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The field of artificial intelligence (AI) has undergone a series of “springs”, marked by optimism, surge in funding, and elevated claims. These AI springs have been punctuated by “AI winters”, marked by disappointment and funding crashes when the claims do not pan out. Our current AI spring, based almost entirely on the successes of deep learning, has persisted for nearly a decade, and many have predicted these successes to be harbingers of near-term human-level AI. In this talk I examine the springs and winters in the history of AI. I also explore the recent achievements of deep learning as well as its weaknesses and vulnerabilities, and discuss the barriers that still face the field in achieving human-like intelligence in machines, and whether the field is on the right path to avoid yet another AI winter. Host: Information Science and Technology Institute (ISTI) |