From Deep Learning to Deep University: Cognitive Development of Intelligent Systems

Authors: Mariia Golovianko, Svitlana Gryshko, Vagan Terziyan
Year: 2017
Venue: Semantic Keyword-Based Search on Structured Data Sources. KEYSTONE 2017, Springer, 6 pp. (to appear)
Link: http://www.cs.jyu.fi/ai/IKC-2017.pptx
Product of the Action: Yes

Keystone Members Authors:
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Abstract:
Search is not only an instrument to find intended information. Ability to search is a basic cognitive skill helping people to explore the world. It is largely based on personal intuition and creativity. However, due to the emerged big data challenge, people require new forms of training to develop or improve this ability. Current developments within Cognitive Computing and Deep Learning enable artificial systems to learn and gain human-like cognitive abilities. This means that the skill how to search efficiently and creatively within huge data spaces becomes one of the most important ones for the cognitive systems aiming at autonomy. This skill cannot be pre-programmed, it requires learning. We offer to use the collective search expertise to train creative association-driven navigation across heterogeneous information spaces. We argue that artificial cognitive systems, as well as humans, need special environments, like universities, to train skills of autonomy and creativity.