Machine Intelligence @ NIPS

Recent years have seen the success of machine learning systems, in particular deep learning architectures, on specific challenges such as image classification and playing Go. Nevertheless, machines still fail on hallmarks of human intelligence such as the flexibility to quickly switch between a number of different tasks, the ability to creatively combine previously acquired skills in order to perform a more complex goal, the capacity to learn a new skill from just a few examples, or the use of communication and interaction to extend one's knowledge in order to accomplish new goals. This workshop aims to stimulate theoretical and practical advances in the development of machines endowed with human-like general-purpose intelligence, focusing in particular on benchmarks to train and evaluate progress in machine intelligence. The workshop will feature invited talks by top researchers from machine learning, AI, cognitive science and NLP, who will discuss with the audience their ideas about what are the most pressing issues we face in developing true AI and the best methods to measure genuine progress. We are moreover calling for position statements from interested researchers to complement the workshop program. The workshop will also introduce the new Environment for Communication-Based AI to the research community, encouraging discussion on how to make it the ultimate benchmark for machine intelligence. The Environment aims at being an interactive playground where systems can only succeed if they possess the hallmarks of intelligence we listed above. In September, we will make a prototype of the Environment available, so that researchers interested in submitting position statements to the workshop can experiment with it and take it into account in their proposals.