Springer Nature Publishes Lithium–ion Battery Book Written by Machine Learning Algorithm


The book is a compilation of a large number of current research articles about lithium-ion batteries.

Springer Nature, a leading academic and educational publisher, has published a book written entirely by machine-learning algorithms.

The book prototype provides an overview of the latest research in the rapidly growing field of lithium-ion batteries. It is a compilation of a large number of current research articles about lithium-ion batteries.

The publisher collaborated with researchers from Goethe University Frankfurt to develop a state-of-the-art algorithm, called Beta Writer, to select, consume and process relevant publications in the field of lithium-ion batteries from Springer Nature’s content platform SpringerLink.

Based on this peer-reviewed and published content, the Beta Writer uses a similarity-based clustering routine to arrange the source documents into coherent chapters and sections. It then creates succinct summaries of the articles.

The extracted quotes are referenced by hyperlinks which allow readers to further explore the original source documents. Automatically created introductions, table of contents and references facilitate the orientation within the book.

What the publisher says?

Niels Peter Thomas, Managing Director Books at Springer Nature, said, “New technologies around Natural Language Processing and Artificial Intelligence offer promising opportunities for us to explore the generation of scientific content with the help of algorithms. As a global publisher, it is our responsibility to take potential implications and limitations of machine-generated content into consideration, and to provide a reasonable framework for this new type of content for the future.”

Henning Schoenenberger, Director Product Data & Metadata Management at Springer Nature, added, “This prototype is a first important milestone we reached, and it will hopefully also initiate a public debate on the opportunities, implications, challenges and potential risks of machine-generated content in scholarly publishing.”

In the future, Springer Nature plans to expand this pilot project by developing prototypes for content from other subject areas as well.

Springer Nature’s first machine-generated book is available as eBook and print book. The eBook is freely available for readers on SpringerLink.