This paper seeks to elucidate weaknesses within the philosophy of artificial intelligence (AI) in an attempt to work towards a more holistic understanding about what kind of knowledge satisfies the conditions of intelligence. It begins by articulating the development of AI research, clarifying the implications of the work of Turing (1950) and Searle (1980). From here, a background is given of the development of artificial life (AL), and the notion of game-playing is introduced as a construct for revealing intelligence capabilities. The game of chess is recognised as having been paradigmatic in AI as a measure of machines against humans, with IBM’s Deep Blue being the critical machine to provoke a sense of machines surpassing humans. When Deep Blue beat the Grand Master chess player Garry Kasparov in 1997, the world would sit back and contemplate whether machines are too capable. In response, the paper rejects chess-playing as a sufficient indication of intelligence in the strong sense and argues that other kinds of games serve as a greater challenge and a more accurate reflection of human intelligence. From this, Bernard Suits’s classic philosophy text, The Grasshopper, is used to elaborate on what it entails to play a game. The Deep Blue Grasshopper is thus, a game-playing AI machine that responds to a broader notion of game-playing. This notion encompasses the possibility for creativity, spontaneity, and arbitrary choices that lead to successful strategic options. The paper concludes with a critique of the possibility of there being non-linear intelligence that can sustain the main thesis of the paper.