Harvard University announced Thursday it’s releasing a high-quality dataset of nearly one million public-domain books that could be used by anyone to train large language models and other AI tools. From a report: The dataset was created by Harvard’s newly formed Institutional Data Initiative with funding from both Microsoft and OpenAI. It contains books scanned as part of the Google Books project that are no longer protected by copyright.

Around five times the size of the notorious Books3 dataset that was used to train AI models like Meta’s Llama, the Institutional Data Initiative’s database spans genres, decades, and languages, with classics from Shakespeare, Charles Dickens, and Dante included alongside obscure Czech math textbooks and Welsh pocket dictionaries. Greg Leppert, executive director of the Institutional Data Initiative, says the project is an attempt to “level the playing field” by giving the general public, including small players in the AI industry and individual researchers, access to the sort of highly-refined and curated content repositories that normally only established tech giants have the resources to assemble. “It’s gone through rigorous review,” he says.

Leppert believes the new public domain database could be used in conjunction with other licensed materials to build artificial intelligence models. “I think about it a bit like the way that Linux has become a foundational operating system for so much of the world,” he says, noting that companies would still need to use additional training data to differentiate their models from those of their competitors.