Comment on Even Apple finally admits that 8GB RAM isn't enough

• rockSlayer@lemmy.world ⁨4⁩ ⁨months⁩ ago

  That’s extremely dependent on the use case, but in my opinion, generally no. However CAMM has been released as an official JEDEC interface and does a good job at being a middle ground between repairability and speed.

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  • halcyoncmdr@lemmy.world ⁨4⁩ ⁨months⁩ ago

    It’s an officially recognized spec, so Apple will ignore it as long as they can. Until they can find a way to make money from it or spin marketing as if it’s some miraculous new invention of theirs, for something that should just be how it’s done.

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    • umami_wasbi@lemmy.ml ⁨4⁩ ⁨months⁩ ago

      Parts pairing will do. That’s what Apple known for, knee capping consumer rights.

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• BorgDrone@lemmy.one ⁨4⁩ ⁨months⁩ ago

  Yes, there are massive advantages. It’s basically what makes unified memory possible on modern Macs. Especially with all the interest in AI nowadays, you really don’t want a machine with a discrete GPU/VRAM, a discrete NPU, etc.

  Take for example a modern high-end PC with an RTX 4090. Those only have 24GB VRAM and that VRAM is only accessible through the (relatively slow) PCIe bus. AI models can get really big, and 24GB can be too little for the bigger models. You can spec an M2 Ultra with 192GB RAM and almost all of it is accessible by the GPU directly. Even better, the GPU can access that without any need for copying data back and forth over the PCIe bus, so literally 0 overhead.

  The advantages of this multiply when you have more dedicated silicon. For example: if you have an NPU, that can use the same memory pool and access the same shared data as the CPU and GPU with no overhead. The M series also have dedicated video encoder/decoder hardware, which again can access the unified memory with zero overhead.

  For example: you could have an application that replaces the background on a video using AI. It takes a video, decompresses it using the video decoder , the decompressed video frames are immediately available to all other components. The GPU can then be used to pre-process the frames, the NPU can use the processed frames as input to some AI model and generate a new frame and the video encoder can immediately access that result and compress it into a new video file.

  The overhead of just copying data for such an operation on a system with non-unified memory would be huge. That’s why I think that the AI revolution is going to be one of the driving factors in killing systems with non-unified memory architectures, at least for end-user devices.

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  • vaultdweller013@sh.itjust.works ⁨4⁩ ⁨months⁩ ago

    I feel like this is an arguement for new specialized computers at best. At worst it shows that this AI crap is even more harmful to the end user.

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  • neo2478@sh.itjust.works ⁨4⁩ ⁨months⁩ ago

    That’s a fantastic explanation! Thank you!

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  • dustyData@lemmy.world ⁨4⁩ ⁨months⁩ ago

    Bus goes Vrrrroom vrrooom. Fuck AI.

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• FarraigePlaisteach@lemmy.world ⁨4⁩ ⁨months⁩ ago

  And even if the out-of-the-box RAM is soldered to the machine, it should still be possible to add supplementary RAM that isn’t soldered for when the system demands it. Other computers have worked like this in the past with chip RAM but a socket to add more.

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• gravitas_deficiency@sh.itjust.works ⁨4⁩ ⁨months⁩ ago

  It’s highly dependent on the application.

  For instance, I could absolutely see having certain models with LPCAMM expandability as a great move for Apple, particularly in the pro segment, so they’re not capped by whatever they can cram into their monolithic SoCs. But for most consumer (that is, non-engineer/non-developer users) applications, I don’t see them making it expandable.

  Or more succinctly: they should absolutely put LPCAMM in the next generation of MBPs, in my opinion.

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