[sapphireblue]

3 years ago many systems that exist today would be regarded as "scifi" or "maybe 10 years into the future". One of the most striking examples is Visual Question Answering with dynamic memory networks [1]. The model is given raw pixels and encoded question in natural language, it should output a natural language answer. See how it works on data it hasn't seen: http://i.imgur.com/074G9pg.jpg

Do not underestimate what good ML model can learn given enough data. And in case of online shopping there usually is more than enough data, and big companies like Amazon have been using ML (context bandits) for quite some time.

1. https://arxiv.org/abs/1603.01417

[argonaut]

Then would know that visual question answering performs quite poorly. It makes for a nice demo, but it's trivial/quick/easy to find entire areas of questions where the models completely. The questions have to be worded very carefully. The models are quite finnicky and dumb. For example, dynamic memory nets aren't the state of the art - the state of the art for these datasets doesn't use anything nearly as complicated as memory, etc.

[argonaut]

*completely fail