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I disagree. Apple is selling hardware and scaling AI by utilizing it is simply a smart move. Instead of building huge GPU clusters, having to deal with NVIDIA
by _the_inflator 2y ago
I disagree.
Apple is selling hardware and scaling AI by utilizing it is simply a smart move.
Instead of building huge GPU clusters, having to deal with NVIDIA for GOUs (Apple kicked NVIDIA out years ago because of disagreements), Apple is building mainly on existing hardware.
This is in other terms utilizing CPU power.
On the other hand this helps their marketing keeping high price points when Apple now is going to differentiate their COU power and therefore hardware prices over AI functionality correlating with CPU power. This is also consistent with Apple stopping the MHz comparisons years ago.
- klabb3 2y agoDid you reply to the right comment? Feels like we’re talking about different things altogether.
- bingbingbing777 2y agoWhat AI is Apple scaling?
- bionhoward 2y agoSeen MLX folks post on X about nice results running local LLMs. https://github.com/ml-explore/mlx https://github.com/ml-explore/mlx Also, Siri, and consider: you’re scaling AI on apple’s hardware, too, you can develop your own local custom AI on it, there’s more memory available for linear algebra in a maxed out MBP than the biggest GPUs you can buy. They scale the VRAM capacity with unified memory and that plus a ton of software is enough to make the Apple stuff plenty competitive with the corresponding NVIDIA stuff for the specific task of running big AI models locally.
- Wytwwww 2y ago> there’s more memory available for linear algebra in a maxed out MBP than the biggest GPUs you can buy. But this hardly applies to 95% if not more people of all people running Apple's hardware, the fastest CPU/GPU isn't worth much if you can fit any at least marginally useful LLM model on the 8GB (or less on iPhones/iPads) of memory that you device has?