With Artificial Intelligence deeply embedded in contemporary life, are we witnessing a fundamental shift in research? Or just new tools to seamlessly integrate into our workflows? Growth in massive many-parameter LLMs in chemistry includes those specifically trained for the field, but also general-purpose models tested for chemistry competence. Impressive claims have been made for LLMs’ chemical applicability. With cheminformatics and QSAR having evolved progressively from simple linear regressions into Chemical Machine Learning, our subject is ideally positioned to pioneer and reflect thoughtfully upon these developing technologies.
In education, an ever-increasing majority of students use AI as a go-to study resource. Is this the endgame for Higher Education and scholarship? Or, like the calculator and internet, can AI be flexibly incorporated into our teaching? Addressing these questions is essential in a world where the carefully considered, well-informed and appropriate use of AI is an essential skill for young researchers and graduates.
