If you want to know whether artificial intelligence is a gigantic economic bubble, don’t just take pundits’ word for it. Major investors are now moving their money to try to protect themselves from the AI bubble popping.

cross-posted from: https://lemmy.ml/post/54396848

If you want to know whether artificial intelligence is a gigantic economic bubble, don’t just take pundits’ word for it. Major investors are now moving their money to try to protect themselves from the AI bubble popping.

For an industry that we’re told is central to our collective future, the artificial intelligence (AI) industry increasingly seems to be built on a combination of artificially inflated hopes and bad accounting.

The industry’s critics have been raising concerns about its finances for a while: the fact that most of its flagship firms are grossly unprofitable, that they’ve had to jack up their prices to try break even (leading their business customers to pump the brakes on using their products), or that many of the eye-popping investment announcements that are meant to show demand for AI is strong have actually been circular financing — meaning different AI firms cycling money to and from each other.

But none of it has seemed to slow the industry’s boom or the relentless hype machine behind it. Until now, anyway. It used to be that you mostly heard concerns about the industry’s underlying economics in newspapers, blogs, social media posts, and podcasts, and that those concerns went completely unreflected in the markets. But these concerns seem now to have finally bled over into investors’ thinking.

  • pelespirit@sh.itjust.works
    20·
    2 days ago

    The problem: After 6 months, every single vibed up slop project has failed to get through QA, and the developers can’t get AI to address the issues QA is reporting (similar stuff as people have been reporting with the slop-clones of Office and Photoshop, UI elements that fail to do anything despite looking like they should, the software doing one thing when it was asked to do another).

    • Is AI imploding within itself through poisoning and no new content?
    • Are they putting in their own guardrails to take away the really good innovations because of greed?
    • AI was never as good as they claimed, even the super advanced models?
    • All of the above?

    I’m more curious than anything. It seems to be getting worse for the free models.

    • Feathercrown@lemmy.worldEnglish
      9·
      1 day ago

      Is AI imploding within itself through poisoning and no new content?

      Model collapse doesn’t retroactively affect models that have already been trained, so this option seems like a pretty nonrigorous belief

      Are they putting in their own guardrails to take away the really good innovations because of greed?

      This would be difficult and likely counterproductive, but they are known to adjust the amount of compute they allow models to use, so they could be throttling that

      AI was never as good as they claimed, even the super advanced models?

      Ding ding ding, we have a winner! AI has improved, but those who are selling it will always and forever oversell it, like they would with any product.

    • jj4211@lemmy.world
      10·
      2 days ago

      I’d say it’s never been as good as Musk and Altman especially make it sound.

      If you drill into the nuance of their proof points that their companies bother to share, it’s generally a bit more clear that things aren’t exactly ‘asterisk free’ even then. Most recently I read how one of them proudly proclaimed they were 100% manual code free, but for the task described they still had 200 developers, which is significantly more developers than I have traditionally seen. To get things vaguely working, you need to be relentless in providing a super comprehensive set of requirements and criteria that are impeccable at fully capturing what is needed and could reasonably go wrong. Also a fanatical amount of detail to audit how the solution was reached and correct missteps, like when it decides to delete a failing test case instead of fixing the correlated problem. The ‘purist’ approach is, in my opinion, worse for the sake of just signaling how ‘AI-friendly’ you are.

      I can at least buy that from a pragmatic perspective, the codegen can accelerate things if used under a more balanced approach, being able to be in the code and grasp in detail where it might have gone wrong and correct it before it gets lost in a mess of garbage. It will do things that a human might skip that they shouldn’t, like hooking various unlikely errors and providing a nicer treatment. It is often useful to get a general idea of a good choice of library to do something and how it fits in your code, though you still have to beware that it may invent details that would be nice and convenient, but are wrong.

      The problem is that narrative is totally not what they need to justify the spend. They needed to take randos and prompt up things without full understanding. They needed AI codegen to be really valued on the same level as a full headcount. This trickles down to little folk like the team lead in my situation, where he thinks this is his only ticket to the ‘big leagues’ if he manages to drive a success story for ‘AI native’. He doesn’t understand any of it and his team doesn’t understand any of it and so of course the AI can’t bring what actually understanding the scenario would.

      Even more rough for that guy: he imagines a world of slopping up code and then selling the result, without ever having unique skill or insight. Assuming that can work, then why would any company buy your slop instead of just slopping it up themselves?

      • Feathercrown@lemmy.worldEnglish
        7·
        1 day ago

        Remarkably well said. I don’t have much of substance to add, but it is funny to me that:

        To get things vaguely working, you need to be relentless in providing a super comprehensive set of requirements and criteria that are impeccable at fully capturing what is needed and could reasonably go wrong.

        is basically describing what programming already was.

      • pelespirit@sh.itjust.works
        81·
        2 days ago

        I have found AI to be great as an extra pair of eyes, organizing, and finding obscure sources. So it’s a great assistant, not creator. You have to know what you’re doing.

        It’s like sending a fresh set of very smart, right out of school, employees to do the job. They have been trained to do everything you want them to do and more, but guiding them takes expertise. These recruits can’t do it on their own, they need a leader.

        Are the companies understanding this, or is greed blinding them?