BI 072 Mazviita Chirimuuta: Understanding, Prediction, and Reality
Podcast |
Brain Inspired
Publisher |
Paul Middlebrooks
Media Type |
audio
Categories Via RSS |
Education
Natural Sciences
Science
Technology
Publication Date |
Jun 01, 2020
Episode Duration |
01:18:53

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 processes.

Show notes:

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 processes. Show notes: Her website.Outside color website (with links to more of her publications)Her book Outside Color: Perceptual Science and the Puzzle of Color in Philosophy.Papers we discuss or mention:Prediction Versus Understanding in Computationally Enhanced Neuroscience.Your brain is like a computer: function, analogy, simplification.Charting the Heraclitean Brain: Perspectivism and Simplification in Models of the Motor Cortex.

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 processes.

Show notes:

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