A new study shows that there are many technologies that run on algorithms and machine learning, which could predict how our brain works. This study shows that how our brain process the image and how computers can predict what paintings people are going to like. It is done with the help of special software by which the computer first analyzes the image and curvature in it, and with the help of it, concludes a specific result which tells if the image is correct or not or is it well-structured or not.
For instance, some people like the thick brushstrokes and soft color palettes of an Impressionist painting like that of Claude Monet, while some prefer the abstract shapes and bold colours of a Rothko. There is a certain temperament about individual art tastes. Now a new Caltech study shows that a simple computer program can accurately predict which paintings a person would like. For this study, more than 1,500 volunteers were recruited to rate paintings in Impressionism, Cubism, Abstract, and Colour Fields genres. The volunteers’ responses were fed into a computer program, and after this familiarization period, the computer was able to predict the volunteers’ artistic preferences much better than it would have happened by chance. “The evaluation of art was personal and subjective, so I was surprised by the result,” says lead author Kiyohito Iigaya, a postdoctoral researcher who works in the Caltech lab of psychology professor John O’Doherty.
