Like it or not, Apple needs Mac Pro.

[1d1otic]

https://forums.macrumors.com/threads/mac-pro-reportedly-on-back-burner-and-largely-written-off-at-apple.2471279/

Despite that Mac Pro is being on the back burner, Apple will need to develop high-end and/or workstation grade Apple Silicon chips for their own future. I would skip the performance and specs of Macs cause it's gonna be a long conversation despite the fact that Mac's max performance is poor but the most important fact is, they need workstation grade chips to make their own servers for AI.

Take a look at Gemini 3.0. Google trained their own AI with their own chips, TPU. Which means, Apple can also do it as long as they can make their own powerful chips. M3 Ultra? It's extremely slow compared to others especially Nvidia. Furthermore, since Apple Silicon is SoC based, it's too expensive to mass produce especially with ultra-fusion due to the die size. Dont forget that Apple does NOT make chips to sell so they'll need to use chips from Mac, not custom chips just for servers.

Tho Apple is planning to make new chips with a whole new design thanks to TSMC's SoIC, they will need Mac Pro grade Apple Silicon chips one way or another cause in order to compete and improve their Apple Intelligence.

So what Apple is doing with Mac Pro is totally unacceptable.

 

[leman]

Just a few comments on this:

- What makes you think that Apple wants or needs to train models on their own hardware (inference is a different matter)?
- M3 Ultra is slow for ML because it still lacks ML acceleration. M5 Ultra might be less slow.
- The latest macOS beta introduces Infiniband support, which is the protocol Nvidia uses to build large AI clusters. This would allow you to connect multiple Studios together and use them as a distributed ML accelerator at a lower price than an equivalent hypothetical Mac Pro. And it is very possible that this is what Apple will use internally to link multiple Max or Ultra class chips into coherent compute clusters.

 

[!!!]

The Mac Studio is essentially the replacement for the Mac Pro, there's no difference aside from upgradability/extendability.

The problem with Apple's chips in terms of AI is that training requires high-precision GPU-like cores, which apple struggles at (and NVIDIA does not). Apple does have the NE-cores, but they are geared towards running the model, and thus have worse precision and don't have all of the necessary functions for training.

I don't see how the Mac Pro would help, unless Apple gives in and allows NVIDIA/AMD GPUs, or Apple goes on to make their own dedicated GPUs. The SOC model just does not work when you need high performance GPUs, you'll run into thermal limits.

- The latest macOS beta introduces Infiniband support, which is the protocol Nvidia uses to build large AI clusters. This would allow you to connect multiple Studios together and use them as a distributed ML accelerator at a lower price than an equivalent hypothetical Mac Pro. And it is very possible that this is what Apple will use internally to link multiple Max or Ultra class chips into coherent compute clusters.

If Apple were to go as far as designing their own AI compute cluster, using full M-series processors would be a waste, you don't need so many CPU cores. It might be cost-effective to use binned chips with good GPU cores and bad CPU cores, but even then they may as well design a completely custom board/system that can integrate multiple chips in a better way than separate computers. Take a look at NVIDIA's DGX systems, they're essentially a bunch of GPUs with tons of VRAM all plugged into a single powerful CPU.

Basically, Apple could be far more optimized than just plugging in Mac Studios together. In fact, I believe it's probably more profitable for them to sell every M-chip to consumers and just rent out some of Google's TPUs to train with, which is what they're currently doing.