221–230 of 722 posts
Who is the target audience for this? Well informed gamers know Intel's discrete GPU is hanging by a thread, so they're not hoping on that bandwagon. Too small for ML. The only people really happy seem to be the ones buying it for transcoding and I can't imagine there is a huge market of people going "I need to go buy a card for AV1 encoding".
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They are probably held back by same reason thats preventing AMD and nVidia from doing it either.
NVidia and AMD make $$$ on datacenter GPUs so it makes sense they don't want to discount their own high-end. Intel has nothing there so they can happily go for commodization of AI hardware like what Meta did when releasing LLaMA to the wild.
Who is the target audience for this? Well informed gamers know Intel's discrete GPU is hanging by a thread, so they're not hoping on that bandwagon. Too small for ML. The only people really happy seem to be the ones buying it for transcoding and I can't imagine there is a huge market of people going "I need to go buy a card for AV1 encoding".
Had this been available a few weeks ago I would have gone through the pain of early adoption. Sadly it wasn't just an upgrade build for me, so I didn't have the luxury of waiting.
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Nvidia's $30,000 is a 90% margin product at scale. They could charge 1/3 that and still be very profitable. There has rarely been such a profitable large corporation in terms of the combo of profit & margin. Their last quarter was $35b in sales and $26b in gross profit ($21.8b op income; 62% op income margin vs sales). Visa is notorious for their extreme margin (66% op income margin vs sales) due to being basically a…
> And indeed that's exactly what will be required for any serious attempt to cut into their monopoly position. You misunderstand why and how Nvidia is a monopoly. Many companies make GPUs, and all those GPUs can be used for computation if you develop compute shaders for them. This part is not the problem, you can already go buy cheaper hardware that outperforms Nvidia if price is your only concern. Software is the is…
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They all look like amusement parks nowadays.
Also, RGB means RGB... just set the color to white for a more clean look? But reading the manual is not for you.
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Just how "basic" do you think a GPU can be while having the capability to interface with that much DRAM? Getting there with GDDR6 would require a really wide memory bus even if you could get it to operate with multiple ranks. Getting to 128GB with LPDDR5x would be possible with the 256-bit bus width they used on the top parts of the last generation, but would result in having half the bandwidth of an already mediocre…
What if they put 8 identical GPUs in the package, each with 1/8 the memory? Would that be a useful configuration for a modern LLM?
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M3/M4 Max MacBooks with 128GB RAM are already way better than an A6000 for very large local LLMs. So even if the GPU is as slow as the one in M3/M4 Max (<3070), and using some basic RAM like LPDDR5x it would still be way faster than anything from NVidia.
The M4 Max needs an enormous 512bit memory bus to extract enough bandwidth out of those LPDDR5x chips, while the GPUs that Intel just launched are 192/160bit and even flagships rarely exceed 384bit. They can't just slap more memory on the board, they would need to dedicate significantly more silicon area to memory IO and drive up the cost of the part, assuming their architecture would even scale that wide without hit…
Too late, and it has a bad rep. This effort from Intel to sell discrete GPUs is just inertia from old aspirations, won't really help noticeably to save it, as there is not much money in it. Most probably the whole Intel ARC effort will be mothballed, and probably many more will.
What's the alternative? I think it's the right call since there isn't much competition in GPU industry anyway. Sure, Intel is far behind. But they need to start somewhere in order to break ground. Strictly speaking strategically, my intuition is that they will learn from this, course correct and then would start making progress.
> "They need to start somewhere in order to break ground"
Intel has big problems and it's not clear they should occupy themselves with this. They should stabilize, and the most plausible way to do that is to cut the weak parts, and get back to what they were good at - performant secure x86_64 CPUs, maybe some new innovative CPUs with low consumption, maybe memory/solid state drives.
Who is the target audience for this? Well informed gamers know Intel's discrete GPU is hanging by a thread, so they're not hoping on that bandwagon. Too small for ML. The only people really happy seem to be the ones buying it for transcoding and I can't imagine there is a huge market of people going "I need to go buy a card for AV1 encoding".
What do you mean by this - I assume you mean too small for SoTA LLMs? There are many ML applications where 12GB is more than enough.
Even w.r.t. LLMs, not everyone requires the latest & biggest LLM models. Some "small", distilled and/or quantized LLMs are perfectly usable with <24GB