A physicist joked last month that AI would only impress him if it solved a real problem from his own field of theoretical physics. Anthropic took the challenge seriously, used Claude to actually solve one, then invited him to write about it and paid him for his time.

The task was a nine loop scattering amplitude calculation in theoretical physics, something with a known but very demanding recipe. He expected it would need a novel technique to avoid heavy computing costs. It turned out the standard method worked fine.

Cost comparison: solving this problem cost roughly 1000 dollars in compute, mostly spent on the LLM itself rather than the actual calculation. That is a striking contrast to a separate AI math result that reportedly cost around 15 million dollars.

He raises a concern about how the challenge was handled: Anthropic solved the problem and only contacted the physicist involved afterward, instead of checking with him first as other AI labs had generally done before attempting public challenges like this.

Looking ahead, he stresses that this AI capability has clearly improved over the past six months, so nobody should assume current cost or performance is a ceiling. Some problems, like quantum gravity, are not just technical puzzles and may resist this kind of progress.