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‘A feedback loop with no brake’: how an AI doomsday report shook US markets (www.theguardian.com)
submitted 8 months ago by to c/technology@lemmy.world
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[–] 23 points 8 months ago* (last edited 8 months ago) (8 children)

Lol, they sort of seem to know it's all castles on clouds and any spark e.g. a substack post could trigger the loaded spring. Yet, nobody thinks they'll be the ones holding bags of shit.

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  • [–] 11 points 8 months ago (7 children)

    They kind of know. The dot com crashed many companies, and also gave rise to Amazon. They're all just hoping they'll be the one that invested in the next Amazon.

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  • [–] 5 points 8 months ago (6 children)

    Have they made a profit yet?

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  • [–] 12 points 8 months ago (5 children)

    Amazon didn't make any profit for a decade and made 360 billion least year. They tell investors that AI will be the same.

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  • [–] 8 points 8 months ago (2 children)

    The difference was that Amazon knew how to make a profit, but was reinvesting into infrastructure plays and bigger fish.

    If they had to, they could have been a modestly profitable bookshop in 2002. AWS and monster logistics might not have developed to put them in the 13-digit club though.

    Does any AI-centric play have that fundamental fallback? The services that seem to be most effective at direct monetization, the coding tools, are typically running at huge losses. If they raised costs to cover, precious few firms will pay basically the salary of a senior dev for an emulation of an enthusiastic junior dev with an affinity for footguns.

    The less enterprise-focused products-- parasocial toys, image and video gen, will likely try to dip into consumer subs and advertising, but can that generate the cash volumes these platforms demand?

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  • [–] 6 points 8 months ago (1 child)

    If people would always demand answers for those questions, we wouldn't have speculative bubbles. For now, everybody seems to still believe the "it's the worst it'll ever be right now" and the "just more scaling bro" answers.

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  • [–] 1 point 8 months ago

    Trying to sell consumers on "scaling solves everything" is going to be a hard sell.

    If we look at general purpose computation, which had decades of actual scaling-solves-everything growth, you had two influences that made the message resonate with customers:

    • Clear existing applications where more power made the experience straightforward better. Your spreadsheet took an hour to recalculate at 8MHz and 20 minutes at 25MHz. A lot of the "bigger model" stuff is plateauing with marginal or spotty gains. If I feed another 5 Internets of data to ChatGPT, will that summarized email be that much better?

    • New applications that could be demoed on specialised low capacity hardware and scaled down to consumers as more power became available. Think of early CGI on hardware costing tens of millions, and now you can run Blender on a $149 laptop. Since most commercial AI plays are hosted services, there's not much opportunity to tease that way anymore.

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  • [–] 2 points 8 months ago (1 child)

    How much of that profit less decade was just them reinvesting in their company as opposed to burning money like you're trapped on Everest and need every bit of heat you can get?

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