MIT researchers have developed a computing system that could lead to great advances in the automated identification of online images and, ultimately, provide a basis for computers to ‘see’ in a manner similar to humans, Science Daily reports. For the study, researchers created a mathematical system that can shrink the data from a single picture. Using the system, they found that many images are recognizable even when coded into a numerical representation containing as little as 256 to 1024 bits of data. Reducing the size of an image to such small amounts of data enables ordinary PCs to search through a database of millions of images or similar pictures in less than a second, according to the lead researcher. Science Daily adds that, “unlike other methods that require first breaking down an image into sections containing different objects, this method uses the entire image, making it simple to apply to large datasets without human intervention.” Currently, the system can be applied to the most common kinds of images, such as those depicting cars, people, flowers and buildings. However, the more complex or unusual an image is, the less likely it is to be correctly matched (Science Daily, 5/26/08).