Comment by paxys a day 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.
I can see them being used for training if they're vacant.
The 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.
>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.
How about Apple? How is Apple training its next foundation models?
To 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.
If they were taking that approach, they would have absolutely first-class integration between AI tools and user data, complete with proper isolation for security and privacy and convenient ways for users to give agents access to the right things. And they would bide their time for the right models to show up at the right price with the right privacy guarantees.
I see no evidence of this happening.
As an outsider, the only thing the two of you disagree on is timing. I probably side with the ‘time is running out’ team at the current juncture.
Apple can make more money from shorting the stock market, including their own stock, if they believe the bubble will deflate.
The options for a company in their position are:
1. Sit out and buy the tech you need from competitors.
2. Spend to the tune of ~$100B+ in infra and talent, with no guarantee that the effort will be successful.
Meta picked option 2, but Apple has always had great success with 1 (search partnership with Google, hardware partnerships with Samsung etc.) so they are applying the same philosophy to AI as well. Their core competency is building consumer devices, and they are happy to outsource everything else.
Well they tried and they failed. In that case maybe the smartest move is not to play. Looks like the technology is largely turning into a commodity in the long run anyways. So sitting this out and letting others make the mistakes first might not be the worst of all ideas.
This whole thread is about whether the most valuable startup of all time will be able to raise enough money to see the next calendar year.
It's definitely rational to decide to pay wholesale for LLMs given:
- consumer adoption is unclear. The "killer app" for OS integration has yet to ship by any vendor.
- owning SOTA foundation models can put you into a situation where you need to spend $100B with no clear return. This money gets spent up front regardless of how much value consumers derive from the product, or if they even use it at all. This is a lot of money!
- as apple has "missed" the last couple of years of the AI craze, there has been no meaningful ill effects to their business. Beyond the tech press, nobody cares yet.
I mean, they tried. They just tried and failed. It may work out for them, though — two years ago it looked like lift-off was likely, or at least possible, so having a frontier model was existential. Today it looks like you might be able to save many billions by being a fast follower. I wouldn’t be surprised if the lift-off narrative comes back around though; we still have maybe a decade until we really understand the best business model for LLMs and their siblings.
> I mean, they tried. They just tried and failed.
They tried to do something that probably would have looked like Copilot integration into Windows, and they chose not to do that, because they discovered that it sucked.
So, they failed in an internal sense, which is better than the externalized kind of failure that Microsoft experienced.
I think that the nut that hasn't been cracked is: how do you get LLMs to replace the OS shell and core set of apps that folks use. I think Microsoft is trying by shipping stuff that sucks and pissing off customers, while Apple tried internally declined to ship it. OpenClaw might be the most interesting stab in that direction, but even that doesn't feel like the last word on the subject.
I think you are right. Their generative AI was clearly underwhelming. They have been losing many staff from their AI team.
I’m not sure it matters though. They just had a stonking quarter. iPhone sales are surging ahead. Their customers clearly don’t care about AI or Siri’s lacklustre performance.
From a technology standpoint I don’t feel Apple’s core competency is in AI model foundations
Sure, Siri is, but do people really buy their phone based off of a voice assistant? We're nowhere near having an AI-first UX a la "Her" and it's unclear we'll even go in that direction in the next 10 years.
They are in housing their AI to sell it as a secure way to AI, which 100% puts them in the lead for the foreseeable future.
But is Google buying those GPU chips for their own use, or to have them on their data centers for their cloud customers?