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Just want to point out the "more layoffs". We are still in the Uber-subsidized part of the relationship.
This is the honeymoon and the marriage ain't off to a great start
It's absolutely baffling how the gig-economy had been normalized.
I am a news junkie. Just this week they were talking to a business expert about youth unemployment (note it's bad everywhere but it's starting to get bad in 1st world now so we are caring finally) and his response was yeah it's bad but basically we have to get used to a future of hustling doing multiple gigs with no health benefits because that's where things are going.
Fucking government is bent over the barrel letting industry define the workers terms of engagement it's disgusting.
The companies need to at least seem to grow forever. See Facebook to meta VR stuff to AI. The business models could not grow forever that's the reason for this constant reinvention of themselves.
At some point AI and building these data centers will have to lead to quantum break , wow we have AGI or to monetization.
Who's going to pay the actual energy costs+ margin for all their tokens? Not me
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 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
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.
We are discussing cost. There is fixed cost (training) and variable cost (inference). Both components being discussed.