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This paper briefly reviews the history of meta-learning and describes itscontribution to general AI. Meta-learning improves model generalizationcapacity and devises general algorithms applicable to both in-distribution andout-of-distribution tasks potentially. General AI replaces task-specific modelswith general algorithmic systems introducing higher level of automation insolving diverse tasks using AI. We summarize main contributions ofmeta-learning to the developments in general AI, including memory module,meta-learner, coevolution, curiosity, forgetting and AI-generating algorithm.We present connections between meta-learning and general AI and discuss howmeta-learning can be used to formulate general AI algorithms.

A Brief Survey of Associations Between Meta-Learning and General AI