About This Document
- sl:arxiv_author :
- sl:arxiv_firstAuthor : Thomas Dean
- sl:arxiv_num : 1807.00082
- sl:arxiv_published : 2018-06-29T22:59:08Z
- sl:arxiv_summary : 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.@en
- sl:arxiv_title : Amanuensis: The Programmer's Apprentice@en
- sl:arxiv_updated : 2018-11-08T13:33:18Z
- sl:bookmarkOf : https://arxiv.org/abs/1807.00082
- sl:creationDate : 2019-11-12
- sl:creationTime : 2019-11-12T16:25:10Z
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