• AA5B@lemmy.world
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    2 hours ago

    Remember this is “unified”, it’s not like you can upgrade, nor is it available in the “cheap” packaging we’re used to.

    You’ll get whatever Apple puts on the SoC, and you’ll be happy with it

    • eicker@lemmy.world
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      2 hours ago

      The upside is that unified memory is genuinely different from traditional RAM. The CPU, GPU and Neural Engine all share the same memory pool, so data doesn’t need to be copied back and forth. That reduces latency, improves efficiency and lets AI models, graphics and other workloads access much larger datasets. It also uses less power and saves board space. The downside is obvious: because it’s integrated into the chip, you have to choose the right amount upfront, since it can’t be upgraded later.

      • NotMyOldRedditName@lemmy.world
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        1 hour ago

        Ya, these high memory amounts and ever increasing memory bandwidth are heavily (but not only) targeting people wanting to run local large AI models like a full deepseek on their machines.

        You might not be able to train as well on them as NVIDIA + CUDA, but for local inference, they’re an alternative to NVIDIA and more reasonably priced for the model sizes you can run, and each iteration they get better as the bandwidth increases.