It goes a tad bit beyond classical conditioning… LLM’a provides a much better semantic experience than any previous technology, and is great for relating input to meaningful content. Think of it as an improved search engine that gives you more relevant info / actions / tool-suggestions etc based on where and how you are using it.

Here’s a great article that gives some insight into the knowledge features embedded into a larger model: https://transformer-circuits.pub/2024/scaling-monosemanticity/

That’s why it’s on the OS-level. For example, for text, it seems to work in any text app that uses the standard text input api, which Apple controls.

User activates the “AI overlay” on the OS, not in the app, OS reads selected text from App and sends text suggestions back.

The App is (possibly) unaware that AI has been used / activated, and has not received any user information.

Of course, if you don’t trust the OS, don’t use this. And I’m 100% speculating here based on what we saw for the macOS demo.

He sort of invented it, so you have to think he’s commenting on the concept here, not the implementation.

I have tried a lot of medium and small models, and there it just no good replacement for the larger ones for natural text output. And they won’t run on device.

Still, fine-tuning smaller models can do wonders, so my guess would be that Apple Intelligence is really 20+ small and fine tuned models that kick in based on which action you take.

How so? Many people want to use AI in privacy, but it’s too hard for most people to set it up for themselves currently.

Having AI tools on the OS level so you can use it in almost any app and that is guaranteed to be processed on device in privacy will be very useful if done right.

I mean, that’s fair, if you don’t believe in his integrity than this news have very little value to you.

The concept is useful. A well known idea capture of it is the famous “As We May Think” article from Vannevar Bush all the way back in 1945, which conceptualized a machine “Memex” that would enhance humans capabilities with for example memory and recall. A lot of humans needs help with this and use devices for this daily, with notes, map lookups of where you parked, find my things for devices, analytics for photo libraries etc etc etc.

The only issue here is the implementation.