People think of things like language and mathematics as basic and foundational, but they're actually examples of very high level abstract thinking. That's what you should take away from this post (while ignoring the fact that it's marketing for a math skills company). And why is this important? It informs our understanding of AI. Consider this claim: "While deep learning require large amounts of training data to perform at the level of humans, children can learn from a small number of examples. A few storybook pictures can teach them not only about cats and dogs but jaguars and rhinos and unicorns... One of the secrets of children's learning is that they construct models or theories of the world. … even 1-year-old babies know a lot about objects."
Well, that's old-school constructivist thinking, and it's not wrong, exactly, but we need to remember: a 1-year old baby has had a year's worth of near-constant data input. The ability to construct models or theories, like language and mathematics, is a high-level skill. We don't get to it without a lot of pattern-recognition having happened first. It's just that we pretend it hasn't happened in the child, while in AI it is explicitly done. Via Doug Peterson.
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