Embracing Uncertainty: The New Machine Intelligence
Computers are traditionally viewed as logical machines which follow precise, deterministic instructions.
The real world in which they operate, however, is full of complexity, ambiguity, and uncertainty. In this year’s Turing Lecture, Professor Chris Bishop discusses the field of machine learning, and shows how uncertainty can be modelled and quantified using probabilities.
He looks at the recent developments in probabilistic modelling which have greatly expanded the variety and scale of machine learning applications, and he explores the future potential for this technology.
In honour and recognition of Alan Turing’s contribution in the field of computing, the IET and the BCS established the Turing Lecture in 1999. It is a world leading event, presenting a topic from current research in computer science given by an acknowledged expert in the field.
Professor Bishop is Chief Research Scientist at the Microsoft Research Laboratory in Cambridge, and also holds a Chair in Computer Science in The University of Edinburgh School of Informatics. He presented the 2008 Royal Institution Christmas Lectures Hi-Tech Trek — The Quest for the Ultimate Computer.
He’s an excellent speaker, and this looks to be an interesting talk about recent advances in and applications of machine learning. There is a reception at 5pm, with the lecture at 5.30pm, and a ticket-only event afterwards. The lecture is free, but the IET ask for registration; which in turn means you need to create an account at the IET website; which means handing over address, phone number, eye colour, etc. Sorry about that.