Because their focus on user privacy makes it difficult for them to train at scale on users' data in the way that their competitors can. Ironically, this focus on privacy initially stemmed from fumbling the ball on Siri: recall that Apple never made privacy a core selling point until it was clear that Siri was years behind Google's equivalent, which Apple then retroactively tried to justify by claiming "we keep your data private so we can't train on it the way Google can." The result was a vicious cycle: initially botch AI rollout -> justify that failure with a novel marketing strategy around privacy that only makes it harder to improve their AI capabilities -> botch subsequent AI rollouts as a result -> ...

To be clear, I'd much rather have my personal cloud data private than have good AI integration on my devices. But strictly from an AI-centric perspective, Apple painted themselves into a corner.

It's been a long running thing that Apple can't do software as well as competitors, though in my experience they've beat Google and a few others at devex and UX in their mobile frameworks overtime despite initial roughness. Slow and steady might win this race eventually, too.

it's pretty Apple-ish to not jump into a frenzy, and wait for turbulence to settle, i believe. delegation to Gemini fits that theory?

They aren’t so good at everything else either.

Apple is almost purely customer products, they don't have the resources to compete with the giants in this field.

Their image classification happens on-device, in comparison Google Photos does that server side so they already have ML infra.

See ML research papers from Apple. Their researchers prefered small models over LLM. So they thought researchers' effort would make up the lack of compute. Then the scale law hit them hard.

have you used iOS 26?

"liquid ass" is how most of my friends describe it

I think that's the thing: Apple is good at very little, but they seem like they're good at "everything else" because they don't do much else. Lots of companies spread themselves really thin trying to get into lots of unrelated competencies and tons of products. Apple doesn't.

Why does a MacBook seem better than PC laptops? Because Apple makes so few designs. When you make so few things, you can spend more time refining the design. When you're churning out a dozen designs a year, can you optimize the fan as well for each one? You hit a certain point where you say "eh, good enough." Apple's aluminum unibody MacBook Pro was largely the same design 2008-2021. They certainly iterated on it, but it wasn't "look at my flashy new case" every year. PC laptop makers come out with new designs with new materials so frequently.

With iPhones, Apple often keeps a design for 3 years. It looks like Samsung has churned out over 25 phone models over the past year while Apple has 5 (iPhone, iPhone Plus, iPhone Pro, iPhone Pro Max, iPhone 16e).

It's easy to look so good at things when you do fewer things. I think this is one of Apple's great strengths - knowing where to concentrate its effort.

There's no reason to think that Apple would have any more skill at making a frontier AI model as they do at making airplanes or growing soybeans. Not much overlap between consumer electronics design and expertise, data, training, and datacenters needed for AI.

> but so good at everything else?

They aren't.