Excellent optimistic post in a sea of negativity, and with actual suggestions, too. After reading, my mental image is this: think of Olympiads in Ancient Greece.
* A weightlifter was only awarded a laureate if he were able to lift a heavy stone (have no idea what they were lifting, for illustrative purposes only :-)
* Along comes Archimedes who invents what we would call an exoskeleton. Now any regular guy can lift twice as much as last year’s athlete.
* What to do? You can cancel the Olympiads, but they are actually useful as training, motivation, etc So now you have to give the prize on other factors, eg how well he can lift, has he opened a gym in the city, etc
BTW, physics and bio are not exempt, so those researchers better read and try to stay ahead.
I don´t think so. For programming agents can run code, check compiler output, etc. For mathematics, it is almost the same once you factor in the usage of lean.
For the reality, you can´t close the loop that fast, or with that precision. You will have to slow down by several orders of magnitude.
Doesn’t have to. There are petabytes of experimental physics data that can be fed to AI to extract additional insights. The only holdup is this is slightly harder to than math. With bio, you’re right, generally designing and conducting an experiment goes hand in hand and theoretical biologist is not a common label.
>There are petabytes of experimental physics data..
There is one thing you are missing. Math is precise. Physical measurements are arbitrary imprecise...