Systems Neuroscience Approach to General Intelligence

Abstract

AI technology and neuroscience have progressed such that it’s again prudent to look to the brain as a model for AI. Examining current artificial neural networks, theoretical computer science, and systems neuroscience, this workshop will uncover gaps in knowledge about the brain and models of intelligence. Bernard Baars modeled the brain’s cognitive processes as a Global Workspace. This was elaborated in network neuroscience as the Global Neuronal Workspace, and in theoretical computer science as the Conscious Turing Machine (CTM) [1]. The CTM is a substrate independent model for consciousness. AI researchers have proposed variations and extensions of the Global Workspace, connecting the CTM to Transformers [2] and using them to communicate among specialist modules [3]. Meanwhile, neuroscience has identified large-scale brain circuits brain that bear striking resemblance to patterns found in contemporary AI architectures such as Transformers. This workshop will aim to map the Global Workspace and CTM to AI systems using the brain’s architecture as a guide. We hypothesize that this approach can achieve general intelligence and that high resolution recordings from the brain can be used to validate its models. The goal of this workshop is to bring together a multi-disciplinary group comprising AI researchers, systems neuroscientists, algorithmic information theorists, and physicists to understand gaps in this larger agenda and to determine what’s known about what’s needed to build thinking machines.