Amazon’s Architecture for Continual Learning
The research proposes a novel AutoML-based architecture to solve one of the toughest challenges in ML.
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Continual learning is one of the most monumental challenges in modern machine learning(ML). The traditional paradigm in ML evolves around training( or pretraining these days) models with human intervention. From a practical standpoint, this paradigm causes models to be “stuck on time” in terms of knowledge at any given time. Continual learning is an emerging paradigm to build ML models that can incrementally improve their knowledge. One of the most innovative work in this space came from Amazon Science( Amazon’s research division) published in a 2019 paper proposing a…
