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Is this a joke? Seriously, look at the competitors: - Google, who had been developing and distributing Tensorflow and Tensorflow-based hardware for computer v
by smoldesu 3y ago
Is this a joke?
Seriously, look at the competitors:
- Google, who had been developing and distributing Tensorflow and Tensorflow-based hardware for computer vision and early transformer models before "CoreML" even existed, let alone shipped.
- Facebook, who wrote and distributed Pytorch, and trained + released Llama before an Apple press release even uttered "LLM". They also ship dozens of AI-powered features on the server-side and locally on Quest.
- Nvidia, who had been shipping 192gb+ systems for over a decade, as well as researching GANs, LLMs and Neural Nets and putting those features in CUDA as early as 2014.
- Microsoft, who not only wrote their own CoreML-styled API (Olive/DirectML), but actually maintains a cross-platform AI toolkit with ONNX.
...and Apple, the least-vocal company WRT AI is somehow the one that predicted LLMs with the release of an iterative product update? You'd have better evidence if you backed this up with astrology or gematria.
> And remember: llama.cpp is not even taking full advantage of the modern APIs Apple announced
Because as-is, CoreML does not have the features required to run GGML models out-of-the-box.
Suffice to say nobody is really investing in Apple for their ML potential. If you wanna catch falling knives though, be my guest.
- behnamoh 3y agoIs this a joke? None of the companies that you mentioned have any incentive to let users run local LLMs. And Facebook/Meta doesn't make hardware (GPU) in case you didn't know.
- smoldesu 3y agoRegardless of incentive; every company I just mentioned already does more to let users run LLMs than Apple. Google wrote Tensorflow, Meta designed Pytorch, Nvidia wrote CUDA and the fundamental AI papers, and Microsoft distributes ONNX. By comparison, Apple... - Doesn't support PCIe inferencing hardware - Refuses to sign their competitor's drivers - Ships a neural engine they ignore for significant tasks - Doubled-down on the proprietary CoreML API and model format - Cut funding for OpenCL, their original Open Source GPGPU effort - Doesn't provide Open Source GPU compute primatives for their own GPU hardware - Actively ignores efforts to Open Source said hardware with better Open Source drivers - Continues converting models to their own format instead of fixing Apple hardware as a compute target ...and you mean to tell me that the M2 "predicted" LLMs? By supporting more memory? Apple was the last company out of everyone mentioned that even started working with AI. It's fine if you enjoy your Apple Silicon Mac, but it no more "predicted the rise of local LLMs" than AVX and SSE did in 1999. You made no effort to correlate the two ideas, and Apple's antagonistic role in open standards development kinda offsets whatever slight victory you can claim. Even Nvidia does more for local LLM development, and that's sad.