Image from Google Jackets

How we learn : why brains learn better than any machine ... for now / Stanislas Dehaene. [print]

By: Material type: TextTextLanguage: English Original language: French Publication details: New York, New York : Viking, [(c)2020.Edition: First American editionDescription: xxviii, 319 pages, 16 unnumbered pages of plates : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0525559884
  • 9780525559887
  • 9780525559894
Uniform titles:
  • Apprendre! English
Subject(s): LOC classification:
  • BF318.H699 2020
  • BF318.D322.H699 2020
Available additional physical forms:
  • COPYRIGHT NOT covered - Click this link to request copyright permission:
Contents:
Seven definitions of learning Why our brain learns better than current machines Babies' invisible knowledge The birth of a brain Nurture's share Recycle your brain Attention Active engagement Error feedback Consolidation Conclusion. Reconciling education with neuroscience.
Summary: "In today's technological society, with an unprecedented amount of information at our fingertips, learning plays a more central role than ever. In How We Learn, Stanislas Dehaene decodes its biological mechanisms, delving into the neuronal, synaptic, and molecular processes taking place in the brain. He explains why youth is such a sensitive period, during which brain plasticity is maximal, but also assures us that our abilities continue into adulthood, and that we can enhance our learning and memory at any age. We can all 'learn to learn' by taking maximal advantage of the four pillars of the brain's learning algorithm: attention, active engagement, error feedback, and consolidation. The human brain is an extraordinary machine. Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. The exciting advancements in A.I. of the last twenty years reveal just as much about our remarkable abilities as they do about the potential of machines. How We Learn finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain's learning algorithms, in our schools and universities as well as in everyday life"--
Item type: Circulating Book (checkout times vary with patron status)
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Status Date due Barcode
Circulating Book (checkout times vary with patron status) G. Allen Fleece Library Circulating Collection - First Floor Non-fiction BF318.D322.H699 2020 (Browse shelf(Opens below)) Available 31923001904784

Based in part on: Apprendre! : les talents du cerveau, le defi des machines.

Seven definitions of learning Why our brain learns better than current machines Babies' invisible knowledge The birth of a brain Nurture's share Recycle your brain Attention Active engagement Error feedback Consolidation Conclusion. Reconciling education with neuroscience.

"In today's technological society, with an unprecedented amount of information at our fingertips, learning plays a more central role than ever. In How We Learn, Stanislas Dehaene decodes its biological mechanisms, delving into the neuronal, synaptic, and molecular processes taking place in the brain. He explains why youth is such a sensitive period, during which brain plasticity is maximal, but also assures us that our abilities continue into adulthood, and that we can enhance our learning and memory at any age. We can all 'learn to learn' by taking maximal advantage of the four pillars of the brain's learning algorithm: attention, active engagement, error feedback, and consolidation. The human brain is an extraordinary machine. Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. The exciting advancements in A.I. of the last twenty years reveal just as much about our remarkable abilities as they do about the potential of machines. How We Learn finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain's learning algorithms, in our schools and universities as well as in everyday life"--

COPYRIGHT NOT covered - Click this link to request copyright permission:

There are no comments on this title.

to post a comment.

Powered by Koha