• @MotoAsh
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      4 months ago

      Not if it’s for inference only. What do you think the “AI accelerators” they’re putting in phones now are? Do you think they’d be as expensive or power hungry as an entire 3090 for performance if they were putting them in small devices?

      • ShadowRam
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        84 months ago

        Ok,

        Show me a PCE-E board that can do inference calculations as fast as a 3090 but is less expensive than a 3090.

      • @[email protected]OP
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        4 months ago

        Yeah show me a phone with 48GB RAM. It’s a big factor to consider. Actually, some people are recommending a Mac Studio cause you can get it with 128GB RAM and more and it’s shared with the AI/GPU accelerator. Very energy efficient, but sucks as soon as you want to do literally anything other than inference

        • @Fuzzypyro
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          14 months ago

          I wouldn’t say it particularly sucks. It could be used as a powerhouse hosting server. Docker makes it very easy to do no matter the os now a days. Really though I’d say its competition is more along the lines of ampere systems in terms of power to performance. It even beats amperes 128 core arm cpu at a power to performance ratio which is extremely impressive in the server/enterprise world. Not to say you’re gonna see them in data centers because price to performance is a thing as well. I just feel like it fits right into the niche it was designed for.

          • @[email protected]OP
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            14 months ago

            How could you solve the problem of storage expansion? I assume there exists some kind of thunderbolt jbod thing or similar