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Comment by bwfan123 | Hacker News Reader

> Jarred prompted Claude to try again, and it spent a day and a half coordinating about 60 Claude subagents, which this time went much deeper: between them, they ran 2,400 shell commands and wrote hundreds of Python scripts.1

If there is anything to learn from the history of science, it is that breakthroughs happen via better or new theory and not by brute-force compute [1].

[1] https://arxiv.org/pdf/2607.27794

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Nah, the main lesson is that fundamentally new ways of doing things are only accepted once the old guard are all dead [1].

[1] https://en.wikipedia.org/wiki/The_Structure_of_Scientific_Re...

This isn't 'brute-force'. It's just time-compressed. You could imagine a human(s) getting this result similarly, but it would take months/years.

It's a _little bit_ brute force, no? I don't disagree with the idea of a human following a similar path, but it ignores that humans have cognitive processes that may lead to pruning the search space in _different_ ways, and may ultimately mean fewer steps or a more directed path to the answer than 100s of python scripts.

We do “a little bit of brute force” in science all the time. That’s what I’ve observed in seven years of science.

Moreover, frontier models have some degree of reasoning. So, I don’t think the gap is all that big.

If you want to call "try multiple solutions to a hypothesis" brute force, then yes, literally all of engineering and science has been brute-forced since the beginning of history.

Brute-force compute hasn't been an option for most of the history of science.

Very true. Humans have historically tried to systematically reduce the search space and only dedicate their "compute" to things that seem highly likely to yield results.

It still isn't an option for most problems, either because it would take far more computing power than is available or because the number of things to compute is infinite. In both cases, new theory is what can succeed instead. Developing new theory by brute force can be attempted, but will almost always run into the same problems. Using AI to develop new theory is using heuristics rather than brute force.

But it does raise the bar for what is brute-force solvable by a lot, which is very significant

Sometimes you just need to put in some effort to looking through the search space, not even exhaustively. This seems to be able to do automate doing that work.

> If there is anything to learn from the history of science, it is that breakthroughs happen via better or new theory and not by brute-force compute

that might just be an illusion. humanity as a whole applies brute force by just trying all the reasonable new theories until one of us discovers something that works and declares it a breakthrough

Whether or not Thomas Edison actually said this, the saying goes genius is 1% inspiration and 99% perspiration, and that predates computers by decades.

I think that mathematics is a uniquely positioned space because this type of progress is possible for AI models exactly because they do not have to necessarily come up with new theories.

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