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PODCAST

Brain Inspired

Paul Middlebrooks

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

science natural sciences

All Episodes

01:35:43

BI 086 Ken Stanley: Open-Endedness

Brain Inspired ·

2020/10/12

Ken and I discuss open-endedness, the pursuit of ambitious goals by seeking novelty and interesting products instead of advancing directly toward defined objectives. We talk about evolution as a prime example of an open-ended system that has produced astounding organisms, Ken relates how open-endedness could help advance artificial intelligence and neuroscience, and we discuss a range of topics related to the general concept of open-endedness, and Ken takes a couple questions from Stefan Leijnen and

en-US

01:43:41

BI 085 Ida Momennejad: Learning Representations

Brain Inspired ·

2020/09/30

Ida and I discuss the current landscape of reinforcement learning in both natural and artificial intelligence, and how the old story of two RL systems in brains - model-free and model-based - is giving way to a more nuanced story of these two systems constantly interacting and additional RL strategies between model-free and model-based to drive the vast repertoire of our habits and goal-directed behaviors. We discuss Ida’s work on one of those “in-between” strategies, the successor representation RL

en-US

01:56:01

BI 084 György Buzsáki and David Poeppel

Brain Inspired ·

2020/09/15

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

en-US

01:13:16

BI 083 Jane Wang: Evolving Altruism in AI

Brain Inspired ·

2020/09/05

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

en-US

02:15:38

BI 082 Steve Grossberg: Adaptive Resonance Theory

Brain Inspired ·

2020/08/26

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,

en-US

01:22:05

BI 081 Pieter Roelfsema: Brain-propagation

Brain Inspired ·

2020/08/16

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

en-US

01:31:09

BI 080 Daeyeol Lee: Birth of Intelligence

Brain Inspired ·

2020/08/06

Daeyeol and I discuss his bookBirth 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),

en-US

01:19:04

BI 079 Romain Brette: The Coding Brain Metaphor

Brain Inspired ·

2020/07/27

Romain and I discuss his theoretical/philosophical work examining how neuroscientists rampantly misuse the word "code" when making claims about information processing in brains. We talk about the coding metaphor, various notions of information, the different roles and facets of mental representation, perceptual invariance, subjective physics, process versus substance metaphysics, and the experience of writing a Behavior and Brain Sciences article (spoiler: it's a demanding yet rewarding

en-US

01:14:37

BI 078 David and John Krakauer: Part 2

Brain Inspired ·

2020/07/17

In this second part of our conversation David, John, and I continue to discuss the role of complexity science in the study of intelligence, brains, and minds. We also get into functionalism and multiple realizability, dynamical systems explanations, the role of time in thinking, and more. Be sure to listen to the first part, which lays the foundation for what we discuss in this episode. Notes: David’s page at the Santa Fe Institute.John’s BLAM lab website.Follow SFI on twitter:

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01:33:04

BI 077 David and John Krakauer: Part 1

Brain Inspired ·

2020/07/14

David, John, and I discuss the role of complexity science in the study of intelligence. In this first part, we talk about complexity itself, its role in neuroscience, emergence and levels of explanation, understanding, epistemology and ontology, and really quite a bit more. Notes: David’s page at the Santa Fe Institute.John’s BLAM lab website.Follow SFI on twitter: @sfiscience.BLAM on Twitter: @blamlabRelated Krakauer stuff:At the limits of thought. An Aeon article by DavidComplex Time:

en-US

01:16:03

BI 075 Jim DiCarlo: Reverse Engineering Vision

Brain Inspired ·

2020/06/24

Jim and I discuss his reverse engineering approach to visual intelligence, using deep models optimized to perform object recognition tasks. We talk about the history of his work developing models to match the neural activity in the ventral visual stream, how deep learning connects with those models, and some of his recent work: adding recurrence to the models to account for more difficult object recognition, using unsupervised learning to account for plasticity in the visual stream, and controlling

en-US

01:22:35

BI 074 Ginger Campbell: Are You Sure?

Brain Inspired ·

2020/06/16

Ginger and I discuss her book Are You Sure? The Unconscious Origins of Certainty, which summarizes Richard Burton's work exploring the experience and phenomenal origin of feeling confident, and how the vast majority of our brain processing occurs outside our conscious awareness. Are You Sure? The Unconscious Origins of Certainty.Brain Science Podcast.

en-US

01:25:10

BI 073 Megan Peters: Consciousness and Metacognition

Brain Inspired ·

2020/06/10

Megan and I discuss her work using metacognition as a way to study subjective awareness, or confidence. We talk about using computational and neural network models to probe how decisions are related to our confidence, the current state of the science of consciousness, and her newest project using fMRI decoded neurofeedback to induce particular brain states in subjects so we can learn about conscious and unconscious brain processing. Notes: Visit Megan's cognitive & neural computation

en-US

01:18:53

BI 072 Mazviita Chirimuuta: Understanding,...

Brain Inspired ·

2020/06/01

Mazviita and I discuss the growing divide between prediction and understanding as neuroscience models and deep learning networks become bigger and more complex. She describes her non-factive account of understanding, which among other things suggests that the best predictive models may deliver less understanding. We also discuss the brain as a computer metaphor, and whether it's really possible to ignore all the traditionally "non-computational" parts of the brain like metabolism and other life

en-US

01:10:57

BI 071 J. Patrick Mayo: The Path To Faculty

Brain Inspired ·

2020/05/25

Patrick and I mostly discuss his path from a technician in the then nascent Jim DiCarlo lab, through his graduate school and two postdoc experiences, and finally landing a faculty position, plus the culture and issues in academia in general. We also cover plenty of science, like the role of eye movements in the study of vision, the neuroscience (and concept) of attention, what Patrick thinks of the deep learning hype, and more. But, this is a special episode, less about the science and more

en-US

01:47:07

BI 070 Bradley Love: How We Learn Concepts

Brain Inspired ·

2020/05/15

Brad and I discuss his battle-tested, age-defying cognitive model for how we learn and store concepts by forming and rearranging clusters, how the model maps onto brain areas, and how he's using deep learning models to explore how attention and sensory information interact with concept formation. We also discuss the cognitive modeling approach, Marr's levels of analysis, the term "biological plausibility", emergence and reduction, and plenty more. Notes: Visit Brad’s website.Follow Brad on

en-US

01:26:35

BI 069 David Ferrucci: Machines To Understand Stories

Brain Inspired ·

2020/05/05

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 assistants that can learn and synthesize a massive amount of information for us when we need that information for whatever project we're working on. We also discuss the nature of understanding, language, the role of the biological sciences for AI, and

en-US

01:34:44

BI 068 Rodrigo Quian Quiroga: NeuroScience Fiction

Brain Inspired ·

2020/04/24

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, literature, and philosophy. We discuss a few of the topics in the book, like AI, identity, free will, consciousness, and immortality, and we keep returning to concept cells and the role of abstraction in human cognition. Notes: Rodrigo's lab

en-US

00:49:00

BI 067 Paul Cisek: Backward Through The Brain

Brain Inspired ·

2020/04/18

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 thinks the key to understanding intelligence is to trace our evolutionary past through phylogenetic refinement. Paul's lab website.(A few of) his papers we discuss or mention:Resynthesizing behavior through phylogenetic refinement.Navigating

en-US

246 results

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