Comment by jt2190

When I was there a few years ago, we only got CPUs and GPUs for training. TPUs were in too high of demand.

I can see them being used for training if they're vacant.

Apple does have their own small foundation models but it's not clear they require a lot of GPUs to train.

I 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.

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.

From a technology standpoint I don’t feel Apple’s core competency is in AI model foundations

They might know something?