> Microsoft said it does not plan to sell the chips
Add it to the list of things you can't buy at any price, and can only rent. That list is getting pretty long, especially if you count "any electronic device you can't fully control or modify".
Add it to the list of things you can't buy at any price, and can only rent. That list is getting pretty long, especially if you count "any electronic device you can't fully control or modify".
My bet: if it really becomes clear what capabilities an AI accelerator chip needs and lots of people want to run (or even train) AIs on their own computers, AI accelerators will appear at the market. This is how capitalism typically works.
My further bet: these AI accelerators will initially come from China.
Just look at the history of Bitcoin: initially the blocks were mined on CPUs, but then the miners switched to GPUs and "everybody" was complaining about increasing GPU prices because of all the Bitcoin mining. At some moment, Bitcoin mining ASICs appeared from China and after those spread, GPUs were not attractive anymore for Bitcoin mining (of course the cryptocurrency fans who bought the GPUs for mining attempted to use their investment for mining other cryptocurrencies).
Yet many startups and existing designers anticipated this demand correctly, years in advance, and they are all still kinda struggling. Nvidia is massively supply constrained. AI customers would be buying up MI250s, CS-2s, IPUs, Tenstorrent accelerators, Gaudi 2s and so on en masse if they wanted to... But they are not, and its not going to get any easier once the supply catches up.
Unless there's a big one in stealth mode, I think we are stuck with the hardware companies we have.
Theres also some kind of actual AI crypto project that I wouldn't touch with a 10 foot pole.
But ultimately, even if true distribution like Petals figures out the inefficiency (and thats hard), it had the same issue as non Nvidia hardware: its not turnkey.
Can you order any of these devices online as a regular person? Anybody can order a $300 Nvidia GPU and program it. This is the reason why deep learning originated on the GPUs. Forget those other AI accelerators, even if you bought something like a consumer grade AMD GPU, you couldn't program it because it's restricted. The reason why Nvidia's competitors are struggling is because their hardware is either too expensive or hard to buy.
As I already hinted in my post: I see a huge problem in the fact that in my opinion it still is not completely clear to this day which capabilities an AI accelerator really needs - too much is in my opinion still in a state of flux.
A good example of this is Intel canceling, and AMD sidelining, their unified memory CPU/GPU chips for AI. They are super useful!.. In theory. But actually, they totally useless because no one is programming frameworks with unified memory SoCs in mind, as Nvidia does not make something like that.
My bet: in 6 months jart will have models running on local or server, with support for all platforms and using only 88K of ram ;)
If any of these companies truly made competitive silicon they absolutely would commercialize it.
I suspect they aren't as competitive as the press releases hold them to be, and this Microsoft entrant is likely to follow the same path. Like Google, Tesla, Amazon and others it seems mostly an initiative to negotiate discounts from nvidia.
It would be great if there were really competition. When Google was hyped about their Tensor chips they did have a period where they were looking to commercialize it, and there are some pretty crappy USB products they sell.
Now, I know that what you actually mean is selling the chips themselves to third parties :) But it's not obvious that there's any point to it given their already existing model of commercializing the chips.
First, literally everyone is already supply-constrained due to limits on high end foundry capacity. Nvidia has a ton of capacity because they're one of TSMC's top two customers. The big tech companies will have much smaller allocations which are used up just supplying their own clouds. Even if the demand for buying these chips rather than renting were there, they just don't have the chips to sell without losing out on the customers who want to rent capacity.
Second, the chips by themselves are probably not all that useful. A lot of the benefit is coming from the silicon/system/software co-design. (E.g. the TPUv4 papers spent as much attention on the optical interconnect as the chips). Selling just chips or accelerator cards wouldn't do much good to any customers. Nor can they just trust that systems integrators could buy the cards and build good systems to house them in. They need to sell and support massive large scale custom systems to third parties. That's not a core competency for any of them, it'll take years to build up that org if you start now. And it means they need to ship the software to the customers, it can't continue being the secret sauce any more.
Nvidia on the other hand has been building up an ecosystem and organization for exactly this for the last decade.
And TSMCs top customer is not even playing in the cloud space.
https://ir.amd.com/news-events/press-releases/detail/1168/am...
I, personally, am interested in retrocomputing, amateur/hobbyist electronics, and hobbyist computing (including semiconductors [2]). While these techniquess and devices may be light years away from anything resembling a computer that can compete with SotA commercial offerings, they do offer the promise of “keeping the candle lit” as it were. I will note that if you follow Sam Zeloof’s chronicles, he progressed through the earliest phases of semiconductor development far faster than the industry did back when it was pioneering the technology. Of course, he had the benefits of knowing it was already possible and access to the written knowledge of the experts who went before him.