Natural Language Processing Models That Automate Programming Will Transform Chemistry Research and Teaching

Abstract

Natural language processing models have emerged that can generate usable software and automate a number of programming tasks with high fidelity. These tools have yet to have an impact on the chemistry community. Yet, our initial testing demonstrates that this form of Artificial Intelligence is poised to transform chemistry and chemical engineering research. Here, we review developments that brought us to this point, examine applications in chemistry, and give our perspective on how this may fundamentally alter research and teaching.

6 pages, 3 figures, plus 8 page SI with additional examples and extended figure details

References in corpus (4)

• Evaluating Large Language Models Trained on Code
• Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
• Improving language models by retrieving from trillions of tokens
• Automatic code generation enables nuclear gradient computations for fully internally contracted multireference theory

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• Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems