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PaperclipPerfector  7d ago (text post)   23765 thread views

Culture War Roundup for the week of October 12, 2026

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No experimental data is overstating it, but he didn't need to collect any fresh data tailored to his ideas. Someone else (presumably) would have eventually gotten to relativity if they ran a series of experiments narrowing down what the heck is happening with time and lightspeed.

He simply figured it out with the data from experiment N-1 (or maybe N-2 or N-3), where a "normal" researcher would need the data from experiment N. If a future AI can pull off the same trick but better, then researchers will need to stay more than one dataset ahead of the public releases if they want to make a discovery first.

I basically agree with this but my impression is that modern experimental data is far more expensive and time-consuming to obtain than the data of the past.

That would make the gains to intelligence more important, not less.

If you can use the data from the Large Hadron Collider to make findings that most researchers would need the Future Circular Collider (its proposed successor) to find, then you've saved about $10B. Decades ago you couldn't have saved that much because people didn't spend that much.

That would make the gains to intelligence more important, not less.

I think this is probably correct, but my point is about a different issue, which is the issue of an AI company swooping in, making the discoveries, publishing them, and foreclosing the opportunities of the human researchers to make and publish the discoveries. This seems to be what is likely to happen in mathematics, if it's not happening already.

Arguably, with physics one could prevent this kind of scoop by keeping the data close to the vest. I'm pretty sure that even before AI got big, there were blackout periods with astronomical data. Although one can ask whether the situation is really that much better for individual researchers if most of what they are doing is feeding the proprietary data into their own AI.

But to your point, yeah, it seems that for scientific progress as a whole, AI analysis of experimental data would make things faster and more efficient.

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