Plenary 1: Machines (that learn) to See


April 23, 2013


Andrew Blake


Microsoft Research


Andrew Blake, Distinguished Scientist, Lab Director of Microsoft Research Cambridge. Discusses the question of whether intelligent systems will turn out to depend more on theories and models, or simply on largely amorphous networks trained on data at ever great scale. The world of computer science and artificial intelligence can indulge in a bit of cautious celebration. There are several examples of machines that have the gift of sight, even if to a degree that is primitive on the scale of human or animal abilities. Machines can: navigate using vision; separate object from background; recognize a variety of objects, including the limbs of the human body. These abilities are great spin-offs in their own right, but are also part of an extended adventure in understanding the nature of intelligence.


Andrew Blake

Andrew Blake received his Ph.D. from the University of Edinburgh in 1983. Until 1987 he was on the faculty of the department of Computer Science at the University of Edinburgh and a Royal Society Research Fellow. From 1987 to 1999, he has been on the faculty of the Department of Engineering Science in the University of Oxford, where he ran the Visual Dynamics Research Group, became a Professor in 1996, and and was a Royal Society Senior Research Fellow for 1998-9. In 1999 he moved to Microsoft Research Cambridge as Senior Researcher working in Machine Learning and Perception, while continuing to be associated with the University of Oxford as Visiting Professor of Engineering. He was elected a Fellow of the Royal Academy of Engineering in 1998.