Synthetic Books

TL;DR

The paper introduces the concept of synthetic books created using AI language models, discussing their artistic value, challenges, and potential in redefining written language and art.

Contribution

It proposes the new concept of synthetic books generated by autoregressive AI models and explores their artistic and contextual implications through case studies.

Findings

Synthetic books are created using AI language models like GPT-2 and GPT-3.

Artistic quality of AI-generated content remains a challenge.

Interactive projects demonstrate new artistic possibilities with AI-generated text.

Abstract

The article explores new ways of written language aided by AI technologies, like GPT-2 and GPT-3. The question that is stated in the paper is not about whether these novel technologies will eventually replace authored books, but how to relate to and contextualize such publications and what kind of new tools, processes, and ideas are behind them. For that purpose, a new concept of synthetic books is introduced in the article. It stands for the publications created by deploying AI technology, more precisely autoregressive language models that are able to generate human-like text. Supported by the case studies, the value and reasoning of the synthetic books are discussed. The paper emphasizes that artistic quality is an issue when it comes to AI-generated content. The article introduces projects that demonstrate an interactive input by an artist and/or audience combined with the deep-learning-based language models. In the end, the paper focuses on understanding the neural aesthetics of written language in the art context.