Neat, I guess humans have a `import dlib; dlib.get_frontal_face_detector()` somewhere. ;)
Humans are born with knowledge priors regarding space and agentness (even the ability to recognize faces from non-faces) https://medicalxpress.com/news/2020-03-earliest-newborns-visual-cortex-reveals.amp …pic.twitter.com/VBKftr7btn
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Cognitive biases, apophenia (incl. pareidolia) and similar phenomena tell us much about the human priors The human priors or human nature are the basis for the explanation of other phenomena, e.g religion
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Does this translates into a need for more knowledge-based approaches in machine learning, as complement to statistical learning? What can we learn from these insights to improve how machines learn?
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We also need to use more symbolic learning.
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Well.. we don't "know" things when born, as knowledge is constructed, but the innate behaviors are there to bootstrap the process (it's why we still see shapes in clouds or a face on Mars).
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Human is more than body mind complex, there is some higher intelligence and power.
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Going out on a veeery frail limb here: It'd be fun to disprove a theory such as: All cellular life has a tuned communication mechanism at the quantum level, paired at the time of cell division [imagine pulling apart a dualistic sphere in a smoke test chamber: mirrored swirls].
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We are not born empty, but also not complete either.
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