Four of our talented fellows, @ahunklinger.bsky.social, Fabian Krüger, Matt Ball and Bob van Schendel presented a poster on how academia-industry partnerships drive #innovation in #drugdiscovery at #AIS25. They did a fantastic job representing AiChemist and the #MSCA! 👏

In our newest preprint, we discuss current explainable AI (XAI) methods. We divided the workflow of a generative decoder-only model into four information contexts for XAI: training dataset, input query, model components, and output sequence. See here: arxiv.org/abs/2506.19532 @aichemist.bsky.social

Are you curious about what protein language models learn? Check out our newest preprint! 🚀https://arxiv.org/abs/2506.19532 We reviewed explainable AI (XAI) techniques across all parts of the generative protein design workflow and discussed their applications, limitations, and untapped potential!