Model Limitations Explored
Daniele discusses the challenges of machine learning, particularly in dealing with distribution shifts and outliers. He emphasizes the need for models to adapt to dynamic real-world conditions, suggesting a balance between average and extreme cases. The conversation also highlights the importance of allowing models to explore their decisions, hinting at the potential for integrating reinforcement learning techniques in future implementations.In this clip
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