• @GeneralInterest
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    123 hours ago

    Maybe it’s like the dotcom bubble: there is genuinely useful tech that has recently emerged, but too many companies are trying to jump on the bandwagon.

    LLMs do seem genuinely useful to me, but of course they have limitations.

    • @datelmd5sum
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      42 hours ago

      We’re hitting logarithmic scaling with the model trainings. GPT-5 is going to cost 10x more than GPT-4 to train, but are people going to pay $200 / month for the gpt-5 subscription?

      • Madis
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        051 minutes ago

        But it would use less energy afterwards? At least that was claimed with the 4o model for example.

        • @fuck_u_spez_in_particular
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          -112 minutes ago

          4o is also not really much better than 4, they likely just optimized it among others by reducing the model size. IME the “intelligence” has somewhat degraded over time. Also bigger Model (which in tha past was the deciding factor for better intelligence) needs more energy, and GPT5 will likely be much bigger than 4 unless they somehow make a breakthrough with the training/optimization of the model…

      • @GeneralInterest
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        -12 hours ago

        Businesses might pay big money for LLMs to do specific tasks. And if chip makers invest more in NPUs then maybe LLMs will become cheaper to train. But I am just speculating because I don’t have any special knowledge of this area whatsoever.