Visual Turing Test millions of dollars into computer vision research, and are trying to build systems that closely resemble the human visual system. Recently Facebook announced its new platform M, which looks at an image and provides a description of it to help the visually impaired. Such systems might be able to perform well on the VTT. Visual Turing Test Computer vision research is driven by standard evaluation practices. The current systems are tested by their accuracy for tasks like object detection, segmentation and localization. Methods like the convolutional neural networks seem to be doing pretty well in these tasks, but the current
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.