That would imply that the current AI cycle would be able to persist at its current levels of frothiness indefinitely: In the in-between lull periods, these GPU farms would be seen as something to sell off. This doesn't even take into account the eventual depreciation of the GPUs in question, as better GPUs/accelerators come into the market.

Most companies have an AWS account that they can throw on more money at for 'AI research & implementation'. With such an account existing in the first place, along with said price depreciations, the company in question would have to be certain that they'll use said GPUs all the time to make up for the upfront costs they'll be putting up with.

Often you are better off running certain workloads on lesser GPUs. But this requires certain tricky compiler-level optimizations. For example, can run certain LLM inference with comparable latency on cheaper A40s vs running on A100s. Could also run on 3090s (sometimes even faster). This helps with operating costs but may also resolve availability constraints.