The publication of Shannon’s ‘A Mathematical Theory of Communication’ (1948) has been described as “delayed-action bomb”. It reshaped psychology and neuroscience and has been credited as foundational to the field of cognitive science. Yet after the initial shockwave, the pace of new ideas in cognitive science emerging from the theory slowed dramatically. This trend has begun to reverse, as evidenced by this workshop. But what accounts for the stagnation, and what accounts for the recent change? I argue that information is not enough. Information is a resource or a constraint, but is not sufficient as a computational theory of intelligence. An important step forward for cognitive science came from the combination of information theory with expected utility theory (rate-distortion theory). More recent progress has been driven by the advent of principled approximation methods in computation. The combination of all of these ideas yields ‘information-theoretic computational rationality’, a powerful framework for understanding natural intelligence.