Rapid developments in the field of automated learning have caused a major shift in the approach to the learning of intelligent systems, from explicit instruction to the automatic learning from a large number of labeled examples. Deep neural network models are integrated in the core of new AI technologies such as the autonomous car. Yet, there are still fundamental differences between current AI technologies and human intelligence. In this talk I will present some examples of these differences, including computational models that demonstrate how an AI system can learn complex visual concepts (such as hand recognition, gaze estimation and spatial relations) rapidly and without explicit supervision like humans, and in particular infants, do.
Danny Harari, Weizmann Institute of Science.