You have to be careful with those things. My alma mater has a tale of a student 7 or 8 years ago who built a neural net to detect lizards in photos. He fed the system a bunch of pictures to teach it what lizards look like. When it came time to test he got remarkable results: it was 100% effective in positively identifying lizards. Then he fed it a picture of empty ground and the net happily confirmed that this picture contained a lizard as well! Turns out, if all of your training data is positive the computer just learns "everything is a lizard".
Of course, real-life researchers would never dare make such a mistake but this tale always amuses me so I couldn't resist :)