This post summarizes the key ideas from Zhang et al. (2026), “Molecular Knowledge Representations in the Era of Artificial Intelligence,” a preprint published on ChemRxiv (DOI: 10.26434/chemrxiv.15002830/v1). The Core Problem Molecules are quantum-mechanical objects. Their exact description is computationally intractable, and any real sample is a messy mixture of impurities, conformers, and side products. This means every representation of a molecule is, by necessity, an approximation — shaped by the interactions and length scales we care about.
May 23, 2026
Simon Willison recently appeared on Lenny’s Podcast to discuss what he calls the November inflection point: the moment in late 2025 when frontier models crossed a threshold where agentic coding went from “mostly works if you watch carefully” to “almost always does what you asked.” His highlights post is worth reading in full, but reading it through the lens of computational drug discovery, several themes land with unusual force.
Apr 4, 2026