Cross Domain Generalisation in Humans and Machines
Schedule
Thursday, February 4, 2021
16:00 UTC
Leonidas Alex Doumas
Dr
The University of Edinburgh
Host: Analogical Minds
Recording
Open recording
Event Information
Recording
Available
Host
Analogical Minds
Duration
60 minutes
Abstract
Recent advances in deep learning have produced models that far outstrip human performance in a number of domains. However, where machine learning approaches still fall far short of human-level performance is in the capacity to transfer knowledge across domains. While a human learner will happily apply knowledge acquired in one domain (e.g., mathematics) to a different domain (e.g., cooking; a vinaigrette is really just a ratio between edible fat and acid), machine learning models still struggle profoundly at such tasks. I will present a case that human intelligence might be (at least partially) usefully characterised by our ability to transfer knowledge widely, and a framework that we have developed for learning representations that support such transfer. The model is compared to current machine learning approaches.
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