Semanlink - Machine learning: problems ; Education AND Good

[1807.00082] Amanuensis: The Programmer's Apprentice

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**The use of natural language to facilitate communication
between the expert programmer and apprentice AI system.**

> 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.

> [#Dehaene](/tag/stanislas_dehaene)'s work extends the [#Global Workspace Theory](/tag/global_workspace_theory) of Bernard Baars. Dehaene’s version of the theory combined with Yoshua Bengio’s concept of a [#consciousness prior](/tag/consciousness_prior.html) and deep reinforcement learning suggest a model for constructing and maintaining the cognitive states that arise and persist during complex problem solving.

2019-11-12 About

Simple and efficient semantic embeddings for rare words, n-grams, and language features – Off the convex path

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2018-09-18 About

A Theoretical Approach to Semantic Coding and Hashing | Simons Institute for the Theory of Computing (2016)

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2018-05-26 About

A Simple but Tough-to-Beat Baseline for Sentence Embeddings (2017)

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2018-05-10 About

Semantic Word Embeddings – Off the convex path

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2017-11-21 About

An overview of word embeddings and their connection to distributional semantic models - AYLIEN (2016)

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2017-07-20 About