The laboratory has long provided a physical hub for research. These physical spaces are increasingly digitised, integrating automated devices to support research. Computational tools are also becoming important enablers of scientific practices, allowing researchers to interrogate large datasets and extract novel insights. Extending these practices opens the possibility of new virtual labs, which leverage AI to accelerate discovery, by enhancing researchers’ ability to progress their ideas. This vision of AI-enabled innovation through virtual laboratories is the focus of work by Samuel Kaski, ELISE Coordinator and co-Director of the ELISE Robust Machine Learning Programme, and his teams at the Finnish Center for Artificial Intelligence and University of Manchester.

Achieving this vision requires AI that can facilitate the scientific method. AI techniques already underpin analytical tools such as simulation, emulation, and digital twins that are embedded in today’s scientific practices. More sophisticated AI methods could increase the power of these simulations, by combining different data sources, integrating pre-existing domain knowledge to increase the scientific relevance of results, and returning information to human users as actionable, explainable insights.

Read more about AI-assisted Virtual Laboratories as part of the ELISE Strategic Research Agenda →