Easiest way to tell, how much dancing around did we listen to and how many diagrams did we have to look at? If they had their own tech we wouldn't be looking at diagrams we'd just be getting told Siri AI, it's private, it's powerful, here's what it can do. Instead we had 10 minutes talking around the tech and this diagram [1] which is a signal that it's a bunch of other peoples stuff cobbled and wrapped together.
[1]:https://www.apple.com/newsroom/images/2026/06/apple-introduc...
It's a 3B Apple Foundation model.
https://machinelearning.apple.com/research/introducing-apple...
If you've got a mac, you can use this to play around with it:
Google also awhile back announced being able to run full Gemini by leasing / renting hardware in your own datacenters so companies can train or access data without needing to send things to their datacenters. Nvidia based. Guessing Private Compute might just be Apple leasing a ton of those?
What could "refined" mean here?
But beside that, I feel like the app variant got worse the day they've had that wwdc-style release thing recently.
Previously it was a sparring partner that could actually keep up. But now it just doesn't.
Truly a shame. And nothing that could be fixed by local models any time soon, given that you need the size for the (cross-)domain knowledge.
Search would be better without the added AI hallucinations above it. If I want an AI answer I'll go and ask Claude, the quality difference is huge.
That's not Gemini, that's AI Mode (in Search), they're different products built by fairly different part of Google (actually one is built by Deepmind).
(I don't think it's much comparable to https://gemini.google.com/app at least in the past you'd get very different results)