The true power of artificial intelligence (AI) for chemical research is in addressing challenges that are difficult or impossible to solve using conventional methods. Already, AI techniques are being tailored to identify patterns in chemical datasets 1 , predict reaction outcomes 2 , and accelerate discovery and optimisation cycles . The efficient navigation of chemical space, exploring or targeting relevant regions in the high-dimensional composition-structure-property landscape, remains one of the longstanding goals in computational chemistry.