Yea, that’s still not training the underlying ML model, at least from a traditional ANN standpoint.

Apple cannot train the model to unlock for your face in the lab. They don’t know your face! You are training it when you are setting up FaceID

I think you have a fundamental misunderstanding of how ML works and what it actually does. (No offense, most folks don’t)

The model in the lab is “trained” to identify elements of whatever the target of the ML is meant to identify, whether its fingerprints, cars, dogs or faces. Artificial Neural Networking (ANN, aka deep learning) uses multilayered descriptors which the model actually chooses for itself (Traditional ML relies on humans to choose descriptors). These descriptors build the learned model by being tested with a huge amount of true and false training data (In FaceID’s case they likely fed the model millions of faces scraped from the internet along with pictures of non-faces)

Once the learned model is ready, it will be fed test data to determine its level of accuracy (This is the number that Tim Cook gave us onstage)

That learned model is what is actually pushed to your device. When you set up face ID, its going to analyze your face using the learned model from the lab and populate its data points. Its “ability to learn changing features over time” is not an adjustment of the learned model, but instead tweaking of the collected data points within the model.

Hopefully this makes sense and helps describe what’s actually happening. 👍🏼