Continual Learning in AI Models: Tackling Catastrophic Forgetting Meta Description : Explore how continual learning helps AI models retain knowledge over time, overcoming catastrophic forgetting and enabling adaptive, lifelong learning in dynamic environments. Introduction Traditional AI models are trained once on a fixed dataset and then deployed for use. However, when exposed to new data, these models often struggle to retain previously learned knowledge—a phenomenon known as catastrophic forgetting . This limitation prevents AI from adapting to dynamic, real-world environments where new information constantly emerges. Continual learning (CL) , also known as lifelong learning , addresses this challenge by enabling AI models to learn incrementally, retaining old knowledge while adapting to new tasks. In this blog, we’ll explore how continual learning works, its significance, key techniques, and applications across industries. What is Continual Learning in AI? Continual l...
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