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.

Citation

Dean, Thomas, et al. 2018. “Amanuensis: The Programmer’s Apprentice.” arXiv preprint arXiv:1807.00082.

@article{Dean2018,
author = {Thomas Dean and Maurice Chiang and Marcus Gomez and Nate Gruver and Yousef Hindy and Michelle Lam and Peter Lu and Sophia Sanchez and Rohun Saxena and Michael Smith and Lucy Wang and Catherine Wong},
year = {2018},
title = {Amanuensis: The Programmer's Apprentice},
journal = {arXiv preprint arXiv:1807.00082},
url = {https://arxiv.org/abs/1807.00082}}