Conventionally design-of-experiments, Bayesian optimization, or recently Bandit optimization, systematically plans and conducts experimental investigations using statistical methods to efficiently explore chemical processes, optimize parameters, and understand the effects of multiple variables on outcomes. Large-language models: Large-language models for chemistry utilize vast amounts of text data and advanced natural language processing techniques (Figure ) to generate insights, predict properties, and assist in discovery (Figure ) and materials design within chemistry. , Gabe Gomes recently showed that a large-language model could be integrated into a chemical workflow (Figure ). Figure . Large language model in chemistry by Gomes et al. In a consortial effort, researchers from IBM, Oxford University, and Enamine drug target inhibitor discovery with a deep generative foundation model. They target a protein sequenceconditioned sampling on the generative foundation model to design small-molecule inhibitors for two dissimilar targets: the spike protein receptor-binding domain (RBD) and the main protease from SARS-CoV-2 (Figure ). Figure : Selected compounds from a large library Identified for COVID Analyze analytical data with artificial intelligence: Artificial intelligence analyzes analytical data by employing advanced algorithms and computational techniques to extract insights, patterns, and correlations, enhancing decision-making and predictive modeling capabilities. In particular, generative artificial models like Foundation Models or LLM and Artificial General Intelligence (AGI) will play a role in the future.