Fable and Mythos were abruptly suspended in June over concerns that they could be used by hackers.
  • green_goglin@thelemmy.clubEnglish
    20 hours

    Advanced AI tools trained by AI agent predecessor(s) which were largely trained with Reddit shitposts.

  • Korkki@lemmy.mlEnglish
    1 day

    Ban only meant to create perceived value and hype for these models.

    • CommanderCloon@lemmy.mlEnglish
      2 hours

      China literally just put out an open weight model that verifiably beats the unverified Mythos claims in some scenarios; the reality is that they most likely want the US to “win” the AI race (which they cant, closed models will always be beat by open weight, which is what China is doing)

      They’re already on shaky finances, having an export ban would just pop the bubble sooner (and what remains of the US economy along with it)

    • Malyca@lemmy.zipEnglish
      22 hours

      Months ago. Right after they said they wouldn’t.

  • pinball_wizard@lemmy.zipEnglish
    23 hours

    Pencil pushers gonna push pencil.

    I’ll be surprised if we learn there was actually no dark web back room deal providing this stuff to anyone who didn’t appreciate the law getting in the way.

  • magnue@lemmy.worldEnglish
    21 hours

    I missed fable 5. Was nice to use in the 3 days I had access as long as it didn’t refuse.

  • Joe@discuss.tchncs.deEnglish
    1 day

    There is also a commercial aspect…

    Bigger models are more expensive to train and serve…

    Inference is currently insanely profitable if you have the hardware and the automation in place to support and serve it. At that point, it’s a money printing machine, and you want to squeeze as much out of it as you can.

    While training new models is extremely expensive, and serving them probably makes less profit (at least initially).

    Having an external brake applied to the frontier labs is likely good for their bottom line, while increasing hype and directing customers’ annoyance away from them.

    It’s likely only a temporary benefit, though. The dragon will catch up and apply more pressure, both on inference price and capabilities.

    • Dran@lemmy.worldEnglish
      1 day

      Can you cite your source on the claim that “inference is currently insanely profitable”? Everything I read suggests that openai and anthropic lose money on their plans.

      • Joe@discuss.tchncs.deEnglish
        10 hours

        My caveats were clearly stated… After capital expenditure, it’s just operational costs, where electricity & cooling are the big ones.

        At that point, it is insanely profitable to serve. The cheap API prices on open weights models hints at the profit margins involved in the US (the frontier labs and hyperscalers don’t open their books for us), unsurprisingly)

        Therefore, the longer they can serve existing and lower cost models at the current rates, the better for their bottom line. It’s just common sense in business.

        It doesn’t mean the company as a whole is profitable. I expect we’ll see turmoil in the coming months and years, and the prize will be compute capacity, with electricity & cooling options.

      • Alex@lemmy.mlEnglish
        24 hours

        I suspect it’s profitable in the abstract - and their accountants would be bad at their jobs if they couldn’t work out what utilisation rate you need to pay for the server runtime.

        However how aggressively you amortise the cost of the training is the key, especially if you keep releasing new models every 6 months.