Work

Hopfield and Hinton’s neural network revolution and the future of AI

Year: 2024

Type: article

Abstract: In this opinion piece, the authors, from the fields of artificial intelligence (AI) and psychology, reflect on how the foundational discoveries of Nobel laureates Hopfield and Hinton have influenced their research. They also discuss emerging directions in AI and the challenges that lie ahead for neural networks and machine learning.

Source: Patterns

DOI: 10.1016/j.patter.2024.101094

Authors: James Z. Wang, Brad Wyble

Institution: Pennsylvania State University

Language: English

Topic: Neural Networks and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $4,900

Funders: National Science Foundation, National Endowment for the Humanities, Burroughs Wellcome Fund, Amazon Web Services, National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering

Awards: Collaborative Research: Cellular and Biomechanical Mechanisms of Rapid Stomatal Dynamics in Grasses, G2987707748, Collaborative Research: Integrated Analysis of the Cell Biological, Biomechanical, and Physiological Dynamics of Stomatal Guard Cells in Plants, CompCog: HNDS-R: Self-Supervision of Visual Learning From Spatiotemporal Context, After Constable’s Clouds: Toward A Machine Learning Paradigm for Studying Pictorial Realism, Collaborative Research: CCRI: New: An Open Data Infrastructure for Bodily Expressed Emotion Understanding, CIF: Small: Interpretable Machine Learning based on Deep Neural Networks: A Source Coding Perspective

OpenAlex ID: W4404182814

FWCI: 1.032

Cites: 14

Cited by: 7

Related to: 10