- cross-posted to:
- usa@lemmy.ml
- cross-posted to:
- usa@lemmy.ml
cross-posted from: https://lemmy.ml/post/54396848
If you want to know whether artificial intelligence is a gigantic economic bubble, don’t just take pundits’ word for it. Major investors are now moving their money to try to protect themselves from the AI bubble popping.
For an industry that we’re told is central to our collective future, the artificial intelligence (AI) industry increasingly seems to be built on a combination of artificially inflated hopes and bad accounting.
The industry’s critics have been raising concerns about its finances for a while: the fact that most of its flagship firms are grossly unprofitable, that they’ve had to jack up their prices to try break even (leading their business customers to pump the brakes on using their products), or that many of the eye-popping investment announcements that are meant to show demand for AI is strong have actually been circular financing — meaning different AI firms cycling money to and from each other.
But none of it has seemed to slow the industry’s boom or the relentless hype machine behind it. Until now, anyway. It used to be that you mostly heard concerns about the industry’s underlying economics in newspapers, blogs, social media posts, and podcasts, and that those concerns went completely unreflected in the markets. But these concerns seem now to have finally bled over into investors’ thinking.
They are profitable on inference (at least anthropic). Inference is cheap, it’s not susbsidized. It’s training that’s expensive, but if the bubble really does pop then current open source models (which are pretty much sold at inference rate + small margin) will actually go down in price since the cost of hardware will have gone down (assuming less demand for GPUs). Considering that the current best open model is roughly one month behind, we won’t revert to pre-ai anywhere. It’s just too cheap for that.
Still, it’s lovely seeing people spreading misinformation based on something they saw on tiktok years ago. Keep up with the times or don’t spread outdated info.
Yeah. That $80 billion loss was all for training I guess 🙄
Well that and the fact that they have a company to run and people to pay. Do you seriously believe inference is not profitable, despite evidence to the contrary being everywhere you look?
It’s not exactly $80 billion, $72 billion of that loss is accounting for the rising valuation giving early investors larger paybacks, aka Google and Amazon. The same people who give Anthropic its compute, at a very very healthy discount, are the ones who benefit most from a high valuation.