[runtime_terror]

But explain to me how these companies will recoup these costs outside of increasing inference pricing?

Their business model is selling inference but the training and other costs have to be accounted for somehow. Unless I'm missing something obvious, inference costs must go up drastically if these companies are going to survive beyond the subsidy stage.

[wongarsu]

Sell more. The hope is that there is a huge addressable market that includes huge per-worker demand in almost all white collar work and lots of inference in people's private lives

If that doesn't work, then yes, then prices will have to go up

[0xffff2]

Both anecdotally for myself and from what I'm reading in the news, it seems just as likely that AI usage has already largely peaked.

There was a lot of hype and exploration of capabilities, but models aren't evolving fast enough to keep that going, so I'm settling down into a familiarity with what an LLM can and can't do that means I am using them less overall that I was 6 months ago when I was throwing everything under the sun at it just to see what happened.

Without either new model breakthroughs or dramatically _lower_ costs, I will be very surprised if the ultimate market doesn't end up within an order of magnitude of where it is today.

[d1sxeyes]

> AI usage has already largely peaked.

I think this is minimally likely. While as individuals on the bleeding edge, we're perhaps using these tools less and less, and our echo chamber reinforces that, the penetration of AI into the normal corporate workplace is still very low - emails rewritten with ChatGPT, meeting notes summaries generated by default, etc. There are a million use cases for LLMs which are not yet built out. The tokenmaxxers will begin using AI less, but the penetration into the mass market will continue at a huge velocity.

[runtime_terror]

I agree that more uses will be found and that maybe we're not at the peak. But it also seems very clear a few players have been actively working to inflate usage numbers by margins that might take a while to replace with legitimate uses

[runtime_terror]

Exactly. Like how Meta has a "blow our money on LLMs" leaderboard. Seems like a few companies are attempting to inflate hype enough so all the investors can exit without losing their heads.

Reminds me of the crypto hype but where the hype agents are some of the largest companies in the world.

[runtime_terror]

Yeah from my understanding they'll need to create a few trillion dollars more demand to break into profitability if we look at all the debt/obligations/contracts

[HDThoreaun]

Obviously they need more paying users. The entire game in tech is taking advantage of (comparatively)low marginal costs to pay off capex once you corner the market

[runtime_terror]

I do think that's at least part of the strategy. The problem is that we've never seen a single product category so hyped in history, literally trillions of dollars invested. To recoup that, some not so trivial miracles will need to happen.

[HDThoreaun]

I think that within 5-10 years most white collar workers around the world will be paying for AI assistants. There are 1.2-1.3 billion such people to sell ai to, so getting more users doesnt really seem like a miracle to me. I do think convincing everyone to use expensive proprietary models instead of open ones hosted cheaply by third parties will be a minor miracle for the AI labs. Definitely not out of the question though.