The history of science has tons of examples of the same thing being discovered multiple time independently; wikipedia has a whole list of examples here. If your goal in studying the history of science is to extract the predictable/overdetermined component of humanity's trajectory, then it makes sense to focus on such examples.
But if your goal is to achieve high counterfactual impact in your own research, then you should probably draw inspiration from the opposite: "singular" discoveries, i.e. discoveries which nobody else was anywhere close to figuring out. After all, if someone else would have figured it out shortly after anyways, then the discovery probably wasn't very counterfactually impactful.
Alas, nobody seems to have made a list of highly counterfactual scientific discoveries, to complement wikipedia's list of multiple discoveries.
To that end: what are some examples of discoveries which nobody else was anywhere close to figuring out?
A few tentative examples to kick things off:
- Shannon's information theory. The closest work I know of (notably Nyquist) was 20 years earlier, and had none of the core ideas of the theorems on fungibility of transmission. In the intervening 20 years, it seems nobody else got importantly closer to the core ideas of information theory.
- Einstein's special relativity. Poincaré and Lorentz had the math 20 years earlier IIRC, but nobody understood what the heck that math meant. Einstein brought the interpretation, and it seems nobody else got importantly closer to that interpretation in the intervening two decades.
- Penicillin. Gemini tells me that the antibiotic effects of mold had been noted 30 years earlier, but nobody investigated it as a medicine in all that time.
- Pasteur's work on the germ theory of disease. There had been both speculative theories and scattered empirical results as precedent decades earlier, but Pasteur was the first to bring together the microscope observations, theory, highly compelling empirical results, and successful applications. I don't know of anyone else who was close to putting all the pieces together, despite the obvious prerequisite technology (the microscope) having been available for two centuries by then.
(Feel free to debate any of these, as well as others' examples.)
Possibly Wantanabe's singular learning theory. The math is recent for math, but I think only like '70s recent, which is long given you're impressed by a 20-year math gap for Einstein. The first book was published in 2010, and the second in 2019, so possibly attributable to the deep learning revolution, but I don't know of anyone making the same math--except empirical stuff like the "neuron theory" of neural network learning which I was told about by you, empirical results like those here, and high-dimensional probability (which I haven't read, but whose cover alone indicates similar content).
I don't think these conditions are particularly weak at all. Any prior that fulfils it is a prior that would not be normalised right if the parameter-function map were one-to-one.
It's a kind of prior people like to use a lot, but that doesn't make it a sane choice.
A well-normalised prior for a regular model probably doesn't look very continuous... (read more)