61–70 of 114 posts
i am more excited about the ondevice foundation model update that is coming https://developer.apple.com/documentation/updates/foundation... (not much info yet) but i maintain https://github.com/Arthur-Ficial/apfel so i might be biased
Have you seen that they've added an `fm` tool? It was mentioned in the Platforms State of the Union. Here's what you get when you run it... https://gist.github.com/robgough/7893602895e7580117475076198...
Wow, this seems to be a new way to convert PyTorch models to a format that runs across CPU, GPU & Apple's Neural Engine (ANE). [0] Does this completely replace the previous API, CoreML? [1] [0]: https://apple.github.io/coreai-optimization/ [1]: https://developer.apple.com/documentation/coreml/
This is just a bit exciting, although I wonder how the performance of this will stack up next to the stuff we already do with, e.g., a metal-optimised model which we then load into llama-cpp or whatever. (unsloth is a good example of doing this for you "batteries included").
- https://maderix.substack.com/p/inside-the-m4-apple-neural-en...
Earlier quoted context omitted.
Those are not GPUs available on iPhones. Will we get there eventually? Maybe! Maybe we end up with GPU clusters built on the edge (e.g. cell towers) for offloading, maybe it’s never economical, maybe a different model architecture makes it simpler, who knows. But it doesn’t seem anywhere imminent with our current world state.
My computer is 15,000 times faster and costs in inflation adjusted dollars half that of my computer in 1995. There's zero reason to think that won't happen over the next 30 years again. For whatever reason every generations thinks they are the peak. Naw man. You're just a blip at the bottom of the logarithmic chart.
Earlier quoted context omitted.
seems they planning to replace it but overall now I'm really confused about this and mlx and coremltools. They should do better work explaining the benefits (and cons) of it and any feature parity between coreai, coreml and mlx.
My reading of it is: - Core ML is for models designed only for Apple platforms - MLX is for models that don't need to be fast - Core AI is for models that run everywhere already and also need to be fast
MLX is not for end user deployment.
Does it mean I can run whatever I want on ANE? Last time I tried it seemed it could only be used by first party features such as Face ID
Free server-size model access for apps with https://developer.apple.com/private-cloud-compute/
i am more excited about the ondevice foundation model update that is coming https://developer.apple.com/documentation/updates/foundation... (not much info yet) but i maintain https://github.com/Arthur-Ficial/apfel so i might be biased
Have you seen that they've added an `fm` tool? It was mentioned in the Platforms State of the Union. Here's what you get when you run it... https://gist.github.com/robgough/7893602895e7580117475076198...
i am more excited about the ondevice foundation model update that is coming https://developer.apple.com/documentation/updates/foundation... (not much info yet) but i maintain https://github.com/Arthur-Ficial/apfel so i might be biased
I also really want to hear more about their containerisation/seatbelt strategy now that they are offering MCP support. Not seen any news about Darwin inside their containers system.
(Apfel is a cool project; it’s been the only thing tempting me to upgrade to Tahoe)
i am more excited about the ondevice foundation model update that is coming https://developer.apple.com/documentation/updates/foundation... (not much info yet) but i maintain https://github.com/Arthur-Ficial/apfel so i might be biased
Have you seen that they've added an `fm` tool? It was mentioned in the Platforms State of the Union. Here's what you get when you run it... https://gist.github.com/robgough/7893602895e7580117475076198...