It looks like AI has followed Crypto chip wise in going CPU > GPU > ASIC

GPUs, while dominant in training large models, are often too power-hungry and costly for efficient inference at scale. This is opening new opportunities for specialized inference hardware, a market where startups like Untether AI were early pioneers.

In April, then-CEO Chris Walker had highlighted rising demand for Untether’s chips as enterprises sought alternatives to high-power GPUs. “There’s a strong appetite for processors that don’t consume as much energy as Nvidia’s energy-hungry GPUs that are pushing racks to 120 kilowatts,” Walker told CRN. Walker left Untether AI in May.

Hopefully the training part of AI goes to ASIC’s to reduce costs and energy use but GPU’s continue to improve inference and increase VRAM sizes to the point that AI requires nothing special to run it locally

  • brucethemoose@lemmy.world
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    9 days ago

    It could be if it’s run locally.

    If you agents run on your hardware, navigate crappy apps and websites and such for you, what do you need the corporate cloud for? How can they show ads or monetize you through that?

    That’s the war raging right now, open-weights vs closed weights.