If you've been around Macs long enough this is very much in Apple's wheelhouse. They already do something similar with Final Cut Pro rendering, Logic Pro, Grand Central Dispatch, and XCode distributed CI/CD. Apple HQ is probably sitting on 1000s of nodes, high powered MBPs, iMacs, that could do lots of inference work overnight.

[0] https://en.wikipedia.org/wiki/Grand_Central_Dispatch

[1] https://developer.apple.com/documentation/dispatch

Pardon me not understanding what this is about?

Basically SETI for AI workloads? At least, this is the impression the landingpage left me with.

I am a bit lost, tbh.

As with all similar SETI@home approaches, this paper does not address the energy cost.

Yes, we can distribute tasks to idle machines in homes and on office desktops, but it is often much more expensive than sending it to a data center where power is cheaper and the hardware is more efficient.

I guess for companies this can be nice? Run some inference in the off-hours on the machines that you already have. Could be useful for analytical tasks that don't require to be instant. On the technical side this doesn't seem that groundbreaking for me though.

My warm take is that Apple is leaving a lot of money on the table by not investing in creating an independent supply chain for their chips and building their own cloud. They arguably had the first mover advantage when it came to general purpose arm compute; all they had to do was flood the market and make it easy for anyone to rent it. Not only would they corner a part of the market but perhaps ease demand pressure on other chip manufacturers too.

We did a little demo/have a patent for a similar idea using idle GPUs on Mercedes vehicles once upon a time - https://patents.google.com/patent/US20230281046A1/en

It would be so incredibly cool if we finally had an accessible consumer-accessible way to turn a network of computers on a network into a supercomputer. A household has a child who gets into 3D artwork and wants to render something? People can opt their tablets, phones, laptops, whatever to crunch out some frames overnight while not being used.

I don't get it. In the paper it sounds like it's "just" a CRUD DB, then you have some fleet of Macs, and they store inputs and outputs in S3. What's the innovation here? Not trying to poo on this, but it looked like the most basic and obvious approach.

They'll throw this together but still not sell you something you can stick in a rack ?

That's why the button is on the underside.

There are a lot of parallels between the DGX (and clones) series devices and these Apple devices, maybe it would be possible to rope in the DGX boxes as well. There's lots of them out there and I'm pretty sure not all of them have high utilization.

  Future work will extend Minions to support distributed model training in addition to inference

It would be especially useful for RL post training of existing models, which is where much of the agentic abilities arise from.

I built something very adjacent to this right before leaving Apple, same name, handed off to my team.

I’m very curious if that project evolved to this……..going to message a few friends now heh

This reminds me of this blog post[0] where they intercept calls to the CUDA API from one host to execute them in a separate host, essentially giving GPUs to VMs that have none, and allowing one GPU to serve multiple instances.

[0]: https://loopholelabs.io/blog/ollama-remote-gpu

Paper:

https://arxiv.org/pdf/2610.12970

Shortest promoted paper I've seen from a FAANG.

Would love to build something like this but for classification models that run on CPU. Like a “Classify @ Home” p2p compute network, to which people could contribute their machines and see what work is being done

Building the classification part now :) https://jeffyclassify.com/

Millions of Mac users could make passive income renting out their plugged in GPU and compute...

Interesting, so this is basically Apple's version of exo ? https://github.com/exo-explore/exo

Apple has reinvented cycle scavenging about 40 years later.

It's not a novel idea, but its provable that someone can take this same concept and do something truly groundbreaking. I wonder if there's value in the idea that you can join a supercomputer network of MAC/Nvidia GPUs as a way of getting off cloud and into "our cloud". As long as you offer compute, you have credit into the system to be able to support your own workloads that can't be done on just your hardware. Need to address concerns about privacy, abuse, etc, but Apple's idea here has some merit if applied right.

I remember seeing this at a presentation two or three years ago. I’m surprised it wasn’t rolled out right after?

Why is this a paper? Should've just been a blogpost. Maybe I don't understand academia

If I can get paid for heating my home with LLM queries this winter, I'm all for it.

Apple rediscovering HPC clusters, but without OS X Server to serve alongside it.

Imagine if Apple made a GENERIC distributed compute framework to leverage idle computing power from Macs for distributed Rendering/Compiling/etc use cases. I'm sure Apple could convince Adobe and others to support this framework for their compute-intensive products and create a really interesting ecosystem for it.

Then universities and business could reduce their need for cloud and have a reason to put that spending towards higher end Macs...

Sounds similar to Salad (salad.com), except for the differing hardware.

I’m a bit disappointed in the lack of depth (and use of Ollama): https://arxiv.org/html/2610.12970v1

Apple has released some small models previously that seemed genuinely great, along with some quality research/efforts. I’m just not seeing the same level of depth here, am I missing something?

Darkbloom is already doing that today (darkbloom.ai)

This project sounds good.

What is it actually like?

internal system, so the IT/HR department is the solution to leechers.

nothing new here.

Is this opt-in or opt-out?

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>Apple steals your electicity while you take a dump