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Protein folding historically was more reliant on physical simulations. Like, David Shaw (of DE Shaw fame) had/has a team optimizing the hell out of simulations.
by danielmarkbruce 2y ago
Protein folding historically was more reliant on physical simulations. Like, David Shaw (of DE Shaw fame) had/has a team optimizing the hell out of simulations. There are oodles of fields (like weather) doing similar, and they are finding they can use statistical models where they previously thought they couldn't.
- passion__desire 2y agoImagine a futuristic sci-fi scenario in which AI is so advanced that it can model so deep into physics (i.e. plank scale), a scale which can't be probed by experiments but the predictions match. We would have a probabilistic Oracle of sorts. It can give answers but no way of knowing why it works.
- danielmarkbruce 2y agoI don't think the why is that confusing. If you do a physical simulation, so many calculations cancel each other out or work in opposite directions. If there is a pattern to it (and it appears there is for many situations), you just short cut it. Consider Roger Federer's ability to predict where a tennis ball will land and how to send electrical signals to his body to move in a way that will return that ball with high precision. It's pretty wild the number of short cuts he can make for what is a very complex calculation.
- danielmarkbruce 2y agoOn second thought, I missed your point, I think. In my example we could reason through why the tennis ball ended where it did. In yours, we couldn't. My bad.
- passion__desire 2y agoI agree with your point of calculations cancelling out. That's why I am not a fan of Butterfly effect. Just as Lewis coined unbirthday, we should coin Unbutterfly effect cancelling each other out.