The aim of this thesis is to argue against achieving Artificial General Intelligence (AGI) revolvingaround (i) programs being insufficient to create human­like intelligence due to their lack ofsemantic grasping and (ii) our inability to effectively model complex systems. The challenge ismagnified by our struggles to mathematically explain basic complex phenomena, raising doubtsabout our capability to replicate intricate structures like human intelligence or vertebrate brains.Attaining AGI requires transcending the limitations of current mathematical and computationalparadigms, with a call for a revolutionary leap in both areas. Despite these challenges, replicatingnon­human intelligence, even if encountered, remains unfeasible due to complexities beyond ourcurrent capabilities. Overall, achieving AGI presents an immensely challenging prospect for theforeseeable future.