| Abstract | The current rise of AI has mainly two origins. The first one is, of course, the invention of machine learning. Statistics and optimization deliver their theories to the machine learning. The combination of the big data and the massively parallel computing enables the machines to “learn” from the data existing on the web, the network and the database, though there is only small hope that machine learning technologies help the machine to solve the design problem like design automation. Another rather inconspicuous origin is the sophistication of the traditional logical approach. The virtue of the logical approach is in its ability to express complex input-output relations, such as the mapping form natural language text to its meaning and the logical relation between a premise and its consequence, in a way that a human can understand. In this talk, I introduce AI grand challenge, “Todai Robot Project” (Can an AI get into the University of Tokyo?), initiated by National Institute of Informatics in 2011, and discuss the impact of near-term AI technologies on design automation. |