<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Datasets — The Latent Daily</title><description>Public datasets and new data releases.</description><link>https://thelatentdaily.com/</link><language>en-us</language><atom:link href="https://thelatentdaily.com/rss/datasets-research.xml" rel="self" type="application/rss+xml"/><item><title>The Pile explained: the open dataset that helped democratize language models</title><link>https://thelatentdaily.com/research/the-pile-dataset-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/the-pile-dataset-explained/</guid><description>EleutherAI&apos;s 825 GB Pile combined 22 diverse text sources into an open training set. What it contained, why diversity mattered and the copyright questions it raised.</description><pubDate>Sun, 18 Oct 2026 05:09:00 GMT</pubDate><category>Datasets</category><category>research</category><category>datasets</category><category>training-data</category><category>eleutherai</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>FineWeb and Common Crawl explained: how web data becomes training data</title><link>https://thelatentdaily.com/research/fineweb-common-crawl-training-data-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/fineweb-common-crawl-training-data-explained/</guid><description>Most language models learn from filtered web crawls. How Common Crawl works, how FineWeb cleaned 15 trillion tokens, and why filtering choices shape model quality.</description><pubDate>Sun, 18 Oct 2026 05:08:00 GMT</pubDate><category>Datasets</category><category>research</category><category>datasets</category><category>training-data</category><category>hugging-face</category><author>dario_admin@resolvia-crm.tech</author></item></channel></rss>