There is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively [1, 2]. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas.
Walking intrigues the deskbound. We romanticize it, but do we do it justice? Do we walk properly? Can one walk improperly and, if so, what happens when the walk is corrected?
This talk centered on Hamming's observations and research on the question "Why do so few scientists make significant contributions and so many are forgotten in the long run?"
A Fermi estimate is a quick-and-dirty solution to an arbitrary scientific or engineering analysis problem. Fermi estimation uses widely known numbers, readily observable phenomenology, basic physics equations, and a bunch of approximation techniques to arrive at rough answers that tend to be correct within an order of magnitude or so. The term is named for Enrico Fermi, who was famously good at this sort of thing.
…It struck me that there is counterpart to this kind of thinking on the synthesis side, where you use similar techniques to arrive at a very rough design for a complex engineered artifact. I call such a design approach Dyson design, after the physicist Freeman Dyson, who was one of the best practitioners of it (not to be confused with inventor James Dyson, whose designs, ironically, are not Dyson designs).