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Apple introduces M4 chip

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Re: Apple introduces M4 chip

#641

Post by Aerbil313 »

paulpan wrote: post #183
EduardoBautista wrote: post #13

The 256gb and 512gb models have 8gb of ram. The 1tb and 2tb models have 16gb. Not a fan of tying ram to storage. https://www.apple.com/ipad-pro/specs/

I don't think it's strictly for price gouging/segmentation purposes. On the Macbooks (running MacOS), RAM has been used as data cache to speed up data read/write performance until the actual SSD storage operation completes. It makes sense for Apple to account for with higher RAM spec for the 1TB/2TB configurations.

Do people not understand that Apple's 'price gouging' is about UX? A person who has the money to buy a 1TB iPad is worth more than average customer. A 16GB RAM doubtlessly results in a faster UX and that person is more likely to continue purchasing.

Re: Apple introduces M4 chip

#642

Post by its_ethan »

MyFirstSass wrote: post #571
littlestymaar wrote: post #566

Earlier quoted context omitted.

> 8gb of ram. WTF? Why so little? That's insane to me, that's the amount of RAM you get with a mid-range android phone.

We've reached a point where their chips has become so amazing they have to introduce "fake scarcity" and "fake limits" to sell their pro lines, while dividing their customers into haves and havenots, while actively stalling the entire field for the masses.

You could, alternatively, read less malice into the situation and realize that the majority of people buying an iPad pro don't even need 8gb of RAM to do what they want to do with the device (web browsing + video streaming).

Re: Apple introduces M4 chip

#643

Post by w1nst0nsm1th »

rsp1984 wrote: post #457

Together with next-generation ML accelerators in the CPU, the high-performance GPU, and higher-bandwidth unified memory, the Neural Engine makes M4 an outrageously powerful chip for AI. In case it is not abundantly clear by now: Apple's AI strategy is to put inference (and longer term even learning) on edge devices. This is completely coherent with their privacy-first strategy (which would be at odds with sending dat…

> to put inference on edge devices...

It will take a long time before you can put performant inference on edge device.

Just download one of the various open source large(st) langage model and test it on your desktop...

Compute power and memory and storage requirements are insane if you want decent result... I mean not just Llama gibberish.

Until such requirement are satisfied, distant model are the way to go, at least for conversational model.

Aside llm, AlphaGo would not run on any end user device, by a long shot, even if it is an already 'old' technology.

I think 'neural engine' on end user device is just marketing nonsense at this current state of the art.

Re: Apple introduces M4 chip

#644

Post by asadotzler »

pxc wrote: post #55

Given that recent Apple laptops already have solid all-day battery life, with such a big performance per watt improvement, I wonder if they'll end up reducing how much battery any laptops ship with to make them lighter.

No, because battery life isn't just about the CPU. The CPU sits idle most of the time and when it's not idle, it's at workloads like 20% or whatever. It's the screens that eat batteries because they're on most or all of the time and sucking juice. Look at Apple's docs and you'll see the battery life is the exact same as the previous model. They have a battery budget and if they save 10% on CPU, they give that 10% to a better screen or something. They can't shrink the battery by half until they make screens twice as efficient, not CPUs which account for only a small fraction of power draw.

Re: Apple introduces M4 chip

#645

Post by tweetle_beetle »

rsp1984 wrote: post #457

Together with next-generation ML accelerators in the CPU, the high-performance GPU, and higher-bandwidth unified memory, the Neural Engine makes M4 an outrageously powerful chip for AI. In case it is not abundantly clear by now: Apple's AI strategy is to put inference (and longer term even learning) on edge devices. This is completely coherent with their privacy-first strategy (which would be at odds with sending dat…

I wonder if BYOE (bring your own electricity) also plays a part in their long term vision? Data centres are expensive in terms of hardware, staffing and energy. Externalising this cost to customers saves money, but also helps to paint a green(washing) narrative. It's more meaningful to more people to say they've cut their energy consumption by x than to say they have a better server obselesence strategy, for example.

Re: Apple introduces M4 chip

#646

Post by aborsy »

rsp1984 wrote: post #457

Together with next-generation ML accelerators in the CPU, the high-performance GPU, and higher-bandwidth unified memory, the Neural Engine makes M4 an outrageously powerful chip for AI. In case it is not abundantly clear by now: Apple's AI strategy is to put inference (and longer term even learning) on edge devices. This is completely coherent with their privacy-first strategy (which would be at odds with sending dat…

What are the example of the edge devices made by Apple?

Re: Apple introduces M4 chip

#647

Post by _ph_ »

therealmarv wrote: post #325

So why should I buy any Apple Laptop with M3 chip now (if I'm not in hurry)? lol

If you are not in a hurry, you almost never should buy new hardware as the next generation will be around the corner. On the other side, it could be up to 12 months, until the M4 is available across the line. And for most tasks, a M3 is a great value too. One might watch how many AI features that would benefit from a M4 are presented at WWDC. But then, the next Mac OS release won't be out before October.

Re: Apple introduces M4 chip

#648

Post by SpaceManNabs »

nomel wrote: post #570
SpaceManNabs wrote: post #551

Earlier quoted context omitted.

This comment is odd. I wouldn't say it is misleading, but it is odd because it borders on such definition. > Apple's AI strategy is to put inference (and longer term even learning) on edge devices This is pretty much everyone's strategy. Model distillation is huge because of this. This goes in line with federated learning. This goes in line with model pruning too. And parameter efficient tuning and fine tuning and pr…

> This is pretty much everyone's strategy. I think this is being too charitable on the state of "everyone". It's everyone's goal . Apple is actively achieving that goal, with their many year strategy of in house silicon/features.

> Apple is actively achieving that goal, with their many year strategy of in house silicon/features

So are other companies, with their many year strategy of actually building models that accessible to the public.

yet Apple is "actively" achieving the goal without any distinct models.

Re: Apple introduces M4 chip

#649

Post by gopher_space »

alfalfasprout wrote: post #499
joelthelion wrote: post #461

Earlier quoted context omitted.

>n case it is not abundantly clear by now: Apple's AI strategy is to put inference (and longer term even learning) I'm curious: is anyone seriously using apple hardware to train Ai models at the moment? Obviously not the big players, but I imagine it might be a viable option for Ai engineers in smaller, less ambitious companies.

Not really (I work on AI/ML Infrastructure at a well known tech company and talk regularly w/ our peer companies). That said, inference on apple products is a different story. There's definitely interest in inference on the edge. So far though, nearly everyone is still opting for inference in the cloud for two reasons: 1. There's a lot of extra work involved in getting ML/AI models ready for mobile inference. And thi…

A cloud solution I looked at a few years ago could be replicated (poorly) in your browser today. In my mind the question has become one of determining when my model is useful enough to detach from the cloud, not whether that should happen.
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