In his latest paper, Yoshua Bengio—one of the world’s leading AI professors at the Université de Montréal—established a link between deep learning and the concept of consciousness (https://arxiv.org/pdf/1709.08568.pdf).

The idea of a “Consciousness Prior” is inspired by the phenomenon of consciousness defined as the formation of a low-dimensional combination of—a few—concepts constituting a conscious thought, i.e., consciousness manifests itsel as awareness at a particular time or instant.”

The notion is that the interim results generated by a Recurrent Neural Network (RNN) can be used to explain the past and to plan the future. The system does not act on the basis of input signals, such as images or texts, but rather controls the “consciousness” established by the information abstracted from input signals.

Consciousness Prior could be used to translate information contained within trained neural networks back into natural language or into classical AI procedures with rules and facts. An implementation of this concept is not presented in the document, but Bengio proposes to integrate the approach into reinforcement learning systems.

Bengio’s ideas may very well lead the way to new frontiers in artificial intelligence.  Time will tell whether his proposal is a revolutionary idea or just a “visionary” mind game.