Git forges will expose a version of every file at every commit in the project's history. If you have medium sized project consisting of say 1000 files and 10,000 commits, the crawler will identify a number of URLs on the same order of magnitude as English Wikipedia, just for that one project. This is also very expensive for the git forge, as it needs to reconstruct the historical files from a bunch of commits.
Git forges interact spectacularly poorly with naively implemented web crawlers, unless the crawlers put in logic to avoid exhaustively crawling git forges. You honestly get a pretty long way just excluding URLs with long base64-like path elements, which isn't hard but it's also not obvious.
Because big sites have decades of experience fighting against scrapers and have recently upped their game significantly (even when doing so carries some SEO costs) so that they're the only ones that can train AI on their own data.
So now, when you're starting from scratch and your goal is to gather as much data as possible, targetting smaller sites with weak / non-existent scraping protection is the path of least resistence.
Because people are reporting constant traffic, which would imply that the site is being scraped millions of times per year. How does that make any sense? Are there millions of AI companies?
- have data to train on
- update the data more or less continuously
- answer queries from users on the fly
With a lot of AI companies, that generates a lot of scraping. Also, some of them behave terribly when scraping or is just bad at it.