I’ve read some of Ed Zitron’s long posts on why the AI industry is a bubble that will never be profitable (and will bring down a lot of companies and investors), and one of the recurring themes is that the AI companies are trying to capture growing market share in an industry where their marginal profits are still negative, and that any increase in revenue necessarily increases their costs of providing their services.
But some of the comments in various HackerNews threads are dismissive, saying that each new generation of models makes the cost of inference lower, so that with sufficient customer volume, the companies running the models can make enough profit on inference to make up for the staggering up-front capital expenditures it took to build out the data centers, train their models, etc.
It’s all pretty confusing to me. So for those of you who are familiar with the industry, I have several questions:
- Is the cost of running any given pretrained model going down, for specific models? Are there hardware and software improvements that make it cheaper to run those models, despite the model itself not changing?
- Is the cost of performing a particular task at a particular quality level going down, through releases of newer models of similar performance (i.e., a smaller model of the current generation performing similarly to a bigger model of the previous generation, such that the cost is now cheaper)?
- Is the cost of running the largest flagship frontier models going down for any given task? Or does running the cutting edge show-off tasks keep increasing in cost, but where the companies argue that the improvement in performance is worth the cost increase?
I suspect that the reason why the discussion around this is so muddled online is because the answers are different depending on which of the 3 questions is meant by “is running an AI model getting cheaper over time?” And the data isn’t easy to synthesize because each model has different token prices and different number of tokens per query.
But I wanted to hear from people who are knowledgeable about these topics.
For an equivalent prompt and similar quality answer, yes. Inference prices are dropping.
However, higher quality answers (or more complex prompt handling) are currently going up in inference price.
The fun part will be once quality hits a point where the average user (or even business) doesn’t care about the incremental quality change any more. Then it’s going to be a race to the bottom for performance per dollar.
Who cares if the not all companies or investors make money? They can make their bets, some will win and some will lose. I just want better tech for cheaper prices.
I care about the downstream effects on everyone else, of who else gets hurt in a crash.
That has nothing to do with the technology. The last crash was caused by a global virus, and the one before that was the banking system…