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by LurkandComment 15 days ago
AI is cheap right now. Let's re-ask this question when it's priced to recover profit and ROI.
3 comments

I have the theory (not tested, subjective) that current economy prefers buying capital (broadly here defined as machine/tools) than having to pay workers salaries, even if both have the same level of competitivity

Capital expenditures are easy to calculate, and it's easy to help raising money. As the current economical system is based on debts, it works quite well: if a company knows that productivity output will raise by 15% over the next year if they spend X dollars, it's easy to get investments (investments firms themselves are relying heavily on private credits, which more and more is coming from bank too). With a system based on debts, they care less about the amount spent, than the yield generated.

With investing in people, it's harder to predict.

Industry does it by buying machines, now knowledge-based companies might do it with GPUs or tokens.

What’s built with all that VC money is already built though; I don’t foresee a future a few years out where we don’t have access to an open-source model roughly as good as the current flagship models for the cost of the compute itself.
It's like the rail industry analogy: we got a big bubble, but the rails are still there. Now with llm, we can just distill expensive one to create cheap open-source ones indeed
Variable costs - electricity etc. Current model is very resource intensive. You know when they build all those Olympic Venues and then once the Olympics is done the ongoing cost is too expensive and then they become derelict buildings.... like that...
Training is resource intensive. Serving gpt4o is not
The hardware will improve in a big way, a lot of money is going into that direction. Llm costs will go down significantly.