IEEE Members: Free
Non-members: FreeDuration: 00:43:34
Ryota Kanai (Araya, Inc), Abstract: I will present our current research exploring potential connections between consciousness and intelligence. In this paper we examined how to combine theories of consciousness with modern deep learning techniques to translate high-level concepts from consciousness research into more concrete computational concepts. Among the theories we considered were Global Workspace Theory (GWT), Information Generation Theory (ITG), and Attention Schema Theory (AST). From this effort, one of the key conclusions is that consciousness has evolved into a platform for general-purpose intelligence. In this talk, I will present a reinterpretation of the GWT as a shared latent space among multimodal specialist modules and outline a roadmap for implementing a Global Latent Workspace (VanRullen & Kanai, 2021) using deep learning techniques, such as an unsupervised translation of representations across latent spaces. With our re-formulation of GWT, we will discuss the functional merits of having a global workspace as well as its implications for neuroscientific research into the brain and the development of brain-to-brain communication technologies.