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minimizing Surprise = Maximizing model evidence.
Variational Free Energy is a bound on . Model as self? Self-evidencing. Model & Self.
The model can/does have a model.
What is a good model?
Statistics absorbed many terms of cognitive science:
Attention, Learning, Memory .... And now those terms are getting re-laundered back into the statistics of cognition. These lineages are separating and re-fusing back together. They have shared ancestry & also recent differences & shared context.
How can/might come into the culture? Organic chemistry → Bringing in the Hexagon, etc. Looking “high tech” → Neurons, cells, collective behavior, Hexagons. How to connect with AI, ChatGPT? e.g. LLM as next-token predictor. High Road — Opposites co-exist and are the same. Two some. Environment is the fatalist point of view, always going to be part of the environment.
Mnemonics & Memes
The Art of Memory by Francis A. Yates. . ... a memory palace/parade.
Linus with his “Markov blanket”
Snoopy flies OODA loop:
the active inference process has a velocity, meaning likewise acceleration.
Variational Free Energy (”nasty surprises” suggests a faulty model):
Or is this a case of confirming evidence that one’s self image — of a model loser perhaps — is correct? Lucy’s model of Charlie Brown seems spot on.