Paper
The missing G
Published Jan 18, 2020 · Erez Firt
AI & SOCIETY
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Abstract
Artificial general intelligence (AGI) is not a new notion, but it has certainly been gaining traction in recent years, and academic as well as industry resources are redirected to research in AGI. The main reason for this is that current AI techniques are limited as they are designed to operate in specific problem-domains, following meticulous preparation. These systems cannot operate in an unknown environment or under conditions of uncertainty, reuse knowledge gained in another problem domain, or autonomously learn and understand the problem-domain. We shall call AI systems capable of such feats artificial general intelligent (AGI) systems. The three tasks of this paper are to provide a working definition of the term AGI, examine the “missing G”, i.e., the set of abilities that current AI systems lack and whose implementation will result in a basic AGI system, and consider different approaches, including a hybrid one, to a comprehensive solution for an AGI.
This paper provides a working definition of artificial general intelligence (AGI), examines the "missing G" abilities needed for a comprehensive AGI system, and considers various approaches, including hybrid ones, to achieve a comprehensive solution.
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