141–150 of 1001 posts
512GB unified memory is absolutely wild for AI stuff! Compared to how many NVIDIA GPUs you would need, the pricing looks almost reasonable.
Let's say you want to have the absolute max memory(512GB) to run AI models and let's say that you are O.K. with plugging a drive to archive your model weights then you can get this for a little bit shy of $10K. What a dream machine. Compared to Nvidia's Project DIGITS which is supposed to cost $3K and be available "soon", you can get a specs matching 128GB & 4TB version of this Mac for about $4700 and the difference…
Lots of AI HW is focused on RAM (512GB!). I have a cost-sensitive application that needs speed (300+ TOPS), but only 1GB of RAM. Are there any HW companies focused on that space?
Earlier quoted context omitted.
That’s what’s weird to me too. It’s not like they would lose sales of macOS as it is given away with the hardware. So if someone wants to buy Apple hardware to run Linux, it does not have a negative affect to AAPL
Except the linux users won't be buying Apple software, from the app store or elsewhere. They won't subscribe to iCloud.
Earlier quoted context omitted.
> This hardware is really being held back by the operating system at this point. Please elucidate.
No native docker support, no headless management options (enterprise strength), Limited QoS management, lack of robust python support (out of the box), interactive user focused security model.
Whoa. M3 instead of M4. I wonder if this was basically binning, but I thought that I had read somewhere that the interposer that enabled this for the M1 chips where not available. That Said, 512GB of unified ram with access to the NPU is absolutely a game changer. My guess is that Apple developed this chip for their internal AI efforts, and are now at the point where they are releasing it publicly for others to use.…
Yeah, if only Apple at least semi-supported Linux, their computers would have no competition.
I just want a break from MacOS, I'll be buying a Thinkpad and will probably never come back. This isn't my moaning, I understand it's their market, but if their hardware supported Linux (especially dual booting) or Docker native, I'd probably be buying Apple for the next decade and now I just won't be.
The memory amount is fantastic, memory bandwidth is half decent(~800 GB/s), and the compute capabilities are terrible(36 TOPS). For comparison, a single consumer card like the RTX 5090 is only 32 GB of memory, has 1792 GB/s memory and 3593 TOPS of compute. The use cases will be limited. While you can't run a 600B model directly like Apple says(cause you need more memory for that), you can run a quantized version, but…
It's nice that these devices have loads of memory, but they don't have remotely the necessary level of compute to be competitive in the AI space. As a fun thing to run a local LLM as a hobbyist, sure, but this presents zero threat to nvidia.
Apple hardware is irrelevant in the AI space, outside of making YouTube "I ran a quantized LLM on my 128GB Mac Mini" type content for clicks, and this release doesn't change that.
Looks like a great desktop chip though.
It would be nice if nvidia could start giving their less expensive offerings more memory, though they're currently in the realm Intel was 15 yearsago, thinking that their biggest competition is themselves.
> support for more than half a terabyte of unified memory — the most ever in a personal computer AMD Ryzen Threadripper PRO 3995WX released over four years ago and supports 2TB (64c/128t) > Take your workstation's performance to the next level with the AMD Ryzen Threadripper PRO 3995WX 2.7 GHz 64-Core sWRX8 Processor. Built using the 7nm Zen Core architecture with the sWRX8 socket, this processor is designed to deliv…
8 channels at 3200 MT/s (1600 MHz) is only 204.8 GB/sec; less than a quarter of what the M3 Ultra can do. It's also not GPU-addressable, meaning it's not actually unified memory at all.