What characterizes an AI winter?

An AI winter is primarily characterized by a decline in funding and interest in artificial intelligence. This phenomenon typically occurs after periods of overhyped expectations where the initial excitement surrounding AI technologies fails to meet the promised outcomes. As a result, stakeholders—ranging from government bodies to private investors—often retract their support, leading to diminished research efforts and slowed progress in the field.

This historical pattern has manifested in cycles throughout the history of AI development, highlighting how public and institutional enthusiasm can sharply drop when anticipated advancements don't materialize or prove to be more challenging to achieve than initially thought. Thus, the ability to navigate these peaks and troughs is crucial for sustaining long-term investment and development in AI technologies.