Yann LeCun, the inventor of the convolutional networks has given a talk at CMU robotics institute which was conveniently recorded and made available to the general public here:
http://www.ri.cmu.edu/video_view.html?video_id=176&menu_id=387
Although the talk is over 1h long, it is certainly worth watching and I strongly recommend doing that before you read any of the following text.
After the lecture
Yann LeCun is a rather colourful character and certainly has strong opinions on many subjects. I find myself at any given time either strongly agreeing or strongly disagreeing with him and it's no surprise it is the same this time around. Anyway, he makes several points in his talk which I think are relevant to our published work on PVM (PVM paper for details) and worth more detailed comment.
- After a brief overview of the state of the art in machine learning and AI, LeCun goes on to talk about more cutting edge stuff. He notes that the next important frontier for AI is learning "Forward Models" via prediction, learning "folk's physics" so to speak (a.k.a, common sense). He presents the observation that reinforcement learning has a very weak learning signal in the case of sparse rewards,