As others said, it's not that this isn't a phenomenon that is unique to now. It happens. I had to pivot a bit of my dissertation near the end because at a random conference I spoke with a researcher from another continent and realized one of my ideas was already out there in some form. I just missed it since it was in a conference proceedings outside the usual set I looked at. So, I had to scramble to adjust and still come up with something novel. I survived, and defended, but it wasn't that much fun at the time.

What isn't so normal is the probability and ease by which this kind of thing can happen today versus decades ago when I was in school. As OpenAI said, it only takes a few hours of compute to do what likely was much more than a few hours of human effort. The only reason this kind of scooping/overlapping was rare was mostly a function of how fast other humans could do the same work. With machines, that totally changes the relative pacing between the human trying to learn how to be a researcher and the machine that can grind out results.

I'm less worried about the phenomenon of overlap and scooping and such. I'm more worried about the long-term impact on fields (not just math), especially considering the early stage students and researchers entering the pipeline now. I'm not sure what happens to disciplines when that pipeline stalls.