Compression is important to processes going on in the mind, but I don't think its a central concept to understand how the mind words. Compression is relevant in

Compression is important to processes going on in the mind, but I don't think its a central concept to understand how the mind words. Compression is relevant inasmuch as our brains perform lossy compression to capture the relevant regularity in our sense data. But this is only the start of the analysis; it doesn't explain anything useful about our cognitive architecture. The problem is strong compression trades space requirements for computational requirements. But going all-in on compression is optimizing for the wrong thing in the context of a bag-of-neurons computational model. von Neumann architectures are good at fast and precise state transitions. A bag-of-neurons is good at leveraging relationships to minimize computational requirements. Thus a plausible cognitive architecture for the mind should emphasize relationships rather than computation. A good cognitive architecture is one where relationships in the data are maximally revealed by the architecture, thus minimizing the computational burden to access and utilize the relationship. This explains why the visual system takes up so much volume of the brain. 3-dimensional sense data is packed with interrelationships and these relationships need support from the cognitive architecture to be utilized. The compression view is only useful to a point--after that the constraints on the bag-of-neurons model become dominant and must drive the architecture search. When it comes to phenomenal consciousness, the question then becomes: is there anything it is like to be a process whose topological structure maximally captures external and internal state relationships? My intuition tells me the answer is yes. One functional requirement of a human brain is that it `believes` it is the author of its decisions. To manifest this `belief` requires a self-representation of itself distinct from the environment, i.e. a target of the attribution of authorship. Facts of this self-representation entail what it is like to be this topological structure.