The role of libraries in the age of artificial intelligence: an analytical look at emerging AI technologies and their applications

Abstract

This comprehensive study presents a fundamental analysis of the transformation of the functional role of modern scientific libraries in the context of global «digital uncertainty» and the exponential development of generative artificial intelligence technologies. The authors conduct a deep retrospective review of the evolution of neural network architectures – from Frank Rosenblatt’s first probabilistic perceptron models and recurrent networks that solved the problem of long-term memory, to modern Transformers and Large Language Models, justifying the inevitability of the current technological transition. The study systematizes advanced generative AI tools, including diffusion visualization models (Stable Diffusion), speech recognition technologies, and document structure understanding, with a detailed assessment of the prospects for their implementation in cultural heritage preservation processes. Special emphasis is placed on the risks of «information noise», neural network hallucinations, and the blurring of the concept of authorship, which updates the library’s new mission as a guarantor of verified knowledge in accordance with the International Federation of Library Associations principles. The practical significance of the research lies in the detailed technical description of the experience of the Central Scientific Library of the Irkutsk Institute of Chemistry named after A.E. Favorskii of the Siberian Branch of the Russian Academy of Sciences in developing an autonomous intelligent search system. The architecture of the solution based on the Retrieval Augmented Generation methodology, local large language models, and efficient fine-tuning methods is presented, ensuring deep semantic search across chemical collections while maintaining full data sovereignty and answer verifiability.