Wang’s definition of Artificial Intelligence is developed via careful and thorough abstractions from human intelligence. Motivated by the goal of building a definition that will be genuinely useful for AI researchers, Wang ultimately provides an agent-centric definition that focuses on systems operating with insufficient knowledge and resources. The definition captures many key components of intelligence, but we suggest that task success could play a slightly larger role. This brings the definition closer in line with our use of the term with animals and human experts, and also further aligns the definition’s associated research framework with the subfield of deep reinforcement learning aimed at general intelligence.