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> The privacy implications of this are dubious. Really? Apple can essentially be asked by Law Enforcement for answers to questions like "Give me all the IMEIs
by secondcoming 5y ago
> The privacy implications of this are dubious.
Really? Apple can essentially be asked by Law Enforcement for answers to questions like "Give me all the IMEIs of people in location X, radius 10 miles, that appear to have pictures of cats"
- londons_explore 5y agoThe model fine tunings can't immediately be used to say "this person has pictures of cats". They effectively are just a big diff of the ML weights. It's a big set of floating point numbers which is hard to get any meaning out of. But experts believe that techniques might be developed in the future to figure out based on the numbers what data must have been in the training set (and hence your photos). Nobodies managed to do that yet.
- mhitza 5y agoNo experience with NN, just basic understanding of these things. If you train a model A) cats, one for B) dogs and one for C) dogs and cats. Is there any research which asks if you can do a network subtraction C-B = D, and get a sensible network D than can loosely do what A does?
- londons_explore 5y agoTry it... but I predict you'll get a model that doesn't work at all...