Generative AI
Applied generative modeling offers an opportunity to reformulate design and discovery in the chemical sciences. Examples of generative models that suggest unexplored chemical species are now abundant. I believe it is time to look beyond demonstrating the operability of generative models and move toward their practical implementation for solving scientific challenges. Arguably, a holy grail of modern […]
AIMNet2: A Neural Network Potential to Meet your Neutral, Charged, Organic, and Elemental-Organic Needs
In our latest paper, we present the 2nd generation of our atoms-in-molecules neural network potential (AIMNet2), which is applicable to species composed of up to 14 chemical elements in both neutral and charged states, making it a valuable model for modeling the majority of non-metallic compounds. Using an exhaustive dataset of 20 million hybrid quantum […]