The Machine and Human Intelligence research group led by Assistant Professor Luigi Acerbi focuses on probabilistic machine and human learning. We study brains and computers alike as statistical inference engines which are probabilistic, approximate, active, robust, and resource-constrained. We develop new methods for approximate Bayesian inference both as tools for artificial intelligence and as models of human intelligence. The group is part of the Department of Computer Science and of the Finnish Center for Artificial Intelligence (FCAI).