751–760 of 1001 posts
Its really saying something about how the tech sector has shifted due to the recent AI wave that Apple is announcing a chipset entirely apart from a product. This has never happened to my knowledge in this companies history? I could be wrong though, even the G3/G4s were launched as PowerMacs.
"With these improvements to the CPU and GPU, M4 maintains Apple silicon’s industry-leading performance per watt. M4 can deliver the same performance as M2 using just half the power. And compared with the latest PC chip in a thin and light laptop, M4 can deliver the same performance using just a fourth of the power." That's an incredible improvement in just a few years. I wonder how much of that is Apple engineering a…
Apple usually massively exaggerates their tech spec comparison - is it REALLY half the power use of all times (so we'll get double the battery life) or is it half the power use in some scenarios (so we'll get like... 15% more battery life total) ?
If Apple ever decides to pivot business to chip manufacturing that allows open access and sale. Then I would revisit.
Always need competition in this space. Especially for low power cpu/gpus.
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 think it will be a winning strategy. Lag is a real killer for LLMs. I think they'll have another LLM on a server (maybe a deal for openai/gemini) that the one on the device can use like ChatGPT uses plugins. But on device Apple have a gigantic advantage. Rabbit and Humane are good ideas humbled by shitty hardware that runs out of battery, gets too hot, has to connect to the internet to do literally anything. Apple…
I'm curious to hear more about this. My experience has been that inference speeds are the #1 cause of delay by orders of magnitude, and I'd assume those won't go down substantially on edge devices because the cloud will be getting faster at approximately the same rate.
Have people outside the US benchmarked OpenAI's response times and found network lag to be a substantial contributor to slowness?
Earlier quoted context omitted.
Didn't have to look long to find a comment mirroring how I feel about these devices. To me it feels like they're just adding power to an artificially castrated device I can barely do anything with. See no reason to upgrade from my original iPad Pro that's not really useful for anything. Just an overpowered device running phone software.
I feel the same way. I just can't justify upgrading from my 10.5" Pro from years ago. It's got pro motion and runs most apps fine. Sure, the battery isn't great after all these years, but it's not like it's getting used long enough to notice.
Even a good battery isn’t that good. That seems to be a software problem.
My only theory is it’s turning on the screen every time it gets a notification. However, I have a case that covers the screen, which should keep the screen off in my opinion. I have thought about disabling 100% of the notification, but without a global toggle that seems pretty annoying to do.
M2's Neural Engine had 15TOPS, M3's 18TOPS (+20%) vs. M4's 38TOPS (+111%). In transistor counts, M2 had 20BTr, M3 25BTr (+25%) and M4 has 28BTr (+12%). M2 used TSMC N5P (138MTr/mm2), M3 used TSMC N3 (197MTr/mm2, +43%) and M4 uses TSMC N3E (215MTr/mm2, +9%).[1][2] [1] https://en.wikipedia.org/wiki/5_nm_process#%225_nm%22_proces... [2] https://en.wikipedia.org/wiki/3_nm_process#%223_nm%22_proces...
An NVIDIA RTX 4090 generates 73 TFLOPS. This iPad gives you nearly half that. The memory bandwidth of 120 GBps is roughly 1/10th of the NVIDIA hardware, but who’s counting!
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…
Make no mistake, they're just waiting for the right MBA to walk through the door, see the sky high value of their users and start chop shopping that.
Enshitiffication is always available to the next CEO, and this is just going to be more and more tempting as the value of the walled garden increases.
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…
> 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 data up to the cloud for processing). Their primary business goal is to sell hardware. Yes, they’ve diversified into services and being a shopping mall for all, but it is about selling lu…
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…
> 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 data up to the cloud for processing). Their primary business goal is to sell hardware. Yes, they’ve diversified into services and being a shopping mall for all, but it is about selling lu…
The important is that a good starting ai learning platform is what … most apple does not touch those price.
Hence with privacy it is a good path.
You do not want communism even if it is not expensive in the short term.
Earlier quoted context omitted.
> 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 data up to the cloud for processing). Their primary business goal is to sell hardware. Yes, they’ve diversified into services and being a shopping mall for all, but it is about selling lu…
> > 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 data up to the cloud for processing). > Their primary business goal is to sell hardware. There is no contradiction here. No need for luxury. Efficient hardware scales, Moore's law has j…