MaxLearn ‘Ebbinghaus’ Forgetting Curve

What it does

Combat Ebbinghaus' Forgetting Curve with MaxLearn's Microlearning approach. Stay ahead, retain more, and revolutionize learning with us today!

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  Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking token costs and degrading the agent's reasoning. This implementation experiments with a biological approach by using the Ebbinghaus forgetting curve to manage context as a living substrate. Memories are assigned a "strength" score where each recall reinforces the data and flattens its decay curve (spaced repetition), while unused data eventually hits a threshold and is pruned. To solve the…

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