Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.
https://braininspired.co/series/brain-inspired/
Gesamtlänge aller Episoden: 8 days 17 hours 30 minutes
BI 069 David Ferrucci: Machines To Understand Stories
David and I discuss the latest efforts he and his Elemental Cognition team have made to create machines that can understand stories the way humans can and do. The long term vision is to create what David calls thought partners, which are virtual assistan
BI 068 Rodrigo Quian Quiroga: NeuroScience Fiction
Rodrigo and I discuss concept cells and his latest book, NeuroScience Fiction. The book is a whirlwind of many of the big questions in neuroscience, each one framed by of one of Rodrigo’s favorite science fiction films and buttressed by tons of history,
BI 067 Paul Cisek: Backward Through The Brain
In this second part of my conversion with Paul (listen to the first part), we continue our discussion about how to understand brains as feedback control mechanisms - controlling our internal state and extending that control into the world - and how Paul
BI 066 Paul Cisek: Forward Through Evolution
In this first part of our conversation, Paul and I discuss his approach to understanding how the brain (and intelligence) works. Namely, he believes we are fundamentally action and movement oriented - all of our behavior and cognition is based on control
BI 065 Thomas Serre: How Recurrence Helps Vision
Thomas and I discuss the role of recurrence in visual cognition: how brains somehow excel with so few “layers” compared to deep nets, how feedback recurrence can underlie visual reasoning, how LSTM gate-like processing could explain the function of canon
BI 064 Galit Shmueli: Explanation vs. Prediction
Galit and I discuss the independent roles of prediction and explanation in scientific models, their history and eventual separation in the philosophy of science, how they can inform each other, and how statisticians like Galit view the current deep learn
BI 063 Uri Hasson: The Way Evolution Does It
Uri and I discuss his recent perspective that conceives of brains as super-over-parameterized models that try to fit everything as exactly as possible rather than trying to abstract the world into usable models. He was inspired by the way artificial neur
BI 062 Stefan Leijnen: Creativity and Constraint
Stefan and I discuss creativity and constraint in artificial and biological intelligence. We talk about his Asimov Institute and its goal of artificial creativity and constraint, different types and functions of creativity, the neuroscience of creativity
BI 061 Jörn Diedrichsen and Niko Kriegeskorte: Brain Representations
Jörn, Niko and I continue the discussion of mental representation from last episode with Michael Rescorla, then we discuss their review paper, Peeling The Onion of Brain Representations, about different ways to extract and understand what information is
BI 060 Michael Rescorla: Mind as Representation Machine
Michael and I discuss the philosophy and a bit of history of mental representation including the computational theory of mind and the language of thought hypothesis, how science and philosophy interact, how representation relates to computation in brains