WHITEPAPER
Materials Informatics: Artificial Intelligence for Curation of Information and Knowledge Acquisition
This booklet is a copy of the original chapter Artificial intelligence for curation of information and knowledge acquisition authored by Christopher L. Farrow, PhD and Alexandre Chabot-Leclerc, PhD of Enthought from the book Next-generation Materials Development Using Materials Informatics, Quantum Computers, Natural Language Processing, and Autonomous Experimental Systems (マテリアルズインフォマティクス・量子コンピュータおよび自然言語処理と自律型実験システムを活用した次世代材料開発).
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ABSTRACT
As competition in new material development intensifies, the importance of knowledge acquisition to accelerate R&D is increasing. The chapter explains how artificial intelligence can contribute to knowledge acquisition. The process of transforming information into knowledge can be divided into two stages: “curation” and “knowledge acquisition.” AI supports both stages by integrating information, assigning meaning, and facilitating researchers’ access to this knowledge. The scientific search system includes components developed in collaboration with our clients and is currently being used in real-world applications.
OUTLINE
Introduction
1. Technology-Assisted Curation
1.1 Curation as Search
1.1.1 NLP-enhanced search
1.1.2 Image Search
1.1.3 Table Search and Domain-Specific Search
1.1.4 Extracting Data from Graphs
1.2 Limitations of Search
2. Generative AI for Curation
2.1 Everything Can Become Text
2.2 Text Can Become Data
2.3 Beyond Text Search: Multi-Modal Embeddings
3. Generative AI for Knowledge Acquisition
3.1 Retrieval-Augmented Generation for Answering Questions
3.2 Agents for Doing Work
3.3 Embeddings for Making Connections
Conclusion
References
Questions? Contact us to get connected to Enthought's Materials Informatics experts.
The full book can be purchased from the publisher's website.
