Trends in Graph Machine Learning with Michael Bronstein - #446
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Ethics and Advancements in Machine Learning
This chapter explores the ethical complexities in machine learning, emphasizing the need for a global perspective beyond U.S.-centric views, particularly concerning racial bias and the use of technology in oppressive environments. It also highlights recent advancements in graph neural networks and implicit representations, discussing their implications for algorithm design and applications across different fields, including healthcare. The conversation bridges the gap between classical algorithms and neural networks, underscoring the need for interdisciplinary collaboration to address ethical concerns and technical challenges.
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