AI Winter
A period of reduced funding and interest in artificial intelligence research, historically occurring when AI fails to meet inflated expectations.
Historical AI Winters
First (1974-1980): After early symbolic AI failed to deliver on grand promises. Second (1987-1993): After expert systems proved too brittle and expensive. Both were triggered by hype cycles followed by disillusionment.
Current Debate
Some researchers worry that the current generative AI boom could lead to another winter if expectations outpace capabilities. Others argue that the economic value being generated is fundamentally different from previous hype cycles.