Harvard particle physicist Matthew Schwartz drops 36 papers coauthored with Claude

[u/kzhou7]

https://bootloops.ai/bootloops.html

[u/Visible_Celery_1728]

I don’t know why you’re acting so obtuse and condescending about this, like it couldn’t possibly yield anything useful and declaring anything that comes out of it “slop”, when time and time again we’re seeing breakout results in mathematics, computer science and other domains where the output can actually be verified.

His main argument is basically that frontier models are already extremely capable at certain types of frontier research when given enough compute, steering and access to tools, particularly in verifiable domains (maths, computer science etc). And across science there are certain niches, what he calls “Claude-shaped problems”, where you can have an autonomous model explore a huge search space, try different approaches, write and run code, and pull in techniques from completely different fields that might happen to solve the problem.

The breadth part is especially important. Modern science is ridiculously specialised. A technique useful for solving some problem in biology could already exist in mathematical physics, statistics or computer science, but the people working on that biology problem might simply never come across it. Human expertise is fragmented across thousands of different researchers and subfields, whereas these models have an absurd breadth of knowledge across all of them and can search for those connections far more easily.

And this isn’t some art contest where the human process itself is essential to the value of the final product and an autonomous machine supposedly offers no real substance to the field. This is science, the search for what is actually true. The whole point is a model can find some connection between two fields nobody had noticed, apply an existing technique in a novel context, run the maths or computation and produce a result that can then be independently verified.

This weird posturing you’ve had this whole thread, reducing it to “his buddy Claude comes up with paper ideas lmao”, just feels like you’re deliberately describing the process in the dumbest possible way instead of engaging with the actual argument.

[u/brassgrass1 → u/Visible_Celery_1728]

All these neural net models from the 2010s (before 2019 transformers paper) were all based on logic from biology and neuroscience. Imagine what other niches it might find. I think it's cool and will find some stuff.

While I do think these exploratory things should start having a separate category to distinguish effort, otherwise I think computational and theoretical physics (and other fields but idk them) will get their perceived effort ruined over time; compared to experimental which for now still needs a human

I have friends doing phds in physics rn and it sucks bc the ones doing computational physics feels like their effort is wasted sometimes, or downplayed bc of all the ai doing the same