Visual Turing Test a very recent work published on March 9, 2015, in the journal "Proceedings" of the National Academy of Sciences, by researchers from Brown University and Johns Hopkins University. It evaluates how the computer vision systems understand the Images as compared to humans. Currently the test is written and the interrogator is a machine because having an oral evaluation by a human interrogator gives the humans an undue advantage of being subjective, and also expects real time answers. The Visual Turing Test is expected to give a new direction to the computer vision research. Companies like Google and Facebook are investing
Turing test much academic or commercial effort—as Stuart Russell and Peter Norvig write: "AI researchers have devoted little attention to passing the Turing test." There are several reasons. First, there are easier ways to test their programs. Most current research in AI-related fields is aimed at modest and specific goals, such as automated scheduling, object recognition, or logistics. To test the intelligence of the programs that solve these problems, AI researchers simply give them the task directly. Russell and Norvig suggest an analogy with the history of flight: Planes are tested by how well they fly, not by comparing them to birds.