Pretty sure they'll offer them at least so long as it takes to bring OpenAI and Anthropic into insolvency. Why wouldn't they? The Chinese models are way more nimble to train and run, bring in a ton of goodwill globally, and put immense pressure on the VC furnace that is the US AI sector. And apparently OpenAI and Anthropic think so, too - why else would they try so hard to ban them instead of outcompeting them?

> The world is out of fab capacity. Can anyone expand on this point? I read an article saying that the big AI co's datacentre spend was a bunch of lies because they can't build datacentres at anywhere near the rate they want to.

Seriously, they’re trying to justify trillion+ IPO’s while setting piles of money on fire, prices aren’t going DOWN.

They aren't going down, but in the meantime they'll cover their ass by bribing their way into the S&P 500 and then use your 60 year old mother's 401k and teacher's pension to fund their risky capital expenditure.

They're going to need to bring in a few trillion dollars fast to meet wall street expectations. Expect prices to rise.

> Speculation here but I think openAI/antrhopic api inference is insanely profitable, it just needs more volume to amortize the training costs. Well, they just rent their hardware, so I'm not so sure. But they'll both be public soon and we should get that breakout in their cost structures, somewhat.

It’s also worth noting that’s the peak benefit. Expect most engineers to not hit those limits on the regular (if at all, since limiting this puts skills in focus again), and that limit to come down over time as the easy processes are automated and humans are re-tasked with harder problems relative to their TC. This is not a good bellwether for the AI industry, including its adherents. Their growth assumed a level of indispensability that’s not being reflected in hard numbers and real costs, which lends credence to the notion that these IPOs being fast-tracked are meant to try and cash out before the bubble really pops in earnest. There’s no way consuming enterprises are going to pay such insane costs for such minimal uplift in the long run, and the AI companies can’t keep offering subsidized tokens via subscription plans at their current pricing.

Between AI and the stock market (which of course relates directly to AI), I’ve lost count of the number of times I’ve heard lately another variation of “this time is different.” Sometimes so close to those words that I wonder why the person speaking them doesn’t feel a bit tingly. Great big warning signs all around.

>Why there are so many people that still believe that AI coding is a fad? Because there's not a single piece of evidence that this has improved the quality of the delivered software, or for that matter even the speed of features any of these companies produce, in fact if anything the opposite. The point of software development, the hint is in the name, is to develop software, not consume tokens. If Uber was now full of 10x engineers the stock price of Uber would be up, not down on a yearly basis. Hilariously enough the only company whose stock price is up appears to be Antrophic

Also, a bucket for VC to put all that NFT, IoT, blockchain, VR investment into. VCs gonna VC and the last 15 years of bets failed so the last few years have been a transition away from those toward "the next thing".

I don't think it is unreasonable to say both will happen, is it? In the long term, tokens will fall in price. Obviously. (If "tokens" continues to be the unit) In the short to medium term, for the IPOs to succeed, people have to start actually paying for what they are using, so the price will go up, and is going up, quite a lot. Once their value is set they will slowly fall from that point (or some point maybe halfway, depending on how much the market is willing to continue to subsidise). I am an AI cynic, but I am now an informed cynic; I am learning agentic tools so I know where they are useful and I know my enemy. I think the "fad" here is cloud-based, metered AI being a dominant work mode. Nothing, so far, has suggested to me that any other outcome is likely than edge- to local-scale, on-device, on-laptop, on-prem models getting good enough to the point where people use them by default and use the cloud models only when they need the extra oomph. I cannot believe that there is anything other than an enormous incentive for companies like Uber to find local, small model and on-premises solutions to their problems, not least while pricing is so changeable and people are getting nasty surprises. Betting on OpenAI and Anthropic being around over the long term in the form that they are now, that feels like valley hopium. Utility monopolies essentially always derive from physical/geograpical limitations, don't they?

That's going to stop eventually, and I think at that point we're going to see business models more like the major CAD providers.

I'm not sure the labs will win either. I wouldn't be surprised to see OpenAI & Anthropic just get acquired, either by Microsoft or Amazon and their models just become another product offering in their public cloud and and some hybrid on-prem offering like Azure Stack HCI or Azure Stack Hub (already basically a "cloud in a black box" that could become "AI in a box")

There’s probably plenty of money to be made in LLMs as a service - but not enough time has passed for the commodification to occur. I’m with you in that when the dust settles I don’t think any of the frontier model providers will have a moat. Just like during the dotcom boom a catchy URL and a webpage that could accept payments wasn’t a moat, either.

The evidence that per-token inference _is_ subsidized is (a) competition is a bloodbath (b) these companies are raising more money than any company has raised ever (c) a maybe-profitable quarter is maybe-coming for Anthropic after maybe-signing a compute deal with SpaceX that legitimizes both companies. The evidence that per-token inference _is not_ subsidized is... a quote or two from Dario and Sam Altman

> theres no evidence that they arent (or can't) use profitable inference to subsidise those other expenses as far as we know there's no evidence that they can produce any profits at all

That's not evidence. Very likely though, but the only evidence we get one way or another is when they IPO.

This is market introductory pricing that hasn't factored in cost recovery. Most of it has been run on early investment with the assumption they will recover costs in the long run. The prices are subsidized across the board and they will need to go up signficantly to recover them.

For claude shops this was a huge hit. But lets back this up. There are some companies that haven't even built a break-even model at this price because they are funded by investment. As soon as those investors lose patience the first dominos will fall. For those who have somewhat of a business model, will it survive a price increase? The bigger question is do the base model providers have enough runway and have a way to keep going as they need to recover costs.