Recently I read this press release: computers get “common sense” to tell a tennis ball from a lemon, right! I quickly dismissed it as another over-optimistic report about a project that will go nowhere. Then I read a short comment (by ivankirgin) here about it.

Common sense reasoning is one of the hardest parts of AI. I don’t think top-down solutions will work. …You can’t build a top down taxonomy of ideas and expect everything too work. You can’t just “hard code” the ideas.

I can’t agree more. But then he continues:

I think building tools from the ground up, with increasingly complicated and capable recognition and modeling, might work. For example, a visual object class recognition suite that first learned faces, phones, cars, etc. and eventually moved on to be able to recognize everything in a scene, might be able to automatically perhaps with some training build up the taxonomy for common sense.

First, he simply does not go far enough. I’d start with even lower level – find the “objects”, their locations, sizes, shapes, etc. This is the “dumb” approach I’ve been suggesting in this blog and the wiki. Once you’ve got those abstract objects, you can try to figure out what those objects represent. In fact, often you don’t need even that. For example, for a home security system you don’t need to detect faces to sound alarm. The right range of sizes will do. A moving object larger than a dog and smaller than a car will trigger the alarm. All you need is a couple of sliders to set it up. Maybe the problem with this approach is that it’s too cheap?

Another point was about training and machine learning. I have big doubts about the whole thing. It is very much like trying to imitate the brain (or something else we observe in nature). Imagine you have a task the people do easily but you don’t understand how they do it. Now you solve the problem in these three easy steps.

• You set up a program that supposedly behaves like the human brain (something you don’t really understand),
• you teach it how to do the task by providing nothing but feedback (because you don’t understand how it’s done),
• the program runs pattern recognition and solves the problem for you.

Nice! “Set it and forget it!” (Here is another example of this approach.) If you can teach computer to recognize objects, you can teach it simpler things. How about teaching computer to add based entirely on feedback? Well, this topic deserves a separate post…