AI Winter refers to a period of reduced activity in Artificial Intelligence research and development. After the initial excitement and funding generated by AI projects in the 1950s, interest and support gradually tapered off, resulting in a decrease in funding for AI initiatives between 1974-1980 - the first winter period, and despite some progress in the early 1980s, the decade ended with another slowdown, leading to the second AI winter, from 1987-1993, a result of high costs in developing and running AI systems, making widespread adoption challenging, and unrealistic expectations leading to disappointment as AI failed to deliver on lofty promises, resulting in reduced funding and skepticism.

However, advancements in deep learning, graphics processing units, big data analytics, and processing have rekindled interest and driven investments in areas of innovation such as facial recognition, machine learning algorithms, AlphaGo - an AI agent for the Chinese board game Go, advanced language recognition and translation, medical diagnoses and imaging, self-driving cars, and ChatGPT.