David, Gyuri, and I discuss the issues they argue for in their back and forth commentaries about the importance of neuroscience and psychology, or implementation-level and computational-level, to advance our understanding of brains and minds – and the names we give to the things we study. Gyuri believes it’s time we use what we know and discover about brain mechanisms to better describe the psychological concepts we refer to as explanations for minds; David believes the psychological concepts are constantly being refined and are just as valid as objects of study to understand minds. They both agree these are important and enjoyable topics to debate.
Jane and I discuss the relationship between AI and neuroscience (cognitive science, etc), from her perspective at Deepmind after a career researching natural intelligence. We also talk about her meta-reinforcement learning work that connects deep reinforcement learning with known brain circuitry and processes, and finally we talk about her recent work using evolutionary strategies to develop altruism and cooperation among the agents in a multi-agent reinforcement learning environment.
Steve and I discuss his long and productive career as a theoretical neuroscientist. We cover his tried and true method of taking a large body of psychological behavioral findings, determining how they fit together and what’s paradoxical about them, developing design principles, theories, and models from that body of data, and using experimental neuroscience to inform and confirm his model predictions. We talk about his Adaptive Resonance Theory (ART) to describe how our brains are self-organizing, adaptive, and deal with changing environments. We also talk about his complementary computing paradigm, how the resonant states in ART support consciousness, his place in the history of both neuroscience and AI, and quite a bit more.
Pieter and I discuss his ongoing quest to figure out how the brain implements learning that solves the credit assignment problem, like backpropagation does for neural networks. We also talk about his work to understand how we perceive individual objects in a crowded scene, his neurophysiological recordings in support of the global neuronal workspace hypothesis of consciousness, and the visual prosthetic device he’s developing to cure blindness by directly stimulating early visual cortex.
Daeyeol and I discuss his book Birth of Intelligence: From RNA to Artificial Intelligence, which argues intelligence is a function of and inseparable from life, bound by self-replication and evolution. The book covers a ton of neuroscience related to decision making and learning, though we focused on a few theoretical frameworks and ideas like division of labor and principal-agent relationships to understand how our brains and minds are related to our genes, how AI is related to humans (for now), metacognition, consciousness, and a ton more.
