This is also a really common thing in ML specifically. We joke about getting Schmidthuber'd, which is when Jurgen Schmidthuber (sometimes correctly) announces that he or one of his colleagues actually proposed your thing 37 years ago in a Japanese linguists journal.

Statistical modeling, from simple classical stuff up to modern deep learning, just has this dynamic where the theory is rich and bottomless, but the actual components of implementation are pretty neat and compact. So for any given idea, there are probably 20,000 other people who have had the same intuition, just with subtly different application or implementation. Add in that depending on what your particular flavor of research is, you might name an almost identical implementation something completely different. And it leads to a huge amount of sour grapes whenever anyone's idea really garners attention.

If you listen to any podcast with a founder in the ML space who has been in it for long enough, they will invariably say at some point "We actually developed xyz over a year before OpenAI"