Trends in Machine Learning & Deep Learning with Zachary Lipton - #556
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Challenges in Machine Learning Research
This chapter explores the disconnect between the ambitious promises of AI companies and the real-world challenges encountered in machine learning applications. It emphasizes the need for a stronger focus on decision-making, robustness, and fundamental problems, like causal inference and ethical alignment, rather than just predictive modeling. The discussion also sheds light on the complexities of domain adaptation, causal learning, and the integration of multiple datasets to improve outcomes in uncertain conditions.
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