Amanuensis: The Programmer's Apprentice

This document provides an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems that leverage and extend the state of the ar...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2018-11
Hauptverfasser: Dean, Thomas, Chiang, Maurice, Gomez, Marcus, Gruver, Nate, Yousef Hindy, Lam, Michelle, Lu, Peter, Sanchez, Sophia, Saxena, Rohun, Smith, Michael, Wang, Lucy, Wong, Catherine
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Dean, Thomas
Chiang, Maurice
Gomez, Marcus
Gruver, Nate
Yousef Hindy
Lam, Michelle
Lu, Peter
Sanchez, Sophia
Saxena, Rohun
Smith, Michael
Wang, Lucy
Wong, Catherine
description This document provides an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems that leverage and extend the state of the art in machine learning by integrating human and machine intelligence. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants. Over time these savants learn cognitive strategies (domain-relevant problem solving skills) and develop intuitions (heuristics and the experience necessary for applying them) by learning from their expert associates. By doing so these savants elevate their innate analytical skills allowing them to partner on an equal footing as versatile collaborators - effectively serving as cognitive extensions and digital prostheses, thereby amplifying and emulating their human partner's conceptually-flexible thinking patterns and enabling improved access to and control over powerful computing resources.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2073484984</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2073484984</sourcerecordid><originalsourceid>FETCH-proquest_journals_20734849843</originalsourceid><addsrcrecordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mRQd8xNzCtNzSvOLLZSCMlIVQgoyk8vSszNTS1SL1ZwLCgoSs0ryUxO5WFgTUvMKU7lhdLcDMpuriHOHroFRfmFpanFJfFZ-aVFeUCpeCMDc2MTCxNLCxNj4lQBAFqVL54</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2073484984</pqid></control><display><type>article</type><title>Amanuensis: The Programmer's Apprentice</title><source>Free E- Journals</source><creator>Dean, Thomas ; Chiang, Maurice ; Gomez, Marcus ; Gruver, Nate ; Yousef Hindy ; Lam, Michelle ; Lu, Peter ; Sanchez, Sophia ; Saxena, Rohun ; Smith, Michael ; Wang, Lucy ; Wong, Catherine</creator><creatorcontrib>Dean, Thomas ; Chiang, Maurice ; Gomez, Marcus ; Gruver, Nate ; Yousef Hindy ; Lam, Michelle ; Lu, Peter ; Sanchez, Sophia ; Saxena, Rohun ; Smith, Michael ; Wang, Lucy ; Wong, Catherine</creatorcontrib><description>This document provides an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems that leverage and extend the state of the art in machine learning by integrating human and machine intelligence. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants. Over time these savants learn cognitive strategies (domain-relevant problem solving skills) and develop intuitions (heuristics and the experience necessary for applying them) by learning from their expert associates. By doing so these savants elevate their innate analytical skills allowing them to partner on an equal footing as versatile collaborators - effectively serving as cognitive extensions and digital prostheses, thereby amplifying and emulating their human partner's conceptually-flexible thinking patterns and enabling improved access to and control over powerful computing resources.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Access control ; Hybrid systems ; Machine learning ; Problem solving ; Prostheses ; Skills</subject><ispartof>arXiv.org, 2018-11</ispartof><rights>2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780</link.rule.ids></links><search><creatorcontrib>Dean, Thomas</creatorcontrib><creatorcontrib>Chiang, Maurice</creatorcontrib><creatorcontrib>Gomez, Marcus</creatorcontrib><creatorcontrib>Gruver, Nate</creatorcontrib><creatorcontrib>Yousef Hindy</creatorcontrib><creatorcontrib>Lam, Michelle</creatorcontrib><creatorcontrib>Lu, Peter</creatorcontrib><creatorcontrib>Sanchez, Sophia</creatorcontrib><creatorcontrib>Saxena, Rohun</creatorcontrib><creatorcontrib>Smith, Michael</creatorcontrib><creatorcontrib>Wang, Lucy</creatorcontrib><creatorcontrib>Wong, Catherine</creatorcontrib><title>Amanuensis: The Programmer's Apprentice</title><title>arXiv.org</title><description>This document provides an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems that leverage and extend the state of the art in machine learning by integrating human and machine intelligence. