Cal Newport:
>To capture the reality of this act, Rockmore tells a story from when he was a young professor. He was working with his colleagues to try to find a more efficient method for solving a large class of wave equations. “We spent every day drawing on blackboards and chasing one wrong idea after another,” he writes. Frustrated, he left the session to go for a run on a tree-lined path. Then it happened.
“As I crested the last hill, I saw it all at once: the key to modifying the algorithm we’d been puzzling over was to flip it around, to run it backward. My hear started racing as I pictured the computational elements strung out in the new opposite order. I sprinted straight home to find a pencil and paper so I could confirm it.”
As Rockmore then elaborates, in popular portrayals of mathematical machinations, the focus is often on this final bit, the eureka moment while jogging through the woods, or John Nash surveying the crowded Princeton bar and figuring out non-cooperative game theory all at once.
But this moment cannot come without the days of frustration at the blackboard. “You can’t really blame the storytellers,” Rockmore writes, “It’s not so exciting to read ‘and then she studied some more.’ But this arduous, mundane work is a key part of the process.”
This absolutely matches my experience as a professional theoretical computer scientist.<
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