As AI models evolve and adoption grows, enterprises must perform a delicate balancing act to achieve maximum value.
That’s because inference — the process of running data through a model to get an output — offers a different computational challenge than training a model.
Pretraining a model — the process of ingesting data, breaking it down into tokens and finding patterns — is essentially a one-time cost. But in inference, every prompt to a model generates tokens, each of…
Article Source
https://blogs.nvidia.com/blog/ai-inference-economics/