[vineyardmike]

The obvious answer to where the AI Labs get customers is Cloud GPUs. Most users (globally) have cheap phones with poor CPUs and small amounts of RAM. They can't run usable models locally, and it's not clear from the Google-Apple deal if G is selling access to their cloud compute as part of that $1B, or just sharing the weights/IP.

Apple themselves have said there is usage limits, with a subscription upgrade for more usage. So clearly AI Labs are directly competing on that front, it's just a normal default/chosen decision. Considering there are defaults and still successful competitors (eg. safari v chrome), there's no reason to think that competition can't handle this too.

Edit: I want to add that Google is also probably willing to give the model away at a discount to its true value in exchange for guaranteeing that their primary competition (who has tons of cash) won’t have an economic incentive to enter the foundation model training arms race.

Most users who actually want these features for anything more serious than summarization and style updates will probably find value in a modest subscription or ad-supported tier of higher quality models, even if just for occasional usage. Apple can provide this, but once you're comparing features, for many Gemini/Claude/ChatGPT may be a better fit.

Oh, and I think there is an unfortunate but real risk that once again, apple totally over-promises here, and their AI models that they ship end up being pretty poor, and that drives users further into subscriptions.

[dwaite]

> Apple themselves have said there is usage limits, with a subscription upgrade for more usage.

Specifically for image generation. They haven't indicated you have limits for Siri interactions.

[vineyardmike]

> "Some features, including image generation, have daily usage limits because they rely on powerful server models. Increased access is available with most iCloud plus subscription plans".

Start at 1:07:00 in their announcement video. Craig is absolutely talking about "Apple Intelligence" as a whole in this segment.

Pragmatically, of course they'd need to add metering to any cloud available APIs that rely on large models. There's no way they will eat the cost of serving unlimited access to a cloud LLM to end users if they won't eat the cost of an image generation model.

[dofm]

> Oh, and I think there is an unfortunate but real risk that once again, apple totally over-promises here, and their AI models that they ship end up being pretty poor, and that drives users further into subscriptions.

OK, that I would concede is a possibility. Though Gemini is clearly capable, and the (alleged) story is that they have licensed a one-trillion parameter form of Gemini. I don't think they are making the same mistake.

ETA: I also concede they could make a different mistake ;-)

[avidphantasm]

The AI labs are racing to create a moat out of trillion-parameter models and the GPUs that can run them. The problem is this is the wrong architecture for most AI inference use cases. On-device inference is where this is going, clearly Apple believes this too. So Zitron is entirely correct about this AI datacenter build out being a boondoggle with no ROI.