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I don't quite get it either. In my line of study, a "Bayesian approach" refers to modeling the conditional posterior probability of the evidence for an event along with the prior probability of the event instead of modeling the conditional likelihood of the event directly. I'm not sure why there is a conspiracy around such a concept.

As an aspiring applied mathematician, I often think of myself as a "wizard"(student) learning "spells"(mathematical models).

Perhaps I need to start referring to myself by a cooler word like "expirimancer", though my ear for word coinage has never been good.

It's interesting to me that you refer to "AI" as a singular monolithic noun. Have you fleshed out your opinion of what AI is in a previous post?

An alternative view is that our intelligence is made of many component intelligences. For example, a professor of mine is working on machine vision. Many people would agree that a machine that can distinguish between the faces of the researchers that built it would be more "intelligent" than one that could not, but that ability itself does not define intelligence. We also have many other behaviors besides visual pattern recognition that are considered intelligent. What do you think?