Investing in AI infrastructure seems very risky to me. With how short of a lifecycle computing hardware generally has, does it make sense to blow billions on hardware that will need to be replaced in a few years? AI companies have been burning billions on hardware. Will the costs of that hardware be covered by profits before the hardware lifecycle is up? That's a big gamble.
We used to talk about AI as having no moat (easy for other players to accomplish similar AI achievements). China has made that clear. Some open weight LLMs are fine and can run on laptops. It seems the new moat is model parameter size and VRAM requirements. I would bet on innovation in hardware or disruptive algorithms changing that game so better LLMs can run on more personal computers. Remember how bitcoin miners all used GPUs then ASICs came along and made that no longer profitable?
There are many ways the AI industry can be disrupted which makes it that much more volatile.
We used to talk about AI as having no moat (easy for other players to accomplish similar AI achievements). China has made that clear. Some open weight LLMs are fine and can run on laptops. It seems the new moat is model parameter size and VRAM requirements. I would bet on innovation in hardware or disruptive algorithms changing that game so better LLMs can run on more personal computers. Remember how bitcoin miners all used GPUs then ASICs came along and made that no longer profitable?
There are many ways the AI industry can be disrupted which makes it that much more volatile.