Apple has new free AI & Machine Learning tools

Apple isn't standing still on AI and machine learning — it has released a free and open-source framework for other AI developers to build on with Apple Silicon.

Even though Apple has publicly been developing Artificial Intelligence tools for years, tools that it is already implementing in the iPhone, the company is regularly perceived to be behind the rest of the industry in AI. That's the power of semantics — because Apple calls it Machine Learning instead of AI, it is believed to not be doing AI enough.

That's even after Tim Cook said that he sees AI as a fundamental technology, or revealedhow long Apple has been working on this.

Apple has decided to take its work to a very specific audience. It's giving away a deep learning (DL) framework that its Machine Learning team has developed.

It's meant to be tested, used, and improved on by other developer groups, whether they say they're working on Machine Learning, or AI.

Just in time for the holidays, we are releasing some new software today from Apple machine learning research.

MLX is an efficient machine learning framework specifically designed for Apple silicon (i.e. your laptop!)

Code: https://t.co/Kbis7IrP80
Docs: https://t.co/CUQb80HGut
— Awni Hannun (@awnihannun) December 5, 2023

"Just in time for the holidays, we are releasing some new software today from Apple machine learning research, says announcement on Twitter/X by Awni Hannum, part of Apple's Machine Learning Research group.

The software, or framework, is called MLX, which Hannum says "is an efficient machine learning framework specifically designed for Apple silicon (i.e. your laptop!)."

"MLX is designed by machine learning researchers for machine learning researchers," says Apple in its MLX documentation. "The framework is intended to be user-friendly, but still efficient to train and deploy models."

More than what this framework gives users, though, is how it is being presented to the world. There was no press release, no announcement, and certainly not a WWDC keynote presentation.

Instead, Apple is contributing to the open source development of AI tools, where developers can see just how the company is far from behind.

"We intend to make it easy for researchers to extend and improve MLX with the goal of quickly exploring new ideas," continued Apple.

The full source code is available on GitHub.

Latest Exclusives

Latest comparisons

18 Comments

discountopinion 108 comments · 9 Years

About 11 months ago

I am so stoked that they did this. AI talent wants open source publishing and this shows Apple being among the leaders in the field.

A taste of positive things to come me thinks.

avon b7 8008 comments · 20 Years

A good move. Somewhat late but better late than never.

I can see a parallel with Huawei (and others) here when in late 2018 Huawei announced the Ascend line of chips and supporting frameworks and made it open source.

They have Mindspore, CANN, Da Vinci Pangu etc and all the hardware to go with it.

Ascend starts with Nano (for things like earbuds) and scales up to cluster systems with thousands of cores.

The question must be then if Apple intends to take that step too and produce (and possibly sell/lease?) a system similar to the Ascend 910 at some point?

It almost seems inevitable.

mpantone 2243 comments · 18 Years

avon b7 said:

A good move. Somewhat late but better late than never.

I can see a parallel with Huawei (and others) here when in late 2018 Huawei announced the Ascend line of chips and supporting frameworks and made it open source.

They have Mindspore, CANN, Da Vinci Pangu etc and all the hardware to go with it.

Ascend starts with Nano (for things like earbuds) and scales up to cluster systems with thousands of cores.

The question must be then if Apple intends to take that step too and produce (and possibly sell/lease?) a system similar to the Ascend 910 at some point?

It almost seems inevitable.

It's a marathon not a sprint and there's no finish line anyhow.

Machine learning/AI is still very much in its infancy, there is plenty of space for multiple players in multiple segments of the market, from mobile devices all the way to supercomputing.

My guess is that Apple will not bring their ML technology as a standalone product to market. They will rather use it to eventually provide broad benefit to their customers and offer differentiation vis-a-vis the competition. They are not interested in selling rackmount devices to stuff into datacenters.

I could conceivably see them rolling their own custom ML silicon for their own servers, optimized for their applications and providing a performance-per-watt advantage over the competition. With the Apple Silicon M3 chip family, they made a major shift to a new GPU architecture that might be a harbinger of this.

Apple does not want to put their chip designs in their competitors' hands.

Remember that Apple's fundamental philosophy is that they are essentially a software company whose code runs best on their proprietary hardware platforms. They do not gain a competitive advantage by shipping trays of Apple Silicon SoCs from TSMC to others.

9secondkox2 3124 comments · 8 Years

avon b7 said:

A good move. Somewhat late but better late than never.

I can see a parallel with Huawei (and others) here when in late 2018 Huawei announced the Ascend line of chips and supporting frameworks and made it open source.

They have Mindspore, CANN, Da Vinci Pangu etc and all the hardware to go with it.

Ascend starts with Nano (for things like earbuds) and scales up to cluster systems with thousands of cores.

The question must be then if Apple intends to take that step too and produce (and possibly sell/lease?) a system similar to the Ascend 910 at some point?

It almost seems inevitable.

Apple doesn’t develop commodity hardware for everyone else to use. They develop hardware and software that coalesces into a tangible, user product for its own customers.

A framework or standard is another thing though as Apple has historically either developed themselves or partnered to develop technologies such as FireWire, QuickTime, thunderbolt, etc. Opening up some of their machine learning (AI) framework seems to be this. It benefits Apple, but also the computing landscape as a whole.

It’s hilarious. While everyone is focused on AI nerd stuff, Apple has already been shopping hyper useful AI in its products. Now if they can just hurry up and finish the new and improved Siri already…

9secondkox2 said:

avon b7 said:

A good move. Somewhat late but better late than never.

I can see a parallel with Huawei (and others) here when in late 2018 Huawei announced the Ascend line of chips and supporting frameworks and made it open source.

They have Mindspore, CANN, Da Vinci Pangu etc and all the hardware to go with it.

Ascend starts with Nano (for things like earbuds) and scales up to cluster systems with thousands of cores.

The question must be then if Apple intends to take that step too and produce (and possibly sell/lease?) a system similar to the Ascend 910 at some point?

It almost seems inevitable.

Apple doesn’t develop commodity hardware for everyone else to use. They develop hardware and software that coalesces into a tangible, user product for its own customers.
A framework or standard is another thing though as Apple has historically either developed themselves or partnered to develop technologies such as FireWire, QuickTime, thunderbolt, etc. Opening up some of their machine learning (AI) framework seems to be this. It benefits Apple, but also the computing landscape as a whole.

It’s hilarious. While everyone is focused on AI nerd stuff, Apple has already been shopping hyper useful AI in its products. Now if they can just hurry up and finish the new and improved Siri already…

There is nothing 'commodity' about an Ascend 910 which costs millions of dollars when used in something like an Atlas system. AFAIK, Apple hasn't shipped anything that others haven't already shipped and yes, Siri is a shortcoming but it's clear that it wasn't a priority for years or else it wouldn't need major improvements.

There are probably more important AI related goals at the moment.