Xkcd time updating gif
In particular, he’s obsessed with showing how “embodied” everything is all the time.This gets kind of awkward, since the predictive processing model isn’t really a natural match for embodiment theory, and describes a brain which is pretty embodied in some ways but not-so-embodied in others.For instance, our visual system detects the presence of shadows in the image and removes them.At a glance, our brain unconsciously infers the sources of lights and deduces the shape, opacity, reflectance, and luminance of the objects.Predictive processing begins by asking: how does this happen?
The bottom-up stream starts out as all that incomprehensible light and darkness and noise that we need to process.
Author Andy Clark (a professor of logic and metaphysics, of all things!
) is clearly brilliant, but prone to going on long digressions about various esoteric philosophy-of-cognitive-science debates.
Given the answer to that question, how would it affect the distribution of edges in the scene?
Given the answer to that question, how would it affect the raw-sense data received? The bottom-up sensory stream has to deal with fog, static, darkness, and neural noise; it knows that whatever forms it tries to extract from this signal might or might not be real.
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Then each level uses Bayes’ Theorem to integrate these two sources of probabilistic evidence as best it can. First, the sense data and predictions may more-or-less match.