mo ago
        Data centres are more complicated than that. For an example, even if you have a fixed power budget at the data centre level, you still have opportunity costs: if you turn some unused GPUs off, you can run other things hotter.
rafaelmn 8mo ago
I think I've heard multiple time that a large % of training compute for SoTA models is inference to generate training tokens, this is bound to happen with RL training

eru 8mo ago

They can run any number of inference experiments. Like a lot of the alignment work they have going on. I am not saying this would be a great use of their compute, but idle is far from the only alternative. (Unless electricity is the binding constraint?)

himata4113 8mo ago
Electricity is charged whenever you use it or not, so very unlikely, but sure, they can find uses for it. Although they are not going to make that much money compared to claude code subscriptions.
- eru 8mo ago
  > Electricity is charged whenever you use it or not, [...] Huh, what? You know you can turn off unused equipment, and at least my nvidia GPU can use more or less Watts even when turned on? Or does Anthropic have a flatline deal for electricity and cooling?
  - himata4113 8mo ago
    in datacenters power allocation is a fixed cost.
    - eru 8mo ago
      If you are big enough, you can and will negotiate.
      - himata4113 8mo ago
        the datacenter has a fixed cost for power, industrial power is not consumer power especially at large scale. Scale really kicks in if you own your power plant (ex: hydro, wind, solar).
        eru 8mo ago
        Data centres are more complicated than that. For an example, even if you have a fixed power budget at the data centre level, you still have opportunity costs: if you turn some unused GPUs off, you can run other things hotter.

rafaelmn 8mo ago

I think I've heard multiple time that a large % of training compute for SoTA models is inference to generate training tokens, this is bound to happen with RL training