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606: Do What Works, Not What's Satisfying: Pseudo-Striving and our Fear of Reality-Based Planning by Cal Newport
Cal Newport asks why we never model our actions after those who have succeeded before us, and offers his opinion on it. Episode 606: Do What Works, Not What's Satisfying: Pseudo-Striving and our Fear of Reality-Based Planning by Cal Newport (Learning). Cal Newport is an Associate Professor of Computer Science at Georgetown University, who specializes in the theory of distributed algorithms. He previously earned his Ph.D. from MIT in 2009 and graduated from Dartmouth College in 2004. In addition to studying the theoretical foundations of our digital age as a professor, Newport also writes…
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