AI Winter
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
Refers to a period when AI research and investment fall into a trough, usually after overly optimistic expectations fail to materialize, causing the public and investors to lose confidence, leading to a significant decline in funding and attention. There have been multiple AI winters in history, such as in the late 1970s and late 1980s.
SCAFFOLDING EFFECT
Reduce cognitive load
Technological cycle vigilance. During technology booms (such as current generative AI), it reminds us to stay rational, not blindly optimistic, and understand that technological development has its inherent cycles; excessive expectations often lead to disappointment and investment contraction.
Anchor fast decisions
Based on the Gartner Hype Cycle. The inflation of expectations leads to overpromising → reality falls short → disappointment and disinvestment → trough. The cycle repeats.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/AI_winterverified
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