期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2020
卷号：117
期号：48
页码：30029-30032
DOI：10.1073/pnas.2020596117
出版社：The National Academy of Sciences of the United States of America
摘要：Scientists today have completely different ideas of what machines can learn to do than we had only 10 y ago. In image processing, speech and video processing, machine vision, natural language processing, and classic two-player games, in particular, the state-of-the-art has been rapidly pushed forward over the last decade, as a series of machine-learning performance records were achieved for publicly organized challenge problems. In many of these challenges, the records now meet or exceed human performance level. A contest in 2010 proved that the Go-playing computer software of the day could not beat a strong human Go player. Today, in 2020, no one believes that human Go players—including human world champion Lee Sedol—can beat AlphaGo, a system constructed over the last decade. These new performance records, and the way they were achieved, obliterate the expectations of 10 y ago. At that time, human-level performance seemed a long way off and, for many, it seemed that no technologies then available would be able to deliver such performance. Systems like AlphaGo benefited in this last decade from a completely unanticipated simultaneous expansion on several fronts. On the one hand, we saw the unprecedented availability of on-demand scalable computing power in the form of cloud computing, and on the other hand, a massive industrial investment in assembling human engineering teams from a globalized talent pool by some of the largest global technology players. These resources were steadily deployed over that decade to allow rapid expansions in challenge problem performance. The 2010s produced a true technology explosion, a one-time–only transition: The sudden public availability of massive image and text data. Billions of people posted trillions of images and documents on social media, as the phrase “Big Data” entered media awareness. Image processing and natural language processing were forever changed by this new data resource.
