It's kind of interesting that you contradict much of what the article concludes, even though the article gives a lot of examples. Maybe your prediction will be true.
We do. First off we have a public parquet-format index of all of the urls we crawl every month. And then that also lives in a HDFS table that determines when we want to recrawl a page we've crawled before.
Appreciate your kind words! Many people have worked at Common Crawl over the years, and it's been a labor of love fueled by positive comments like yours and the large list of PhD theses helped by our public web dataset.
If you're referring to Common Crawl, which has existed since 2008, indeed your predictions are somewhat accurate. It's easy to opt out or limit what is collected. The crawling itself is inexpensive to us and the hosting is from the AWS Open Dataset Sponsorship Program. And there's no charge for downloading it.
We aren't sure if that really made a significant difference in Common Crawl's data quality. It does hurt our dataset from a humanities point of view, alas.
A lot of websites want "bot defense" due to high volume scrapers, and that "bot defense" often also ends up blocking low-volume wget/curl and polite crawlers like Common Crawl's CCBot.
I don't know of anyone who uses Common Crawl as pre-training data without filtering it. We have an annotation system that lets people pick and choose which subsets they'd like to use.
Common Crawl is switching to reporting dataset sizes in nibbles. As an organisation dedicated to data preservation, we feel it would be remiss to allow this underrepresented unit to fall out of use. Our latest crawl now exceeds 689 tebibbles.
Common Crawl Foundation