Neural networks have taken the world of computing in general and AI in particular by storm. But in the future, AI will need to revisit generative models. There are several reasons for this – system robustness, precision, transparency, and the high cost of labelling data. This is particularly true of perceptual AI, as needed for autonomous vehicles, where also the need for simulators and the need to confront novel situations, also will demand generative, probabilistic models.
Biography: Professor Andrew Blake is Research Director at The Alan Turing Institute. Prior to joining the Institute in 2015, Professor Blake held the position of Microsoft Distinguished Scientist and Laboratory Director of Microsoft Research Cambridge, England. He joined Microsoft in 1999 as a Senior Researcher to found the Computer Vision group. In 2008 he became a Deputy Managing Director at the lab, before assuming the directorship in 2010. Before joining Microsoft Andrew trained in mathematics and electrical engineering in Cambridge England, and studied for a doctorate in Artificial Intelligence in Edinburgh. He was an academic for 18 years, latterly on the faculty at Oxford University, where he was a pioneer in the development of the theory and algorithms that can make it possible for computers to behave as seeing machines.
Professor Blake has published several books including “Visual Reconstruction” with A.Zisserman (MIT press), “Active Vision” with A. Yuille (MIT Press) and “Active Contours” with M. Isard (Springer-Verlag). He has twice won the prize of the European Conference on Computer Vision, with R. Cipolla in 1992 and with M. Isard in 1996, and was awarded the IEEE David Marr Prize (jointly with K. Toyama) in 2001.