The problem is that knowledge needs to be in your head to fully participate in reasoning, pattern recognition, creativity, problem solving and basically anything that requires intelligence. No knowledge in your head makes you a rock, not unencumbered.
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This sounds abstract, so let me give a clear example. Let's say you're trying to solve a programming problem and you need to look up regular expression syntax. No problem, just Google regex and in a few seconds you can get the syntax you need.
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However, this protocol is of no use if you have no idea what regex expressions are, how they might work or how they might solve the problem at hand. In other words, you may be able to avoid memorizing syntax, but if you don't hold the *idea* of regex in your head, it's useless.
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If you look at experts in any domain, the thing that separates them is having enormous libraries of stored patterns. This is the dominant "chunking" model, which argues that without in-head knowledge, you can't even *see* what question to ask.
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Classic studies of this involved chess masters/novices. Without enough pattern knowledge, all you see is the pieces. A master sees pins, forks, tactics and higher and higher abstractions.
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Expertise merely illustrates the problem, it isn't the only situation where this applies. We're all experts in our native language. If you don't know a single word you can look it up. If you don't know any words, you can't do anything. It has to be in your head.
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I think the misguided view Tiago is promoting is because of a false dichotomy between "remembering" and "reasoning" or something else. This may itself be a false analogy from computers where CPUs and "logic" is separate from RAM and storage.
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Replying to @ScottHYoung
Computers actually make a good analogy for your point when you realize that every computer has several different types of memory to cover a wide range of different use cases along the spectrum of tradeoffs between size and speedpic.twitter.com/7VVaECOon0
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Replying to @levity
Computers have good speed/size tradeoffs. But the physical mechanisms that implement logic CPU, ALUs, etc. are distinct from memory components in registers, RAM, hard drive, etc.. In the brain, it is likely that stored patterns *are* the logic.
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Replying to @ScottHYoung @levity
Think ML systems where the "stored" patterns of thousands of training examples are the thing that allows for the algorithm to function. Brains are likely different in some respects, but this seems a closer metaphor than the computer division of labor.
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Even “ordinary”, non-ML software serves for this analogy. I have to keep a program in working memory before I can run it. The logic built into hardware is very low-level, more analogous IMO to the biochemical workings of neurons.
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