Natural language processing models that automate programming will transform chemistry research and teaching

Author:

Hocky Glen M.1ORCID,White Andrew D.2ORCID

Affiliation:

1. Department of Chemistry, New York University, USA

2. Department of Chemical Engineering, University of Rochester, USA

Abstract

Natural language processing models have emerged that can generate useable software and automate a number of programming tasks with high fidelity.

Funder

National Institute of General Medical Sciences

Publisher

Royal Society of Chemistry (RSC)

Reference31 articles.

1. M.Chen , J.Tworek , H.Jun , Q.Yuan , H.Ponde , J.Kaplan , H.Edwards , Y.Burda , N.Joseph and G.Brockman , et al. , Evaluating large language models trained on code , arXiv:2107.03374, 2021

2. A.Vaswani , N.Shazeer , N.Parmar , J.Uszkoreit , L.Jones , A. N.Gomez , Ł.Kaiser and I.Polosukhin , Attention is all you need , in Advances in neural information processing systems , 2017 , pp. 5998–6008

3. J.Devlin , M.-W.Chang , K.Lee and K.Toutanova , Bert: Pre-training of deep bidirectional transformers for language understanding , arXiv:1810.04805, 2018

4. More generally, “tokens” are masked

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