[lifeisstillgood]

Computer vision is one of those odd areas that I cannot see a nice gentle slope to adoption, but instead is a step change. For example NLP gives us all sorts of add ons to our current interaction with computers (hey let's do sentiment analysis of customer reviews / emails / etc)

But there is no obvious slope for computer vision - we need an infrastructure of cameras and bandwidth before it becomes ubiquitous

So I struggle to see the profitable intermediate businesses between here and there - and that troubles me.

[TeMPOraL]

There are many intermediate applications. From my own computer vision classes at university I remember examples of jobs when a guy is sitting and looking at a factory line or a machine for 8 hours a day in order to press a button if something goes wrong. This is a kind of work that bores humans out of their minds (thus making them extremely fallible), and that can be done much better with a few cameras and a computer running not-very-supercomplicated computer vision algorithms.

[nl]

I don't think that's entirely true.

There are many tasks where the current levels of accuracy are sufficient (eg, registration plate recognition), and as recognition slowly improves more and more tasks become possible.

Pete Warden has written extensively on this topic[1]. His "hipster detection" algorithm is quite inaccurate by any conventional measurement, but is accurate enough to be useful.

[1] http://petewarden.com/2014/07/31/how-to-get-computer-vision-...

[kastnerkyle]

Every smartphone has a camera... and if self-driving cars become a reality there will be a lot of cameras on the road as well.

Who needs bandwidth when you can push your models to the local device with a small update? They can just send back batched statistics when a high bandwidth network is available. After all, cars need gas or a charge sometime.

It is just a binary patch to change some weights or an architecture layout, which is not so different from updating any other application.

Most businesses are covered with cameras as well as hiring people who's only job is to watch those cameras for anomalous activity - I think there are more opportunities than you realize. Farming is another indistry where this technology could be useful.