We are still in the Uber-subsidized part of the relationship.
It’s not comparable, the costs for Uber are fixed development costs which decrease per customer with more customers. AI is strictly more expensive the more users there are since the cost is per use. The financial outlook for the industry is very bad, it will probably never be profitable except maybe in some extremely niche situations.
I think they mean the company since they’re the most famous example of subsidising the product to gain market share and their name is invoked all the time in discussions of AI economics
It’s not comparable, the costs for Uber are fixed development costs which decrease per customer with more customers. AI is strictly more expensive the more users there are since the cost is per use. The financial outlook for the industry is very bad, it will probably never be profitable except maybe in some extremely niche situations.
Uber fares are also per use…?
Isn’t most of the cost in the model training?
The cost of inference has passed the cost of training quite a while ago and it’s by far the majority of expenses
Thanks for the link, but disagree with your summary.
The Spend on inference has passed the Spend on training.
Training is the monopoly product and even the cheapest known model (deepseek) cost 10s of millions to train.
That’s got nothing to do with how expensive it is to serve models to customers which is what was being discussed.
I don’t think they mean uber the company, I think they meant uber as in over or very.
I think they mean the company since they’re the most famous example of subsidising the product to gain market share and their name is invoked all the time in discussions of AI economics