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants. Over time these savants learn cognitive strategies (domain-relevant problem solving skills) and develop intuitions (heuristics and the experience necessary for applying them) by learning from their expert associates. By doing so these savants elevate their innate analytical skills allowing them to partner on an equal footing as versatile collaborators - effectively serving as cognitive extensions and digital prostheses, thereby amplifying and emulating their human partner's conceptually-flexible thinking patterns and enabling improved access to and control over powerful computing resources.</description><subject>Access control</subject><subject>Hybrid systems</subject><subject>Machine learning</subject><subject>Problem solving</subject><subject>Prostheses</subject><subject>Skills</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mRQd8xNzCtNzSvOLLZSCMlIVQgoyk8vSszNTS1SL1ZwLCgoSs0ryUxO5WFgTUvMKU7lhdLcDMpuriHOHroFRfmFpanFJfFZ-aVFeUCpeCMDc2MTCxNLCxNj4lQBAFqVL54</recordid><startdate>20181108</startdate><enddate>20181108</enddate><creator>Dean, Thomas</creator><creator>Chiang, Maurice</creator><creator>Gomez, Marcus</creator><creator>Gruver, Nate</creator><creator>Yousef Hindy</creator><creator>Lam, Michelle</creator><creator>Lu, Peter</creator><creator>Sanchez, Sophia</creator><creator>Saxena, Rohun</creator><creator>Smith, Michael</creator><creator>Wang, Lucy</creator><creator>Wong, Catherine</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20181108</creationdate><title>Amanuensis: The Programmer's Apprentice</title><author>Dean, Thomas ; Chiang, Maurice ; Gomez, Marcus ; Gruver, Nate ; Yousef Hindy ; Lam, Michelle ; Lu, Peter ; Sanchez, Sophia ; Saxena, Rohun ; Smith, Michael ; Wang, Lucy ; Wong, Catherine</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_20734849843</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Access control</topic><topic>Hybrid systems</topic><topic>Machine learning</topic><topic>Problem solving</topic><topic>Prostheses</topic><topic>Skills</topic><toplevel>online_resources</toplevel><creatorcontrib>Dean, Thomas</creatorcontrib><creatorcontrib>Chiang, Maurice</creatorcontrib><creatorcontrib>Gomez, Marcus</creatorcontrib><creatorcontrib>Gruver, Nate</creatorcontrib><creatorcontrib>Yousef Hindy</creatorcontrib><creatorcontrib>Lam, Michelle</creatorcontrib><creatorcontrib>Lu, Peter</creatorcontrib><creatorcontrib>Sanchez, Sophia</creatorcontrib><creatorcontrib>Saxena, Rohun</creatorcontrib><creatorcontrib>Smith, Michael</creatorcontrib><creatorcontrib>Wang, Lucy</creatorcontrib><creatorcontrib>Wong, Catherine</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dean, Thomas</au><au>Chiang, Maurice</au><au>Gomez, Marcus</au><au>Gruver, Nate</au><au>Yousef Hindy</au><au>Lam, Michelle</au><au>Lu, Peter</au><au>Sanchez, Sophia</au><au>Saxena, Rohun</au><au>Smith, Michael</au><au>Wang, Lucy</au><au>Wong, Catherine</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Amanuensis: The Programmer's Apprentice</atitle><jtitle>arXiv.org</jtitle><date>2018-11-08</date><risdate>2018</risdate><eissn>2331-8422</eissn><abstract>This document provides an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems that leverage and extend the state of the art in machine learning by integrating human and machine intelligence. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants. Over time these savants learn cognitive strategies (domain-relevant problem solving skills) and develop intuitions (heuristics and the experience necessary for applying them) by learning from their expert associates. By doing so these savants elevate their innate analytical skills allowing them to partner on an equal footing as versatile collaborators - effectively serving as cognitive extensions and digital prostheses, thereby amplifying and emulating their human partner's conceptually-flexible thinking patterns and enabling improved access to and control over powerful computing resources.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2018-11
issn 2331-8422
language eng
recordid cdi_proquest_journals_2073484984
source Free E- Journals
subjects Access control
Hybrid systems
Machine learning
Problem solving
Prostheses
Skills
title Amanuensis: The Programmer's Apprentice
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T12%3A36%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Amanuensis:%20The%20Programmer's%20Apprentice&rft.jtitle=arXiv.org&rft.au=Dean,%20Thomas&rft.date=2018-11-08&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2073484984%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2073484984&rft_id=info:pmid/&rfr_iscdi=true