15 points JumpCrisscross 1 hour ago 7 comments
Neywiny 47 minutes ago | parent
yogthos 45 minutes ago | parent
So, it's a race to the bottom because they have to keep spending more and more money on training the models just to keep ahead of the competition, while prices are driven down by the availability of open models.
Chinese companies understand this, and that's why they give their models away in the open. The real money is going to be in integrations and custom services built on top of the models. The models themselves aren't what's valuable.
tocs3 24 minutes ago | parent
This is a real question, because I just don't know. Don't the models needs lots and lots of training that need the gobs of giant data centers? So you either need the infrastructure or the money to buy computing to make the models? I see that all the money is being invested in AI and data centers but I do not quite understand why.
georgemcbay 10 minutes ago | parent
I am no economist or business person but AFAICT the massive amount of money being burned is because everyone in the space believes there will be a Google-like (for search) single winner who takes all when the dust settles on the AI race.
Because of this belief they are willing to burn any amount of money they can get their hands on to get to this mythical finish line as fast as they possibly can, seeing it as existential. Moving fast (particularly when your main cost is hardware capex) means moving expensively.
The real question is why anyone believes this single-winner theory in 2026 when all available evidence over the past few years shows that there is neither a moat nor a lock-in opportunity at all in this market.
For your product to be fit for purpose, it has to be able to automate your customer's ability to switch to a competing product with little to no friction. Good luck building any kind of real moat with that burden.
cyanydeez 22 minutes ago | parent
anxman 44 minutes ago | parent
Everyone has to get capital efficient now — and fast!
dmitrygr 8 minutes ago | parent