Creativity fundamentally comes from memorization?

The science/engineering/math tests I took at Caltech were all open book, open note. They were not about regurgitating facts and formulae. But if you didn't already know them, you didn't have the time to open the book and learn about them.

My high school had majors and one of them was effectively EE; the 14/15 year olds in my major had those formulas down inside of 3 weeks... what EEs did you know that couldn't outperform teenagers?

...I mean, I didn't even go to that great of a college and no one would have made it past the second year of EE without memorizing 10x more formulas than that.

I'm just completely lost on how it's even possible to have an EE degree and needing a card. Signal processing classes required math 100x more difficult than that. I had to know quaternions by my second dsp class.

Indian math system is not memorisation based either.

Math anywhere in the world is all about how many patterns you know/seen. And inventing new math is all about changing one small thing about the stuff you already know and see if it remains logically consistent.

Knowing what to change largely depends on the stuff you already know. To that end even if you don't memorize facts, you still need to memorize patterns.

You have to memorize something. Nobody invents the Apple pie from scratch.

I've long wanted to write about this but never been able to think of anything original to say, but your question forced me to face this with effort. Thanks!

When making flashcards I draw a lot from the softer type of theory-building they do in social sciences. I ask questions like

- What are the properties of this?

- What variants of this exist? I.e. how would I recognise this in the wild, or in other shapes?

- What subcomponents can this be deconstructed into?

- Into which bigger picture does this fit?

- What are the consequences of this? What are its antecedents?

- What is this a special case of? What would a generalisation of this look like?

- Which are other related things? What are their similarities and differences?

- In what context might I need to know this?

Whenever I encounter what seems like a significant thing I loosely ask some of these questions, and try to construct atomic, focused flashcards from the answers.

I say loosely because it would take forever to to through all questions for all flashcards I make, so there's some bit of intuition that attracts me to which I think are the most significant questions for any given thing.

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One trick to make flashcards more specific that I use (maybe even abuse) is putting part of the answer into the prompt. Instead of prompting "What is the property of subexponential distributions I found meaningful in this book?" I might prompt "What behaviour do subexponential distributions have around high barriers that others don't?" -- I'm giving away part of the answer by including "high barrier" in the prompt, but I'm okay with that.

If I'm concerned about that, I might create a second flashcard prompting something like "What can a subexponential distribution do in one step that a more well-behaved distribution needs many steps to do?" with the answer "clear a high barrier". That captures both sides of the property without making too general a prompt.

I also do this a lot with "why" questions. Instead of prompting "what is the definition of y?" I might prompt "why is the definition of y=f(x)?" That gives away essentially the entire answer but focuses on the why instead.

> But all knowledge a person have is based on memory

No it isn't, tacit knowledge isn't based on remembering something it is based on having made a model that parses something. That is what you want to build, memory itself is mostly redundant compared to those models, as those models lets you easily rediscover information but memory doesn't let you parse problems.

Memorizing something implies there is a piece of information you can later recall. If there is nothing to recall such as with tacit skills then you don't learn it by memorizing, you learn it by practice and thinking and theorizing until it "clicks".

A computer can remember everything trivially, but it hasn't built any models based on the information so all that information is useful. The same happens in our head, the value isn't in the memory it is in the structures you built as an answer to that memory. The memory itself is a red herring, don't chase it, chase the understanding.

So for example, I have made a model in my head that parses electronic circuit problems for me, with that I don't need any formulas as it does the work. There is no memory tied to that model, it just solves things, there is nothing to recall, nothing to write down etc, it isn't a piece of information it is an active skill I have built. Saying otherwise is like saying that you memorize how to move your arm, no that is you building up intuition and reflexes, that isn't what we call memorizing.

You can call that a pattern matcher, you can't recall one of your heads pattern matchers. Pattern matchers can be tied to recall, but pattern matchers can also solve problems for you by themselves without ever invoking any memory. Pattern matchers are much more powerful than memories since they can solve a whole slew of similar problems while memories just solves one thing, so there is no need to go memory -> pattern matcher, you can go instantly to pattern matcher without ever commiting anything to memory.