
Michael Nielsen – How science actually progresses
Dwarkesh Patel... · 123:03 · 4 695 écoutes
De l'album Dwarkesh Podcast
Description
The key question in this conversation is, how do we recognize scientific progress?It's especially relevant for closing the RL verification for scientific discovery. But it’s also a surprisingly mysterious and elusive question when you analyze the history of human science.We approach this question through the stories of Einstein (who claimed that he hadn't even heard of the famous Michaelson Morely experiment which is supposed to have motivated special relativity until after he had come up with it), Darwin (why did it take till 1859 to lay out an idea whose essence every farmer since antiquity must have observed?, Prout (how do you recognize that isotopes exist if you cannot chemically separate them?), and many others.The verification loop on scientific ideas is often extremely long and weirdly hostile. Ancient Athenians dismissed Aristarchus's heliocentrism in the 2nd century BC because it would imply that the stars should shift in the sky as the Earth orbits the sun. The first successful measurement of stellar parallax was in 1838. That's a 2,000-year verification loop.But clearly human science is able to make progress faster than raw experimental falsification/verification would imply, and in cases where experiments are very ambiguous. How?Michael has some very deep and provocative hypotheses about the nature of progress. One I found especially thought-provoking is that aliens will likely have a VERY different science + tech stack that us. Which contradicts the common sense picture of a linear tech tree that I was assuming. And has some interesting implications about how future civilizations might trade and cooperate with each other.So many other interesting ideas. Really hope you enjoy this as much as I did.Sponsors* Labelbox researchers built a new safety benchmark. Why? Well, current safety benchmarks claim that attacks on top models are successful only a few percent of the time, but the prompts in those benchmarks don’t reflect how real bad actors actually write. You can read Labelbox’s research here: https
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