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 the machine must use natural language, reason, have knowledge and learn. The test can be extended to include video input, as well as a "hatch" through which objects can be passed: this would force the machine to demonstrate the skill of vision and robotics as well. Together, these represent almost all of the major problems that artificial intelligence research would like to solve. The Feigenbaum test is designed to take advantage of the broad range of topics available to a Turing test. It is a limited form of Turing's question-answer game which compares the machine against the abilities of experts