@inproceedings{d37257e9cba24ff8b98e2c9953d6819f,
title = "Toward human-level massively-parallel neural networks with Hodgkin-Huxley neurons",
abstract = "This paper describes neural network algorithms and software that scale up to massively parallel computers. The neuron model used is the best available at this time, the Hodgkin-Huxley equations. Most massively parallel simulations use very simplified neuron models, which cannot accurately simulate biological neurons and the wide variety of neuron types. Using C++ and MPI we can scale these networks to human-level sizes. Computers such as the Chinese TianHe computer are capable of human level neural networks.",
author = "Long, {Lyle N.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 9th International Conference on Artificial General Intelligence, AGI 2016 ; Conference date: 16-07-2016 Through 19-07-2016",
year = "2016",
doi = "10.1007/978-3-319-41649-6_32",
language = "English (US)",
isbn = "9783319416489",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "314--323",
editor = "Bas Steunebrink and Pei Wang and Ben Goertzel",
booktitle = "Artificial General Intelligence - 9th International Conference, AGI 2016, Proceedings",
address = "Germany",
}