The cost of LLMs have gone down over 30 times in the last 1-2 years. At what point would you think it is economically feasible? I think this a question to ask so that we can tackle the fundamental economics of LLMs.
The cost of LLMs have gone down over 30 times in the last 1-2 years. At what point would you think it is economically feasible? I think this a question to ask so that we can tackle the fundamental economics of LLMs.
It becomes feasible when people are willing to pay more than it costs to run it. But I think this will be a pretty uphill battle, as many use cases are hard to monetize (eg proofreading) and for many use cases you will feel pressure from smaller models (you don't need the most expensive SOTA model to generate an email). There is probably just a very limited amount of use cases that are in the goldilocks zone with their difficulty so that people will be willing to pay for them, AND AI is able to solve them. I think programming might be one of them.
> It becomes feasible when people are willing to pay more than it costs to run it.
This is what I want to challenge. At what point do you think people will pay more than it costs? Lets try to come up with a number because the price of LLMs have dropped more than 30 times in the last 2 years.
It may continue to drop and AI companies will continue to be in loss because the new things will be unlocked due to new efficiences and the same debate over LLM economics will continue.
I think it is already profitable and people are more than willing to pay for the actual costs.
> I think it is already profitable and people are more than willing to pay for the actual costs.
If people are willing to pay for the costs, where are the profitable AI companies?
They don’t make profit because they invest in research and development.
We would also need to know how many people are willing to pay for it, on a consumer level. Additionally business will need to see real ROI for using it.
At the moment everyone is trying their best to implement it, but it remains to be clear if it actually increases a company's profitability. Time will tell, and I think there are a lot of things obfuscating the reality right now that the market will eventually make clear.
Additionally the economics of training new models may not work out, another detail that's currently obfuscated by venture capital footing the bill.
And yet 90% of AI companies do not break a profit. If it was economically feasible, big corps would start cashing in immediately and halt development. They have gone deep with AI so now must go deeper to get to that cashing-in point.
I don't see why they would want to halt development. The industry isn't at a stagnant stage when PE comes in and sucks all the joy out of things.