After life originated on Earth, the next important transition was the emergence of cognitive life, in which simple organisms self-organized into dynamical networks to compress and express complex information in the environment about their own preservation. Cognition in the biosphere can be understood as the formation of paths of information between single entities, implementing a dynamical way to compress relevant information for their own survival, enabling them to make predictions about their environment on much shorter timescales than Darwinian evolution. Ultimately, information’s substrate-independence and interoperability property makes possible symbolic representations such as the genetic code, based upon which life was able to develop, eventually leading to human societies’ complex cognitive capabilities, such as language, science and technology. We argue that cognition is the informational software to life’s physical hardware. If life can be formulated computationally to be the search for sources of free energy in an environment in order to maintain its own existence, then cognition is better understood as finding efficient encodings and algorithms to make this search probable to make the information flow network last. Cognition then becomes the “abstract computation of life”, with the purpose to make the unlikely trajectories more likely for the sake of the organism’s survival. Here, we introduce the notion of “cognitive information”, and show how these sets of phenomena can be quantified by well known as well as new computational tools at the intersection of artificial life, information theory and machine learning.