Neuroscience for Artificial Intelligence

by Huijue Jia

Overview

The ongoing boom of applications for artificial intelligence (AI) is based on algorithms that were inspired by neuroscience discoveries in the 1960s. This is a timely book to introduce the new discoveries and ideas in neuroscience, for the next wave of more powerful AI. AI researchers are all interested in the human brain, which is more capable and energy-efficient, but do not have good reading materials from the rather separate subfields of neuroscience, all with plenty of jargons. Based on hundreds of publications from top journals, the book fills in the gap between existing computational hardware/algorithms and emerging knowledge from neuroscience.

Product Details

ISBN-13:	9781000908855
Publisher:	Jenny Stanford Publishing
Publication date:	05/31/2023
Sold by:	Barnes & Noble
Format:	eBook
Pages:	252
File size:	40 MB
Note:	This product may take a few minutes to download.

About the Author

Huijue Jia received her BS at Fudan University, China, and PhD at Case Western Reserve University, USA, with Dr. Eckhard Jankowsky. After being a postdoc with Dr. Yi Zhang (now at Boston Children’s Hospital and Harvard Medical School), she has served as scientific editor of Nature Communications and has contributed to reviews, commentaries, and other book projects, especially a recent book on the human microbiome. Dr. Jia is currently a principal investigator at Fudan University and Greater Bay Area Institute of Precision Medicine, China. With many publications on bioinformatic analyses of omics data, including metagenomic studies on neuropsychiatric diseases, she is uniquely positioned to bridge the myriad of neuroscience publications and the booming field of artificial intelligence, for the next wave of more powerful algorithms.

Table of Contents

1. Evolving under Constraints 2. The Senses as Basic Input 3. Changing Priorities with Age 4. Memory in Cells 5. Memory in Dendritic Spines 6. Sleeping and Dreaming 7. Mastering Space and Time 8. Arithmetics, Talking, and Reading 9. Causality and Cognitive Exploration