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"Largely" is doing a lot of heavy lifting here. Yes Google and Amazon are making their own GPU chips, but they are also buying as many Nvidia chips as they can
by paxys 9mo ago
"Largely" is doing a lot of heavy lifting here. Yes Google and Amazon are making their own GPU chips, but they are also buying as many Nvidia chips as they can get their hands on. As are Microsoft, Meta, xAI, Tesla, Oracle and everyone else.
- greiskul 9mo agoBut is Google buying those GPU chips for their own use, or to have them on their data centers for their cloud customers?
- dekhn 9mo agogoogle buys nvidia GPUs for cloud, I don't think they use them much or at all internally. The TPUs are both used internally, and in cloud, and now it looks like they are delivering them to customers in their own data centers.
- moralestapia 9mo agoI can see them being used for training if they're vacant.
- HarHarVeryFunny 9mo agoThe various AI accelerator chips, such as TPUs and NVidia GPUs, are only compatible to extent that some of the high level tools like PyTorch and Triton (kernel compiler) may support both, which is like saying that x86 and ARM chips are compatible since gcc supports them both as targets, but note this does not mean that you can take a binary compiled for ARM and run it on an x86 processor. For these massive, and expensive to train, AI models the differences hit harder since at the kernel level, where the pedal hits the metal, they are going to be wringing every last dollar of performance out of the chips by writing hand optimized kernels for them, highly customized to the chip's architecture and performance characteristics. It may go deeper than that too, with the detailed architecture of the models themselves tweaked to best perform on a specific chip. So, bottom line is that you can't just take a model "compiled to run on TPUs", and train it on NVidia chips just because you have spare capacity there.
- moralestapia 9mo ago>but they are also buying as many Nvidia chips as they can get their hands on >But is Google buying those GPU chips for their own use >google buys nvidia GPUs for cloud, I don't think they use them much or at all internally. We're not talking about GPUs.
- moralestapia 9mo agoSorry, TPUs. Duh, that completely obliterated my argument. Anyways ...
- hansvm 9mo agoWhen I was there a few years ago, we only got CPUs and GPUs for training. TPUs were in too high of demand.
- notyourwork 9mo agoBoth. Internal are customers too.
- bredren 9mo agoHow about Apple? How is Apple training its next foundation models?
- consumer451 9mo agoTo use the parlance of this thread: "next" foundation models is doing a lot of heavy lifting here. Am I doing this right? My point is, does Apple have any useful foundation models? Last I checked they made a deal with OpenAI, no wait, now with Google.
- system2 9mo agoI think Apple is waiting for the bubble to deflate, then do something different. And they have the ready to use user base to provide what they can make money from.
- ymyms 9mo agoThey apparently are working on and are going to release 2(!) different versions of siri. Idk, that just screams "leadership doesn't know what to do and can't make a tough decision" to me. but who knows? maybe two versions of siri is what people will want.
- consumer451 9mo agoArena mode! Which reply do you prefer? /s But seriously, would one be for newer phone/tablet models, and one for older?
- pinnochio 9mo agoIt sounds like the first one, based on Gemini, will be more a more limited version of the second ("competitive with Gemini 3"). IDK if the second is also based on Gemini, but I'd be surprised if that weren't the case. Seems like it's more a ramp-up than two completely separate Siri replacements.
- 9mo ago