Scientists have trained a quantum computer to recognize trees. That may not seem like a big deal, but the result means that researchers are a step closer to using such computers for complicated machine learning problems like pattern recognition and computer vision. The team fed hundreds of NASA satellite images of California into a D-Wave 2X processor, and asked the computer to consider dozens of features -- hue, saturation, even light reflectance -- to determine whether clumps of pixels were trees as opposed to roads, buildings, or rivers. They then told the computer whether its classifications were right or wrong so that the computer could learn from its mistakes, tweaking the formula it uses to determine whether something is a tree. After it was trained, the D-Wave was 90% accurate in recognizing trees in aerial photographs of Mill Valley, California. The results demonstrate how scientists can program quantum computers to 'look' at and analyze images, and opens up the possibility of using them to solve other complex problems that require heavy data crunching.
