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Posted by antipaul 1 day ago

Apple ML Research: Muse Spark Open with MLX on Mac Studio(machinelearning.apple.com)
359 points | 193 commentspage 2
wslh 6 hours ago|
Am I right that investing in your own ML hardware only makes sense when you are dealing with private data and confidential sessions, right? (Not counting development or tinkering work).
nico 1 day ago||
Very cool

Has anyone adapted the open Muse model to work like a decision model?

Sort of like Laya but based on muse spark

_pdp_ 1 day ago||
I am super excited about this.

While right now Mac Studio is not a budget device and it certainly costs more than the subsidised subscription, the promise that one day we can run these models on commodity hardware is exciting.

macinjosh 19 hours ago||
Many thought Apple should be competing with the frontier labs while they see themselves as competing with Nvidia.
bigyabai 8 hours ago|
Right now, they're competing with neither.
AndrewKemendo 1 day ago||
Anyone know why they went with Meta models?
bigyabai 1 day ago|
Apple has too many arbitrary, pointless grudges for Ternus to take them all seriously.

Google partnership for Apple Intelligence, Meta partnership for local models, and allegedly NVLink Fusion support for M8 GPUs. Maybe the White House told him that it's time to start burying hatchets. I don't get the impression that Apple's prior AI strategy under Cook made any real progress.

Danox 18 hours ago|||
Not pointless, all of that led to Apple Silicon, and you seem to be ignoring the fact that it’s not costing Apple any money. None of their hookups. This so-called cooperation is costing Apple a dime. But it is costing the other side billions of dollars.

Smile, the models are getting smaller and better, every generation of Apple Silicon is getting better in the opposite direction. The only problem is the cost of memory and that is within the design engineering ability in-house it is also within their financial capacity, so if I’m John or Tim, I too would wake up with a smile because I can fix the one thing that’s giving us trouble memory because we have the talent and the money to fix it in the next four years.

bigyabai 16 hours ago||
Apple Silicon copied AMD's mistake. RDNA and Apple Silicon are both the slowest GPU architecture for AI because they spent 6 years optimizing raster performance over compute. Now there's 4 generations of Apple Silicon Macs that rely on compute shaders for any kind of efficient inference. Even the M5 GPU is less programmable than Nvidia's ARM GPUs from 2017.

ARM datacenters were a trillion-dollar market that Apple made ~$0 off of. The Mac Pro could have fit that niche, but Tim Cook chose to depreciate it instead of letting the PCIe connectors be used with Nvidia cards. He cut off Apple's nose to spite Nvidia's face. It's nonsense, especially since they're crawling back to Nvidia to license their interconnect, in tacit recognition that it wasn't a real grudge in the first place. My guess is that Ternus doesn't have Tim's money allergy, maybe at the White House's request. In any case, the grudge is over, and Apple forfeit ARM HPC altogether.

> because I can fix the one thing that’s giving us trouble memory because we have the talent and the money to fix it in the next four years.

By all means, continue. Which X account or YouTube channel convinced you that Apple could replace SK Hynix in 4 years?

pjmlp 16 hours ago||
Yes, the traditional Mac Pro customer now has pivoted to Windows or some Linux powered enterprise workstation powered by Ubuntu, Red-Hat, SuSE.
AndrewKemendo 1 day ago|||
That makes sense I also assume there’s better allyship with Meta than X long term geopolitically and they are already in bed with google on search

openai and anthropic are too chaotic to bet on would be my guess

isodev 1 day ago||
Preparing to upsell those very expensive Macs coming later this month, are we.
butterlesstoast 1 day ago|
I -- love -- an article -- full of -- em -- dashes.
shagie 1 day ago||
If you type the following into Microsoft Word:

> In this post, we will show how to run the latest frontier-class model - Muse Spark Open, with nearly a trillion parameters - right from your desk, using the latest version of MLX, released today.

You will get

> In this post, we will show how to run the latest frontier-class model – Muse Spark Open, with nearly a trillion parameters – right from your desk, using the latest version of MLX, released today.

Not everything with em dashes is the product of generative AI... some of it is the word processor correctly following the rules of grammar and punctuation.

NekkoDroid 1 day ago||
Do note that those are en-dashes and not em-dashes.
ManuelKiessling 1 day ago|||
If used correctly, I find the em dash one of the most elegant and reader-friendly ways to structure certain parts of a text — that it got such a bad reputation lately really is a shame!
jonathaneunice 1 day ago||
Em dashes—love ’em!—but they do. not. need. personal. space.