Content
Frontiers of Information Technology & Electronic Engineering >> 2022, Volume 23, Issue 9 doi: 10.1631/FITEE.2200297
On the principles of Parsimony and Self-consistency for the emergence of intelligence
Affiliation(s): Electrical Engineering and Computer Science Department, University of California, Berkeley, CA 94720, USA; Department of Molecular & Cell Biology and Howard Hughes Medical Institute, University of California, Berkeley, CA 94720, USA; International Digital Economy Academy, Shenzhen 518045, China; less
Abstract
Keywords
Intelligence ; Parsimony ; Self-consistency ; Rate reduction ; Deep networks ; Closed-loop transcription
Content