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How the AI Bubble Bursts

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Re: How the AI Bubble Bursts

#471

Post by zozbot234 »

aurareturn wrote: post #438
doom2 wrote: post #429

Earlier quoted context omitted.

> Bottom line is that H100 prices are near 3 year highs, A100s are still profitable to run, B200 prices are increasing, no one has enough compute. Then why aren't the hardware manufacturers of components needed by AI companies making plans yesterday to bring new fabs online to meet demand? That isn't a gotcha question, I genuinely want to know. The money involved isn't that much compared to the money changing hands b…

They are. They're making as many fabs as they can as fast as they can. The bottleneck is ASML, who can only make so many EUV machines. No one else can make EUV machines. Scaling chip fabs and chip equipment is much harder. And you have to understand that chip fabs go bankrupt if demand suddenly drops so they have to be more cautious by default.

If you're really compute constrained do you really need EUV machines? You can make do with DUV fabrication nodes, albeit at somewhat higher cost. The trailing edge is where a lot of the mass impactful innovation is, e.g. trying to replicate more advanced EUV nodes with DUV multiple patterning.

Re: How the AI Bubble Bursts

#472

Post by HDThoreaun »

jrflowers wrote: post #470
HDThoreaun wrote: post #451

Earlier quoted context omitted.

> getting medical advice Id be careful stating this is an inappropriate use of LLMs. Im semi tapped in to the medical literature community and there is a lot of serious discussion and research going into the usage of LLMs for medical advice and most of it is showing that LLMs are barely worse than doctors, and much much cheaper/more convenient. They definitely arent ready to completely replace doctors, but it seems t…

> barely worse than doctors I like that this comment is below, and posted after, an example where somebody had to pay extra money to clear up a misdiagnosis of stage 4 cancer by the “barely worse” software

There are many examples of doctors misdiagnosing a wide variety of things, which is largely the point here. People think of doctors as infallible when that is not even close to true.

Im certainly not saying fire all the radiologists, just advising an open mind when the actual literature starts saying that LLMs are as good as doctors in some areas.

Re: How the AI Bubble Bursts

#473

Post by zozbot234 »

H8crilA wrote: post #90
schnitzelstoat wrote: post #28

It's a winner-takes-all market and everyone wants to be the next Google and not the next Lycos or AskJeeves etc. It'd be interesting to see what they spend all the money on though as we seem to be hitting diminishing returns and I'm not sure if the typical enterprise user really cares about small improvements on benchmarks. It seems like it'd probably be better to spend all that on marketing, free trials, exclusivity…

Where to go next? I don't think anyone has gotten close to automating everyday PC usage, likely via screen capture and raw keyboard+mouse inputs. Imagine how much bigger would that market be than vibecoding.

Automating GUI use is a silly idea when the AI can do much of the same things by getting access to a *nix command line - which is how all coding models work. It matters when driving proprietary apps or browsing websites that aren't providing a clean machine-readable API, not really otherwise.

Re: How the AI Bubble Bursts

#474

Post by scrollop »

infecto wrote: post #274
malfist wrote: post #52

Earlier quoted context omitted.

> The cost to serve tokens is absolutely profitable today How can you possibly say that? Everyone knows that's not the case, these companies are losing money every day selling tokens. Revenue is not the same thing as profit.

Don’t confuse what I say. Bottom line these companies are not profitable yet but it is profitable to serve a token via the API. They have increasing demand, not enough supply, models are getting better on quick timelines. For sure there may be some losers but it’s not hard to see that that token serving can be a profitable activity.

This is a claim in the wind until you provide evidence.

Re: How the AI Bubble Bursts

#475

Post by zozbot234 »

mrbungie wrote: post #27
nopinsight wrote: post #11

> nobody is sure if even their metered pricing is profitable This is most likely wrong. Lab executives insist that serving tokens is profitable. It's the cost of training next-gen models that requires them to keep raising ever larger rounds. More importantly, many independent providers price tokens of open-weight models at a fraction of Anthropic's prices.

