A new database containing millions of public domain books is being released, providing researchers and developers with a wealth of data for training AI models. The initiative aims to democratize access to high-quality training data, leveling the playing field for smaller players in the AI industry.
Around five times the size of the Books3 dataset, the Institutional Data Initiative's database includes a vast collection of public domain works spanning genres, decades, and languages. Classics from Shakespeare, Dickens, and Dante are featured alongside lesser-known texts like Czech math textbooks and Welsh dictionaries.
Greg Leppert, executive director of the Institutional Data Initiative, sees this project as a way to democratize access to high-quality training data, leveling the playing field for smaller AI players and individual researchers. Leppert believes this public domain database, when combined with licensed materials, can be used to build powerful AI models. He compares it to the open-source operating system Linux, suggesting that while companies would still need additional data for differentiation, this initiative provides a foundational resource. Microsoft, a supporter of the project, emphasizes its commitment to creating accessible data pools for AI startups, managed in the public interest. Though Microsoft utilizes publicly available data in its own models, they don't necessarily plan to replace all proprietary data with public domain alternatives. OpenAI has also expressed its delight in supporting the project
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