Human computations

Very cool video about free human resources usage I have found the other day. As you could see from my resume, I’m graduated from the Intelligent Decision Support Systems Department of the Kharkov National University of Radio-Electronics. I don’t remember too much from my courses (but I know where and what to search when some sort of knowledge will be necessary, be sure), but what had stuck in my memory is that there are tons of tasks which can’t be easily solved: images classification, object detection, automatic expert systems knowledge bases building, etc. Some of these tasks are partially solved and have satisfactory results (for example mathematical and statistical methods of objects detection), others have bypassing methods (for example, Google uses text from HTML links to classify images). The main reason is that computers are not so smart as humans (maybe it’s not so bad, just think of the “The Matrix” movie).

So, little more about the video. Luis von Ahn, an assistant professor in the Computer Science Department at Carnegie Mellon University, explains the idea of how to use resources of millions of people absolutely free, and get results unachievable by today’s high-end computers. He is very smart, and I took a delight in watching his performance (yeah, performance, because his jokes were no worse than jokes of the best comic actors I’ve seen). I strongly recommend you to watch it, even if you hate artificial intelligence.

Here is an abstract:

Tasks like image recognition are trivial for humans, but continue to challenge even the most sophisticated computer programs. This talk introduces a paradigm for utilizing the human processing power to solve problems that computers cannot yet solve. Traditional approaches to solving such problems focus on improving the software. I advocate a novel approach: constructively channel human brainpower using computer games. For example, the ESP Game, described in this talk, is an enjoyable online game — many people play over 40 hours a week — and when people play, they help label images on the Web with descriptive keywords. These keywords can be used to significantly improve the accuracy of image search. People play the game not because they want to help, but because they enjoy it.

I describe other examples of “games with a purpose”: Peekaboom, which helps determine the location of objects in images, and Verbosity, which collects common-sense knowledge. I also explain a general approach for constructing games with a purpose.

And the video itself:

Stop playing solitaire! Help Google to grab the World!

BTW, “Peekaboom” is consonant with my current project name. No, I’m not developing another clone of the “game with a purpose”. No, I won’t tell you what the project is, at least now. Have other questions?