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Wonder what kind of tech they’ll be using on the server side to develop all those services.

• mousetree 2y ago
  Swift perhaps
• zitterbewegung 2y ago
  Tensorflow and PyTorch have been ported to use the accelerators on the M series of chips and they could just be deploying Mac Pros that are rack mounted. So Python.
  • amelius 2y ago
    Will they be using the ports that have been painstakingly made by open-source enthusiasts without having access to official Apple documentation?
    • kristjansson 2y ago
      I’m pretty sure you’re thinking about the work on the open source GPU driver. AFAIK Apple contributed the MPS backend for pytorch and tensorflow-metal PluggableDevice.
    • coldtea 2y ago
      They often work with the community in helping the ports for a lot of these projects, it's just not publicized as much (and often their engineers aren't allowed to talk about it). E.g. when Apple Silicon was released there were people in various FOSS projects who worked with Apple assistance for porting. Here's an example that comes to mind: "In collaboration with the Metal engineering team at Apple, we are excited to announce support for GPU-accelerated PyTorch training on Mac." https://pytorch.org/blog/introducing-accelerated-pytorch-training-on-mac/ https://pytorch.org/blog/introducing-accelerated-pytorch-tra...
  • bitcrusher 2y ago
    It's been a few years but when I was there, Apple had an almost frothingly EXTREME policy against using ANYTHING from Google, most especially Tensorflow. Things may have changed in the last few years but I would not be surprised if that were still the case.
    • zitterbewegung 2y ago
      https://developer.apple.com/metal/tensorflow-plugin/ https://developer.apple.com/metal/tensorflow-plugin/
• re-thc 2y ago
  iAI
  • bearjaws 2y ago
    Pronounced for the poor team working on it "Aye yai yai".
  • toxican 2y ago
    Coincidentally I just installed Windows 7 on an old ThinkPad from 2009 today. Nice to see some jokes from that era too!
• cayleyh 2y ago
  Some likely candidates are the existing open source tools their ML team has released, most of which either use PyTorch or are usable via PyTorch: - CoreNet, a training toolchain developed by their ML teams: https://github.com/apple/corenet https://github.com/apple/corenet. It's built on PyTorch, but uses MLX - MLX, Apples internal array processing framework which is C/C++/Swift (https://pypi.org/project/mlx/ https://pypi.org/project/mlx/). - CoreML tools, their python package for accessing the lower-level CoreML APIs (https://github.com/apple/coremltools https://github.com/apple/coremltools)