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I would think not. The GPU is a bit part of the equation for compute , and there’s very little in the way of ML libraries targeting the standard graphics APIs a

by dagmx 2y ago

I would think not. The GPU is a bit part of the equation for compute , and there’s very little in the way of ML libraries targeting the standard graphics APIs available on Linux.

talldayo 2y ago
Is that true? Linux is the number one choice for training and inferencing deployment, somebody must be doing something right. It's not like OpenAI was training their LLMs using CoreML, Apple isn't even a contender in the game. They were late to supporting basic industry-standard libraries like Tensorflow and Pytorch, and they still don't commit to an Open, cross-platform alternative. Apple is the #1 loser from the lack of standardization here, and you're trying to make it out as a Linux problem. Imagine if someone from the industry could hear you talking right now.
- hpen 2y ago
  iOS developer here, CoreML is used for edge deployments in the ML space. Just not training. Obviously linux is king but that's for server side my dude.
  - talldayo 2y ago
    "edge deployment" by which you mean client-side application-specific inference. That's not bad, but it's also table-stakes when ONNX/Tensorflow exists and obviously isn't analogous to the server products Nvidia is shipping today. You can "deploy" CoreML the same way Android developers deployed Tensorflow for edge compute 5 years ago, but that wasn't even interesting when people demoed it on Raspberry Pi. Apple is behind.
  - Wowfunhappy 2y ago
    > Obviously linux is king but that's for server side my dude. But isn't that what we're talking about? The submission title is "Apple is developing AI chips for data centers".
    - hpen 2y ago
      Right, "developing"