Brilliant application. Imagine the progress we could make with models post trained on scientific process and a good agentic process.
I've been tinkering with the latter for the last couple of months. Yesterday my system made some progress on instabilities on a particular superconductive system: https://colinocallaghan.com/autonomous-ai-research/Spatial-P...
So much AI in the writing. If you dont care to write i do not care to read.
Cool discovery, but I'd be real curious about the false-positive rate when letting coding agents loose on raw astronomical telemetry. Hallucinations in data reduction are no joke.
Call me when peer review confirms it; until then, it is noise fitting noise. (Reason: Clean cut through the hype directly to scientific validation.)
This is incredible use of AI tools. Big kudos!
Plot twist: The discovery is valid. But we figure out the author was not a innocent PM, but a team of astronomers working for Anthropic, And Anthropic's marketing department come up with the idea of crediting it to a PM. :-D
Found a planet and saved a granny. Wake me up when this planet is acknowledged by any astonomer community with more say than r/ClaudeAI.
Not an astronomer, but I'm a non-programmer who spent two months building a fairly big web app with Claude, so the false-positive question is the one I'd ask too.
What saved me wasn't asking Claude whether it was right (it almost always says yes). It was checks that don't depend on its own report: run it on data where you already know the answer, and give a fresh session only the result and ask it to break it.
For a planet hunt I guess that means hiding a few fake planets in real data to see if it finds them, and running the same pipeline on shuffled data to see how many "planets" it finds in pure noise.
[dead]
Laughed at the reddit comment
> "We got vibe astronomy before GTA6"