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I thought the news of them using Apple Silicon rather than NVIDIA in their data centers was significant. Perhaps there is still hope of a relaunch of xserve; w
by throwaway4good 2y ago
I thought the news of them using Apple Silicon rather than NVIDIA in their data centers was significant.
Perhaps there is still hope of a relaunch of xserve; with the widespread use of Apple computers amongst developers Apple has a real chance of challenging NVIDIA's CUDA moat.
- pjmlp 2y agoNot at Apple's price points.
- throwaway4good 2y agoI think NVIDIA has the highest hardware markup at the moment.
- pjmlp 2y agoDepends on which card one is talking about.
- bayindirh 2y ago[flagged]
- throwaway4good 2y agoMaybe. It is not really obvious how much you for the AI accellerator part of their offerings. For example the chips in iPhones are quite powerful even adjusted for price. However for some cases - like the max chip in the macbooks or the extra ram - their pricing seems high - maybe even nvidia high.
- Hugsun 2y agoYou get considerably more ML FLOPS per dollar in a 4090 than any mac. It seems like the base M2 MAX is at roughly the same price point. It does grant you more RAM. Quadro and Tesla cards might be a different story. I would still like to see concrete FLOPS/$ numbers.
- throwaway4good 2y agoThe M2 is a chip designed to be in a laptop (and it is quite powerful given its low power consumption). Presumedly they have a different chip or at least completely different configuration (RAM, network, etc.) in their data centers.
- mrweasel 2y agoThe interesting point here is that developers targeting the Mac can safely assume that the users will have a processor capable of significant AI/ML workloads. On the Windows (and Linux) side of things, there's no common platform, no assumption that the users will have an NPU or GPU capable of doing what you want. I think that's also why Microsoft was initially going for the ARM laptops, where they'd be sure that the required processing power is available.
- qwytw 2y ago> The interesting point here is that developers targeting the Mac can safely assume that the users will have a processor capable of significant AI/ML workloads Also that a significant proportion (majority?) of them will have just 8 GB of memory which is not exactly sufficient to run any complex AI/ML workloads.
- talldayo 2y agoEasy solution; just swap multiple gigabytes of your model to SSD-based ZRAM when you run out of memory. What could possibly go wrong?
- sofixa 2y ago
- bayindirh 2y agoI mean, even Apple can't match the markups nVidia has right now. If you break a GPU in your compute server, you wait months for a replacement, and the part is sent back if you can't replace it in five days. Crazy times.
- grecy 2y agoI'm wondering how my electricity they will save just from moving from Intel to Apple Silicon in their data centers.