There are plenty of cool advancements in reducing inference cold start when I was meeting with folks in person at FOSDEM this year. However, I still struggle to understand: why would folks care about this?

Major AI Labs all have secured their own compute in the form of hardware, data center, and power generation. That means their resource pool is fixed, and they can do all sorts of tricks to pre-load, pre-allocate, etc... to improve on inference latency.

Cold start is usually a solution for "cloud" environment when your pool is flexible, and you only pay for what you use. Its effectiveness lowered in bare-metal settings as folks do not care about scaling up and down as much.

So my question is: who is this for? AWS and GCP running Anthropic models?