Visual Turing Test Turing Test (VTT) unlike the Turing test has a query engine system which interrogates a computer vision system in the presence of a human co-ordinator. It is a system that generates a random sequence of binary questions specific to the test image, such that the answer to any question "k" is unpredictable given the true answers to the previous "k" − 1 questions (also known as history of questions). The test happens in the presence of a human operator who serves two main purposes: removing the ambiguous questions and providing the correct answers to the unambiguous questions. Given an Image
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.