Hwang, T. (2018). Computational power and the social impact of artificial intelligence. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3147971
Author
Abstract

Machine learning is computational process. To that end, it is inextricably tied to computational power - the tangible material of chips and semiconductors that the algorithms of machine intelligence operate on. Most obviously, computational power and computing architectures shape the speed of training and inference in machine learning, and therefore influence the rate of progress in the technology. But, these relationships are more nuanced than that: hardware shapes the methods used by researchers and engineers in the design and development of machine learning models.

Year of Publication
2018
Journal
SSRN Electronic Journal
DOI
10.2139/ssrn.3147971