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However it's worth noting that in the end, it's the consumer that loses out when these technical/capability moats maintain a de facto sort of monopoly on certain use cases.
Fun fact: More than half of all engineers at NVIDIA are software engineers. Jensen has deliberately and strategically built a powerful software stack on top of his GPUs, and he's spent decades doing it. Until Intel finds a CEO who is as technical and strategic, as opposed to the bean-counters, I doubt that they will manage to organize a successful counterattack on CUDA.
Granted, I may have just gotten off on the wrong foot. The first thing he said to Pivotal during the acquisition announcement was, “You were our cousins, but you’re now more like children.” So the whole tone was just weird.
Having the relatively unique experience of trying to sell an alternative deep learning stack, and then selling that company to Intel, color me skeptical. AMA.
Intel and AMD have had years to provide similar capabilities on top of OpenCL. Maybe they should look into their own failures first.
Fun fact: More than half of all engineers at NVIDIA are software engineers. Jensen has deliberately and strategically built a powerful software stack on top of his GPUs, and he's spent decades doing it. Until Intel finds a CEO who is as technical and strategic, as opposed to the bean-counters, I doubt that they will manage to organize a successful counterattack on CUDA.
Even if Intel falls over its own feet, the incentives to bring in more chip manufacturers are huge. It'll happen, the only question is whether the timeframe is months, years or a decade. My guess is shorter timeframes, this seems to mostly be matrix multiplication and there is suddenly a lot of money and attention on the matter. And AMD's APU play [0] is starting to reach the high end of the market with the MI300A which is an interesting development.
[0] EDIT: For anyone not following that story, they've been unifying system and GPU memory; so if I've understood this correctly there isn't any need to "copy data to the GPU" any more on those chips. Basically the CPU will now have big extensions for doing matrix math. Seems likely to catch on. Historically they've been adding that tech to low-end CPU so it isn't useful for AI work, now they're adding it to the big ones.
Having the relatively unique experience of trying to sell an alternative deep learning stack, and then selling that company to Intel, color me skeptical. AMA.
Well, can you elaborate on what exactly you observed/felt from Intel that makes you skeptical about these claims?
Having the relatively unique experience of trying to sell an alternative deep learning stack, and then selling that company to Intel, color me skeptical. AMA.
(Do we know each other?)
Having the relatively unique experience of trying to sell an alternative deep learning stack, and then selling that company to Intel, color me skeptical. AMA.
Having worked for a deep learning startup which was acquired by Intel, I am likewise skeptical. (Do we know each other?)
As another commenter said, it's CUDA. Intel and AMD and whoever can turn out chips reasonably fast, but nobody gets that it's the software and ecosystem. You have to out-compete the ecosystem. You can pick up a used Mi100 that performs almost like an A100 for 5x less money on eBay for example. Why is it 5x less? Because the software incompatibilities mean you'll spend a ton of time getting it to work compared to an N…