Evidence from machines that learn and think like people

Research output: Contribution to journalComment/debate

1 Scopus citations

Abstract

We agree with Lake et al.'s trenchant analysis of deep learning systems, including that they are highly brittle and that they need vastly more examples than do people. We also agree that human cognition relies heavily on structured relational representations. However, we differ in our analysis of human cognitive processing. We argue that (1) analogical comparison processes are central to human cognition; and (2) intuitive physical knowledge is captured by qualitative representations, rather than quantitative simulations.
Original languageEnglish (US)
Article numbere264
Pages (from-to)35-36
Number of pages2
JournalBehavioral and Brain Sciences
Volume40
DOIs
StatePublished - 2017

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Physiology
  • Behavioral Neuroscience

Fingerprint

Dive into the research topics of 'Evidence from machines that learn and think like people'. Together they form a unique fingerprint.

Cite this