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5min chapter
Can we build a generalist agent? Dr. Minqi Jiang and Dr. Marc Rigter
Machine Learning Street Talk (MLST)
Optimizing Generalization for Enhanced Model Performance
Exploring the nuances of decomposing performance in varied environments, the chapter highlights the pursuit of a universal motif for optimal model functioning. Touching on themes like generalization, data memorization, and task-specific training subsets, the discussion delves into improving out-of-distribution capabilities and leveraging complexity bias for better model performance.
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Discover
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Listen to the best highlights from the podcasts you love and dive into the full episode