State-of-the-art design for computer language processing results in improved models for predicting chemistry
A program for predicting reaction outcomes and retrosynthetic steps has been developed using a cutting-edge approach for translating languages. Named Molecular Transformer, the software uses a new type of neural network that is easier to train and more accurate than the ones that powered earlier translation-based approaches to chemistry.