Artificial General Intelligence

Artificial general intelligence (AGI) is a contested concept in AI research rather than a specific product or company. The term was coined in the early 2000s to revive the original ambition of building machines with "general purpose" intelligence across domains, as opposed to narrow, task-specific systems . Leading labs have offered divergent framings: DeepMind co-founder Demis Hassabis defined AGI as "a system that should be able to complete almost all cognitive tasks that humans can perform," while OpenAI describes it as "highly autonomous systems that outperform humans at most economically valuable work" — with both definitions implicitly excluding physical tasks . The concept remains deeply debated; some researchers, such as Melanie Mitchell in a 2024 Science essay, argue the term lacks scientific rigor, while others maintain that AGI's core meaning — domain-independent intelligence with multiple, learned, potentially conflicting goals — is coherent even if not yet achieved . Elsewhere's corpus does not cover this subject as a specific entity with founding details, funding, or institutional ownership.