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I'm Not Convinced the AI Bubble Exists (matteoraso.github.io)
submitted 13 hours ago by [B] to c/hackernews@lemmy.bestiver.se
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[–] 6 points 11 hours ago (2 children)

The reason why AI companies are spending so much money is to rollout data centres to run the AI in the first place.

Yet all companies fail to point whether there actually is, or will be, enough demand for ALL the capacity being built. Remember, we're talking like 10+ huge datacenters that are effectively useless for anything other than AI.

If the AI industry has to pay off 5 trillion dollars over the course of 20 years, that's 250 billion dollars a year

The author compares with Google/Alphabet revenue, a company which deals in ads and several other services. Guess the problem of comparing a company with a somewhat diverse portfolio vs. one that has one single product. Microsoft had a gross revenue of 281 billion dollars in 2025. AI companies need Microsoft levels of revenue by the end of next year.

Profits Can Grow, By A Lot

They can also not grow, because Anthropic and OpenAI can end up scaring customers into open models.

That means that there will never be a point where a company wins the AI wars

Wrong, Nvidia has clearly won the war by selling shovels that are useless for anything but AI. RAM manufacturers are also laughing all the way to the bank.

the average person isn't going to use a locally hosted model, ever.

True. But average person can stop using said model if it starts being a scummy piece of shit charging hidden fees or eating up tokens more than the week prior. Besides, someone might try to rent their AI stacks for a profit and undercut the 2 inflated giants.

There's Still Plenty Of Capital To Raise

Everything's pointing to the opposite for 2027, with capital drying up, especially with "scaredy investors terrified of democrats being against datacenters". Anthropic going public is likely due to its less than ideal credit rating (thus forcing it to deal with higher interest rates), so they can raise more money and leave suckers holding the worthless share bag.

Alphabet, Meta, and NVIDIA are all AI companies

Alphabet is a "everything about google" business that has a side gig with AI, Meta is a spy operation business that has a side gig with AI, and Nvidia is an overpriced hardware business. None of them is an "AI company". The main problem of this bubble is absurdly excessive investment into AI, lots of scummy "it's technically a loan, but legally the company can omit this from the balance sheet" shenanigans and the desperation to force AI down the throats of the whole world.

I don't think the rhetoric about the AI bubble is really about finances. (...) I think the supposed AI bubble has become such a large talking point because it represents the hope that things can go back to how they used to be. (...) So, people wishcast. They tell themselves that this is all a giant bubble, and one day soon, everything will crash down and immediately go back to how it used to be.

Boy, imagine seeing an unproven technology receiving 2 FUCKING TRILLIONS OF DOLLARS, being promised another 3 in investments and thinking "nah, this ain't about finances".

As many people already said, the genie is out of the bottle. Nobody realistically expects shit to come back like it was before. Slop won, everyone that used to produce content lost, congrats, enjoy the shitshow of razing what little of the non corporate internet remained.

Even if AI turns out to be a bubble, it will be a bubble in the same way that the internet was a bubble, where the underlying technology remains useful.

The bubble is mainly in the datacenters, whose sole reason of existing is feeding AI. Remove AI companies and you'll have literally zero customers. AWS, Meta, Google, Microsoft have no use for nvidia chips for actual server work.

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  • [–] 1 point 8 hours ago (1 child)

    the average person isn't going to use a locally hosted model, ever.

    True.

    I don’t think that’s true at all.

    Platform vendors have already started shipping small LLMs for translation and for AI assistance. If you use Apple Intelligence you’re using local models to some extent for the smaller tasks. Consumer hardware is perfectly capable of running much larger models too if you give it enough RAM, and is only held back by RAM being expensive. My five year old laptop can run 30B-ish LLMs, and if RAM prices hadn’t exploded, then by now surely those 64 GB wouldn’t be an outlier and newer devices would be running more powerful models for “average people” too.

    But prices for RAM will eventually come down again and hardware in general will keep becoming more capable. It’s weird to me to suggest anything else, considering that we went from 8 bit PCs with 64k of RAM to modern smartphones in my lifetime. Why would hardware stop improving exactly now?

    The same applies to LLMs themselves. Qwen 3.8-27B beats expensive online models from two years ago in its stronger areas (e.g. coding). Why would that development suddenly stop now? There’s a hard limit here somewhere regarding the compression of knowledge (just based on information theory, not specific to AI) - which is why smaller models hallucinate more - but that doesn’t rule out e.g. improvements to how external knowledge can be integrated at runtime.

    Accordingly, the AI models shipped with consumer devices will keep becoming more powerful and online models will be needed less and less for “average person” tasks.

    One part of the AI bubble is the assumption that AI will remain compute intensive, which is what drives the data center buildout. But historically, new technologies have often started out as expensive and barely obtainable for average people and then became cheap and ubiquitous within fairly short time frames. It’s weird to me to suggest that LLMs will be an exception especially while also suggesting, at the same time, that the technology will accelerate research and development across the board.

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  • [–] 1 point 2 hours ago

    Consumer hardware is perfectly capable of running much larger models too if you give it enough RAM, and is only held back by RAM being expensive.

    And average users having, at most, 8GB of RAM, with 2GB being eaten by Windows and another 2, minimum, by Chrome. Remember, average user is the person who doesn't bother with latest games and doesn't run linux, they only do some office stuff, watch videos and browse social media.

    But prices for RAM will eventually come down again and hardware in general will keep becoming more capable.

    At best, I expect RAM prices to drop back to their sane price somewhere in 2029-30.

    Also, you may not have noticed, but for average users (people that mostly just browse social media and watch videos), mid-spec computers from 2013 are almost perfectly serviceable today - just swap the HDD for a SSD and you're golden. Smartphones have also stopped getting significant hardware upgrades, despite shittier software trying to force obsolescence on older, mid-spec models.

    Why would hardware stop improving exactly now?

    Because current fabrication process of chips seems to be very close to limits imposed by the laws of physics. The 1nm fab process that TSMC might manage to pull by next year is possibly the literal limit of MOSFET. Unless someone comes up with a different fabrication process that can reach atomic precision, or somehow get more power efficiency from the same area/volume of transistors, or some wonder material, there's no reason to expect hardware to keep improving at the same pace it did decades ago. "AI will discover-" It won't. There is nothing indicating it might, much less will. I'd love to be proven wrong, but I seriously doubt AI will magic out some new way to get Moore's law back on track

    Accordingly, the AI models shipped with consumer devices will keep becoming more powerful and online models will be needed less and less for “average person” tasks.

    I seriously doubt that for a single reason: money. Why let the user have the model when you can rent it off to them? Or, even worse, the model runs locally, but you have to pay a fucking subscription in order to use it because fuck you. "You will own nothing and be happy about it"

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