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☆ Yσɠƚԋσʂ ☆@lemmy.ml to Technology@lemmy.mlEnglish · 1 day ago

If this is true, the hyperscalers are toast

klementoninvesting.substack.com

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If this is true, the hyperscalers are toast

klementoninvesting.substack.com

☆ Yσɠƚԋσʂ ☆@lemmy.ml to Technology@lemmy.mlEnglish · 1 day ago
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  • cross-posted to:
  • technology@midwest.social
In my regular research (behind a paywall), I have been saying for a while that I think the future of AI is not large language models (LLM), but small language models (SLM) run on local desktop computers or even mobile phones.
  • ☆ Yσɠƚԋσʂ ☆@lemmy.mlOP
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    4 hours ago

    If you absolutely need one now, a mac is probably the cheapest way to run them because of the unified memory. With any x86 solution you have to get a separate video card with at least 32gb vram to run a decent local model. However, if you wait a bit then you can probably get a dedicated chip a lot cheaper in the near future https://wccftech.com/alibabas-tsmc-built-5nm-risc-v-chip-xuantie-c950-now-runs-qwen-3-8-27b-model-natively-unlocking-massive-vertical-integration-tailwinds/

    • ShinkanTrain@lemmy.ml
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      4 hours ago

      What about those small prebuilt workstations with Strix/Gorgon Halo chips and big ram pools? Chinese OEMs like Beeline and GMKTec are offering some sleek little boxes. I guess it still technically not unified on a system level, but you allot most of it to VRAM in the BIOS regardless. You can probably get comparable performance with a fraction of the cost.

      • ☆ Yσɠƚԋσʂ ☆@lemmy.mlOP
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        15 minutes ago

        Possibly, I haven’t looked at how easy it is to get your hands on one of those.

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