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 machine for which the action table has at most one entry for each combination of symbol and state. Read-only, right-moving Turing machines are equivalent to NDFAs (as well as DFAs by conversion using the NDFA to DFA conversion algorithm). For practical and didactical intentions the equivalent register machine can be used as a usual assembly programming language. An interesting question is whether the computation model represented by concrete programming languages is Turing equivalent. While the computation of a real computer is based on finite states and thus not capable to simulate a Turing machine, programming languages themselves do not necessarily have