Learning continually with representational drift
Analysis
This article likely discusses a research paper on continual learning in the context of AI, specifically focusing on how representational drift impacts the performance of learning models over time. The focus is on addressing the challenges of maintaining performance as models are exposed to new data and tasks.
Key Takeaways
Reference
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