Nvidia has the best hardware and software for deeplearning, but current use for it, and this huge demand was driven mostly about LLMs. The workload done by LLM

Nvidia has the best hardware and software for deeplearning, but current use for it, and this huge demand was driven mostly about LLMs. The workload done by LLMs can mostly be done by different hardware, that are more ASIC-like and efficient, see Grok for example. If there aren't enough deeplearning uses for Nvidia hardware, meanwhile the big techs might not recognize on its balance sheet, its ability to generate money down the road will be much smaller. I'd be willing to bet that in 10 years, H100s will be worth 0. It's a huge writedown. I'm sure we'll do much more deep learning down the road, but the demand recently for this hardware has been too big, mostly because of hype, this will definitely have an impact on depreciation once the hypes fade off. Even Meta, when they figure out they can do their own custom hardware to do their Instagram recommendations, they will talk directly to TSMC. The CAPEX on this is huge, so are the savings in case they find out a way to use custom hardware. Google went through this route because the found out themselves that it's worth having their own hardware as they do a lot of AI. Given this, I believe that it's a huge risk to have H100s at the moment, so does Blackwell. It's a risky asset.