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Logic doesn't apply to the real world. D. R. Hofstadter and D. C. Dennett (eds.) The Mind's I, 1981.
Marvin Minsky
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Interpretation

What this quote means

This quote suggests that logical reasoning may fall short when confronting the complexities of the real world.

Marvin Minsky's quote emphasizes that while logic is a powerful tool in theory, the unpredictability and complexity of real-life situations often render strict logical frameworks inadequate. It points to the limitations of purely rational thought in understanding human experience and the world around us, highlighting the importance of embracing ambiguity and uncertainty.

Themes

LogicReal WorldComplexityUnderstandingReasoning

In practice

Example use cases

In a debate about artificial intelligence, one might use this quote to argue against overly simplistic views on machine reasoning.

More from Marvin Minsky

If you understand something in only one way, then you don't really understand it at all. The secret of what anything means to us depends on how we've connected it to all other things we know. Well-connected representations let you turn ideas around in your mind, to envision things from many perspectives until you find one that works for you. And that's what we mean by thinking!
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There was a failure to recognize the deep problems in AI; for instance, those captured in Blocks World. The people building physical robots learned nothing.
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You don't understand anything unless you understand there are at least 3 ways.
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I think every person either inherits or eventually makes up their own idea of what they are and who they are and what caused the world to be, and it seems to me that these stories of creation myth, adopted by different cultures - most of them are less insightful than the stories made up by individual poets and writers.
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I believe that everyone has to construct a mental model of what they are and where they came from and why they are as they are, and the word soul in each person is the name for that particular mish-mash of those fully formed ideas of one's nature.
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If you just have a single problem to solve, then fine, go ahead and use a neural network. But if you want to do science and understand how to choose architectures, or how to go to a new problem, you have to understand what different architectures can and cannot do.
Marvin MinskyRead

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