Running llama-2-7b-chat at 8 bit quantization, and completions are essentially at GPT-3.5 levels on a single 4090 using 15gb VRAM. I don’t think most people realize just how small and efficient these models are going to become.

[cut out many, many paragraphs of LLM-generated output which prove… something?]

my chatbot is so small and efficient it only fully utilizes one $2000 graphics card per user! that’s only 450W for as long as it takes the thing to generate whatever bullshit it’s outputting, drawn by a graphics card that’s priced so high not even gamers are buying them!

you’d think my industry would have learned anything at all from being tricked into running loud, hot, incredibly power-hungry crypto mining rigs under their desks for no profit at all, but nah

not a single thought spared for how this can’t possibly be any more cost-effective for OpenAI either; just the assumption that their APIs will somehow always be cheaper than the hardware and energy required to run the model

  • zoe@lemm.eeEnglish
    0·
    1 year ago

    it lacks human input. also there is no economic incentive for ai to learn chess by teaching it much needed human bias. also most useful jobs are more brain-dead than chess, i.e lawyering

    • raktheundead@fedia.io
      3·
      1 year ago

      also most useful jobs are more brain-dead than chess, i.e lawyering

      This sounds like the rationale that myopic ancap arseholes had when they came up with the “smart contract”.

    • self@awful.systemsOPEnglish
      1·
      1 year ago

      also most useful jobs are more brain-dead than chess, i.e lawyering

      ahahaha is this real? please, whose alt is this because it’s perfect