Environments as a bottleneck in AGI development

Abstract

Multiple factors influence the ease of training an Artificial General Intelligence (AGI) model. This article discusses the importance of the training environment in supporting the development of AGI. Two hypotheses are considered: the “easy paths” hypothesis proposes that many environments encourage the development of AGI, while the “hard paths” hypothesis suggests that such environments are rare. The author argues in favor of the latter, citing historical examples of specific tasks, such as chess, Go, and StarCraft, which, despite requiring advanced skills, did not lead to AGI development. The difficulty in creating favorable training environments is highlighted by comparing AGI development to the evolution of human intelligence, emphasizing the complex interplay of various factors that contributed to human cognitive abilities. The author concludes that AGI development may face challenges due to a lack of environments that promote general intelligence – AI-generated abstract.