Nando is a principal scientist at Deepmind and has an appointment at CIFAR, the Canadian Institute for Advanced Research. We talk about why he studies artificial intelligence, many of his current projects advancing machine learning in modern challenging areas like meta-learning, teaching machines how to program other machines, training networks using few training examples, and more.
Anne and I discuss her work elucidating how populations of neurons underly decision-making in mouse brains. We talk about how movement related activity dominates neural activity during decisions, how lapses may reflect exploration of options, a rubric for characterizing animal experiments, her Anne’s List repository to help all of us invite female systems neuroscientists to speak at conferences, and a lot more
Máté and I discuss his work on probabilistic internal models to understand perception and learning and their inherent uncertainty in our brains, bayesian theory, how his models relate to modern deep learning, and lots more.
Nathaniel and I discuss his work on model-based and model-free reinforcement learning, how replay in the hippocampus can help of conjure appropriate memories to plan actions, neuropsychiatric disorders, and more.
Roshan and I discuss her work on the role of dopamine on our meta-control of cognition (cognitive control) in the basal ganglia and prefrontal cortex, the role of dopamine in reinforcement learning, how artificial intelligence might incorporate principles of neuromodulation to improve algorithms, being a woman in science, and much more.
