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The Resource How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource)
How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource)
Resource Information
The item How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in San Francisco Public Library.This item is available to borrow from all library branches.
Resource Information
The item How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in San Francisco Public Library.
This item is available to borrow from all library branches.
- 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"--
- Language
-
- eng
- fre
- eng
- Extent
- 1 online resource
- Note
- Translation of: Apprendre! : les talents du cerveau, le défi des machines
- 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
- Isbn
- 9780525559894
- Label
- How we learn : why brains learn better than any machine ... for now
- Title
- How we learn
- Title remainder
- why brains learn better than any machine ... for now
- Statement of responsibility
- Stanislas Dehaene
- Language
-
- eng
- fre
- eng
- 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"--
- Assigning source
- Provided by publisher
- Cataloging source
- LBSOR/DLC
- http://library.link/vocab/creatorName
- Dehaene, Stanislas
- Dewey number
- 153.1/5
- Illustrations
-
- illustrations
- plates
- Index
- index present
- Language note
- Translated from the French
- LC call number
- BF318
- LC item number
- .D44 2020
- Literary form
- non fiction
- Nature of contents
- bibliography
- http://library.link/vocab/subjectName
-
- Learning, Psychology of
- Cognitive psychology
- Neuroplasticity
- Cognitive science
- Label
- How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource)
- Note
- Translation of: Apprendre! : les talents du cerveau, le défi des machines
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- online resource
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- 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
- Extent
- 1 online resource
- Form of item
- online
- Isbn
- 9780525559894
- Lccn
- 2019036725
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- n
- http://library.link/vocab/ext/overdrive/overdriveId
- 0026507399
- Specific material designation
- remote
- Label
- How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource)
- Note
- Translation of: Apprendre! : les talents du cerveau, le défi des machines
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- online resource
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- 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
- Extent
- 1 online resource
- Form of item
- online
- Isbn
- 9780525559894
- Lccn
- 2019036725
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- n
- http://library.link/vocab/ext/overdrive/overdriveId
- 0026507399
- Specific material designation
- remote
Subject
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.sfpl.org/portal/How-we-learn--why-brains-learn-better-than-any/bhJl5XyepF0/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.sfpl.org/portal/How-we-learn--why-brains-learn-better-than-any/bhJl5XyepF0/">How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.sfpl.org/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.sfpl.org/">San Francisco Public Library</a></span></span></span></span></div>
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.sfpl.org/portal/How-we-learn--why-brains-learn-better-than-any/bhJl5XyepF0/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.sfpl.org/portal/How-we-learn--why-brains-learn-better-than-any/bhJl5XyepF0/">How we learn : why brains learn better than any machine ... for now, Stanislas Dehaene, (electronic resource)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.sfpl.org/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.sfpl.org/">San Francisco Public Library</a></span></span></span></span></div>
