Artificial Intelligence has emerged from the realm of science fiction and become a part of the millennial way of life. The factory of the future is taking shape in Japan and it is being built on an AI platform. Here, robots will learn from each other and every robot will have an embedded GPU to perform real time AI. In 2016, AlphaGo, a computer programme from Google's Deep Mind, had a historic win over the world's most celebrated Go champion, Lee Sedol of South Korea. The same year, Microsoft achieved human parity in speech recognition.
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.
AAAI is a society devoted to supporting the progress in science, technology and applications of AI. I thought I would use this occasion to share with you some of my thoughts on the recent advances in AI, the insights and theoretical foundations that have emerged out of the past thirty years of stable, sustained, systematic explorations in our field, and the grand challenges motivating the research in our field.
Now it come to the second stage in which researchers axe asked to show visions for real applications. The author argues that Grand Challenge AI Applications should be proposed and pursued. These applications should have significant social, economic and scientific impact and serve as showcases of accomplishments of massively parallel AI. For the grand challenge to succeed, massive computing power, massive data resource, and sophisticated modeling would be critical. At the same time, it is thought that such efforts shall be promoted as international projects. I. Introduction This paper describes the role of massively parallel artificial intelligence[Waltz, 1990, Kitano et.