4 ms·
The estimate in the article pins most of the cost on inference, not training, so diurnal patterns are unfortunately not as useful here. > While training ChatGP
by vitus 4y ago
The estimate in the article pins most of the cost on inference, not training, so diurnal patterns are unfortunately not as useful here.
> While training ChatGPT's large language models likely costs tens of millions of dollars, operational expenses, or inference costs, "far exceed training costs when deploying a model at any reasonable scale," Patel and Afzal Ahmad, another analyst at SemiAnalysis, told Forbes. "In fact, the costs to inference ChatGPT exceed the training costs on a weekly basis," they said.
- zamnos 4y agoWhy wouldn't inference follow diurnal patterns?
- reaperman 4y agoAgreed. That seems backwards. Training would not follow circadian rhythms, inference would.
- vitus 4y agoI should clarify: training is not latency sensitive, so you can run your workloads at off-peak hours when people are asleep. Inference means you need to run your workloads at peak when people are using your service. (Looking back, I'm happy that I was careful in my wording in that I didn't say diurnal cycles aren't relevant, just that they aren't as useful in this case) That said, I suppose I misread the specific suggestion about spinning down servers off-peak and was thinking more about spot pricing at peak vs trough.