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How the AI Bubble Bursts

martinvol.pe

171–180 of 557 posts

Re: How the AI Bubble Bursts

#171

This is an awful article. I don't know how it reached #1 on HN. 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. Google, OpenAI, Anthropic, Meta, AWS, Azure are all compute constrained. Every single one of them said so publicly. Neo clouds are telling customers they're all sold out now and you even have to book compute in…

> I think OpenAI is going to be bigger than Microsoft in market cap within the next 3 years. I am yet to see how a one-legged business model with just a single product (that is not crude oil), without a plan and money is going to become sustainable. Oh yeah, maybe they'll finally make money on those autonomous lethal weapons. That sounds the easiest.

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 and Google are two of the most profitable companies in history who almost rely solely on free users for their cash cows. "Ask ChatGPT" is already "google it" for the masses.

Third, there is so much untapped revenue potential from science, medicine field that OpenAI can eventually own with Anthropic. Microsoft stands no chance here since they can't build competing models.

Fourth, I can easily see ChatGPT morphing into agents for consumers and people will pay for them. AI is moving up the value chain fast. I don't see any reason why consumers won't pay for ChatGPT but will pay for Netflix.

Just some basic ideas based on public knowledge. I'm sure there are plenty more.

I'm not going to bet my house that OpenAI will become bigger than Microsoft in 3 years, but I'll put down a few hundred dollars on this bet.

Re: How the AI Bubble Bursts

#172

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…

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.

Re: How the AI Bubble Bursts

#173

Earlier quoted context omitted.

Demand of tokens is absolutely skyrocketing. And unlike the traditional "this will replace humans right away", I think what this introduce is a lot of incentive to spread those token in places where there was never any incentive to hire a software engineer for previously. In turn, that will drive a lot of business activity in those area that will potentially fail given the current quality of the output. This feels li…

Tulips sales also skyrocketed. Seriously, what value are tokens providing other than justifying layoffs. Concretely. Today. Not in the speculating scenario that cardiologist could be replaced with models. We see this new trend of agentic coding, again a promise software will be written that way going forward, despite the number of fiasco already experienced when trusting a model turned bad. The use case may provide v…

It's ridiculous to call this tulips, in the sense of a speculative asset whose price depends on resale. A more similar recent example is the dotcom boom and bust based on building internet infrastructure, or the 2008 crash which was based on cyclical infrastructure overinvestment. These crashes were characterized by demand growth not keeping up with investment because the target markets were tapped out. Not clear when we'll get there with AI. The consumer market seems saturated on chatbots but we're not even close to saturated for b2b or self driving for example. And this discounts other new technological offerings which may unlock larger consumer markets (products where people are willing to pay $100 a month instead of 10 or 20)

All that said the dotcom boom is extremely analogous and that crash was quite bad.

Re: How the AI Bubble Bursts

#174

Earlier quoted context omitted.

This is a classic HN mistaking the map for the territory. R&D and capex absolutely figure into de-facto profitability and sustainability for AI labs, despite their separate treatment in accounting. > well most of us here on HN have benefited from decades of overinflated engineering salaries being paid by often companies that were not profitable and not only unprofitable This is a really concerning perspective: people…

> any company ingesting that much cash needs to justify its capacity to survive. What, why? There are tons of low-margin capex-intensive business out there. I think AI will end up like being like hosting. All the models will converge to being pretty-decent and the companies will have to compete on efficiency since they are selling a generic commodity. You can already see Anthropic fears this scenario since they try s…

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Re: How the AI Bubble Bursts

#175

Earlier quoted context omitted.

Demand of tokens is absolutely skyrocketing. And unlike the traditional "this will replace humans right away", I think what this introduce is a lot of incentive to spread those token in places where there was never any incentive to hire a software engineer for previously. In turn, that will drive a lot of business activity in those area that will potentially fail given the current quality of the output. This feels li…

Tulips sales also skyrocketed. Seriously, what value are tokens providing other than justifying layoffs. Concretely. Today. Not in the speculating scenario that cardiologist could be replaced with models. We see this new trend of agentic coding, again a promise software will be written that way going forward, despite the number of fiasco already experienced when trusting a model turned bad. The use case may provide v…

Tulip futures skyrocketed, it was economic speculation on a useless asset, not supply and demand. Crypto is the analogy, not AI. Given that the major AI labs other than GDM are private, this is even more true.

