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/
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 and machines, levels of computational explanation, and we discuss some examples of representational approaches to mental processes like bayesian modeling.
Show notes:
- Michael's website (with links to a ton of his publications).
- Science and Philosophy
- Why science needs philosophy by Laplane et al 2019.
- Why Cognitive Science Needs Philosophy and Vice Versa by Paul Thagard, 2009.
- Some of Michael's papers/articles we discuss or mention:
- The Computational Theory of Mind.
- Levels of Computational Explanation.
- Computational Modeling of the Mind: What Role for Mental Representation?
- From Ockham to Turing --- and Back Again.
- Talks:
- Predictive coding “debate” with Michael and a few other folks.
- An overview and history of the philosophy of representation.
- Books we mentioned:
- The Structure of Scientific Revolutions by Thomas Kuhn.
- Memory and the Computational Brain by Randy Gallistel and Adam King.
- Representation In Cognitive Science by Nicholas Shea.
- Types and Tokens: On Abstract Objects by Linda Wetzel.
- Probabilistic Robotics by Thrun, Burgard, and Fox.