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This week Ryan and I discuss two editorials on machine learning and its impact and use within Research. The first paper is an Editorial by Rob Arnott, Cam Harvey, and Harry Markowitz discussing, in their opinion, proper protocols for research (back-testing) in the era of machine learning. The Second paper, summarized by Elisabetta, is by Joseph Simonian, Marcos Lopez de Prado, and Frank Fabozzi. In their paper, they discuss, at a high-level, how data science and machine learning can help research.