Agentic coding absolutely blew up from demand, users are not being tricked into paying $200 a month, and they’re not complaining about hitting rate limits because it’s useless.

Re: How the AI Bubble Bursts

#176

This article tries to build upon a lot of half-truths or incorrect facts, like this: > OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new. The discussion about being unprofitable also repeats the reducti…

> The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new.

This statement doesn't discount the original statement: that ads are going into GPT, which Sam called a last resort.

> The discussion about being unprofitable also repeats the reductionist view that these companies are losing money and therefore the business model doesn’t work. This happens with every VC cycle where writers don’t understand that funded companies are supposed to lose money while they grow. That’s what the investment money is for.

Usually propped-up companies don't last in the long term once the VC subsidy runs out. There's a difference between getting VC money in order to buy rocket parts, and getting VC money in order to charge $7 when you would really need to charge $10. The latter problem never goes away.

Re: How the AI Bubble Bursts

#177

Earlier quoted context omitted.

Demand of tokens is absolutely skyrocketing. And unlike the traditional "this will replace humans right away", I think what this introduce is a lot of incentive to spread those token in places where there was never any incentive to hire a software engineer for previously. In turn, that will drive a lot of business activity in those area that will potentially fail given the current quality of the output. This feels li…

Tulips sales also skyrocketed. Seriously, what value are tokens providing other than justifying layoffs. Concretely. Today. Not in the speculating scenario that cardiologist could be replaced with models. We see this new trend of agentic coding, again a promise software will be written that way going forward, despite the number of fiasco already experienced when trusting a model turned bad. The use case may provide v…

I know there is a large force on HN that want to deny the value of tokens and I know it’s anecdotal but the writing is on the wall. If it’s not valuable to your workflow today it will be soon. I already have tests being written, automated hooks into bugs where an initial PR gets generated with a potential fix. It’s far from perfect but junior engineers are far less productive.

Re: How the AI Bubble Bursts

#178

> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fa…

I do wonder how closely prices consumer RAM kits follow the wholesale prices for NAND chips manufacturers see internally. The pcpartpicker graphs you linked show consumer prices have leveled out and may even be starting to fall. Depending on how the economics shake out this could mean we've hit an inflection point.

My personal prediction is that once the VC bill comes due and prices for frontier models starts to climb, competition for efficiency will heat up. The main AI use-cases seem to be falling into buckets, and I doubt serving gigantic, do-it-all general models for every use-case under the sun is remotely cost-effective.

If common use-cases start to be more efficiently served by smaller, more efficient purpose-built models (or systems thereof), it'd make the big frontier models increasingly niche. Cursor's Composer 2 model is a great example of this.

In any case, I think it's pretty fair to speculate we may be seeing RAM prices start falling sooner rather than later.

Re: How the AI Bubble Bursts

#179
post #89

> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fa…

> Reality begs to differ Honestly you're both wrong. RAM prices spiked speculatively, and they're going down for the same reason. Market people always want to argue in fundamentals, when in practice *ALL* the high frequency components of the signal are down to a bunch of traders trying to guess where it's going in the short term. At best those guesses are informed by ground truth ("AI needs a lot of RAM!" "Sam corner…

I’ll believe they’re going down when it doesn’t cost $550 for the $105 ram I purchased 1 year ago. Yes consumer prices lag commercial prices yada yada, I think any hot takes are pointless until we see lower prices or far more convincing evidence it’s coming. When it costs basically a MacBook neo for 32gb of DDR5 ram it’s hard to hear “ram is coming down for sure”

Re: How the AI Bubble Bursts

#180

> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fa…

Not crashing yet. The article is looking 1 to 5 years to come. Given Nvidia's CEO's agitation I would give credit to the prediction, and if it's correct the price will go back to what it was, or even lower of investment in capacity are made today.

My take is new capabilities will consume any price reductions, making them moot. At least in the medium term.

A RAM price drop due to some magic efficiencies assumes everything else doesn't change, which I doubt anyone honestly thinks will be the case.

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