> Lab executives insist that serving tokens is profitable. Maybe marginally profitable, but right now they need to give out subsidies for people to use their products (Antigravity, Codex, Claude Code et al) in an actually useful manner that prevents churn and at the scale they need to justify usage growth forecasts, which they need to keep the wheel turning. Probably if you look at the users who exclusively use the s…

> Are those open-weight models as good as Anthropic? Are they the same parameter class?

Are they as good as Anthropic was one year ago? That's more like it. They don't have to be just as good, they just need to be the most worthwhile for the price. If frontier models are only providing a negligible advantage for what they charge, that absolutely matters.

Re: How the AI Bubble Bursts

#476

Post by dragonwriter »

shimman wrote: post #268
MattRix wrote: post #82

Earlier quoted context omitted.

This is not lying, that is just what run rate revenue means! It makes sense to use as a metric when a company’s user base is growing as fast as Anthropic’s is.

It makes sense to be extremely misleading about actual accounting figures? In what world is it okay to say you have $19b in ARR when you have only ever generated $5b for the entire duration of your company's existence? Did Enron start a business school I'm unaware of something?

> In what world is it okay to say you have $19b in ARR when you have only ever generated $5b for the entire duration of your company's existence?

In the same world that it makes sense to say that your current speed is 57mph when you've only driven 15 miles since starting the trip.

Re: How the AI Bubble Bursts

#477

Post by [deleted] »

piker wrote: post #147
karolist wrote: post #105

Earlier quoted context omitted.

You can have an opinion about a tool as a user, without ever having ability to create such a tool yourself, that's literally what every tech and auto reviewer does.

Sure, and the less you understand about the tool’s fundamental capabilities, the less useful your opinion is. The best reviewers have deep knowledge.

[deleted]

Re: How the AI Bubble Bursts

#478

Post by youniverse »

mattmanser wrote: post #172
joefourier wrote: post #106

Earlier quoted context omitted.

It’s absolutely not winner take all. LLMs have become a commodity and the cost of switching models is essentially nil. Even if ChatGPT has brand recognition amongst lay people, your grandparents aren’t the ones shelling out $200/mo for a Claude code subscription and paying for extra Opus tokens on top of that. Anthropic’s revenue is now neck and neck with OpenAI, but if tomorrow they increased the price of Opus by 5x…

I have non-tech friends telling me about preferring other models like gemini, this feels like the early days of search engines when people were willing to switch to find better results.

Yep i have nontech friends and even the younger generation students talking about how Claude is better at certain tasks or types of homework problems lol.

If it's used as a tool not just search, then people will definitely talk about the other stuff. Students who rely on free tiers will also definitely just have everything bookmarked.

Re: How the AI Bubble Bursts

#479

Post by fragmede »

niam wrote: post #453
aurareturn wrote: post #171

Earlier quoted context omitted.

Sure. I'll give you a basic plan without any insider knowledge on OpenAI. First, OpenAI and Anthropic are the leaders in model capabilities. Google is a close 3rd but 3rd nonetheless. Second, ChatGPT likely has about 1 billion active users right now. I think ads on ChatGPT will surpass even Google search ads in the future. There will be a class of users who will never pay for ChatGPT subscriptions and that's ok. Meta…

I don't discount this as a possibility but my impression is that the OpenAI brand isn't very sticky. Internet Explorer being pre-installed on Windows devices didn't prevent it from being demolished by newcomer Chrome throughout the 2010s. Now we're looking at a product that's even less integrated, and whose value is exposed through universal interfaces (human language, images, etc.). If OpenAI succeeds, I imagine tha…

For people that use ChatGPT the same way you do, yeah it's not. For people in the throes of AI psychosis who've named their ChatGPT and have a deep relationship with it, switching to a newer model from OpenAI is an issue, nevermind switching to a different model from a different company.

Re: How the AI Bubble Bursts

#480

Post by m12k »

Remember, having the dot com bubble burst did not prevent the internet from being integrated more and more in society over the next couple decades. What it did was stop the headless investment where money was thrown at anything that tangentially could be called "online". We went from "nobody knows what this is, but everyone wants a piece of it" to "we know what it is, and we sure did pursue a lot of bad ideas when we didn't". Expect something similar to happen with AI - having the bubble burst will not stop it in its tracks, but it will change what gets invested in.
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