| The article continues with: > If a common motion associated with theft is detected, your phone screen quickly locks – which helps keep thieves from easily accessing your data. So it's probably a machine learning model that was trained on motion data of snatches, but it's likely not AI in the sense of LLMs. But I wonder how many false positives this could yield. For example you are in a hurry and you snatch your phone from a table. How precicesly can this model decide with just motion data, if this was theft or not. |
If I snatch a phone from the table (probably already locked?) or drop it, I will suck up the additional login.
I have long thought about the utility of a little locking-beacon. If phone suddenly gets out of range, should auto lock. If only Bluetooth were not so unreliable.