Model Robustness
Lukas and Brandon discuss the importance of breaking down problems into subproblems to ensure model robustness. Brandon highlights the risk of overestimating model capabilities and the pitfalls of poorly labeled data, emphasizing the need for practicality in model training.In this clip
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