2 ms·

You only need a huge dataset to train the network. The trained network itself is (relatively) tiny, so it can be loaded and run on iPhones.

• radicality 10y ago
  When you say relatively, just how many MBs of data would a trained net be that can recognize objects and do the kind of recognition/photo grouping they showed at the keynote?
• visarga 10y ago
  It's a whole subfield of machine learning called model distillation or model compression that concerns with shrinking large neural nets, or ensembles of them, to fit on small devices like phones and tablets. By reducing the space needed by 10x, they only lose 1-2% in accuracy. But what I like about it is that neural networks can be transferred between different architectures, and the whole process of training a neural net can be sped up by starting from a previous result.