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#92 - SARA HOOKER - Fairness, Interpretability, Language Models

Machine Learning Street Talk (MLST)

CHAPTER

Navigating the Challenges of SOTA Chasing and Value Reflection in Models

This chapter delves into the trend of SOTA chasing in machine learning, highlighting the limitations of merely increasing model size and data. The discussion emphasizes the importance of model efficiency and adapting to evolving human values and beliefs in the quest for fairness.

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