Murray Shanahan is Professor of Cognitive Robotics in the Dept. of Computing at Imperial College London, where he heads the Neurodynamics Group. His publications span artificial intelligence, robotics, logic, dynamical systems, computational neuroscience, and philosophy of mind. He was scientific advisor to the film Ex Machina, which was partly inspired by his book “Embodiment and the Inner Life” (OUP, 2010).
In the two videos below, he describes what he sees as the main obstacles to achieving human-level artificial intelligence given the current state of machine learning, and suggests a number of ways these obstacles might be overcome. These include speculations on:
a) Geoff Hinton‘s notion of thought vectors,
b) hybrid symbolic-neural approaches, and
c) cognitive architectures inspired by Bernard Baars‘s global workspace theory.