NaiveTortoise

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This is awesome! I've been thinking I should try out the natural number game for a while because I feel like formal theorem proving will scratch my coding / video game itch in a way normal math doesn't.

Against Dog Ownership

Minor note - having spent significant time in multiple homes with one dog and more recently a home with multiple, my anecdotal observation is that even just having 2 dogs changes the dynamic from dog obsessed with humans to dogs that have each other and are maybe still obsessed with their humans as well.

What are your greatest one-shot life improvements?

Are you putting yours on paper or storing it digitally?

Project Proposal: Gears of Aging

(Not the author, obviously.) Part of my personal intuition against this view is that even amongst mammals, lifespans and the way in which lives ends seems to vary quite a bit. See, for example, the biological immortality Wikipedia page, this article about sea sponges and bowhead whales, and this one about naked mole rats.

That said, it's still possible we're locked in a very tricky-to-get-out-of local optima in a high dimensional space that makes it very hard for us to make local improvements. But then I suspect OP's response would be that the way to get out of local optima is to understand gears.

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Only related to the first part of your post, I suspect Pearl!2020 would say the coarse-grained model should be some sort of causal model on which we can do counterfactual reasoning.

Insights from Euclid's 'Elements'

FWIW as someone who learned Python first, was exposed to C but didn't really understand it, and then only really learned C later (by playing around with / hacking on the OpenBSD operating system and also working on a project that used C++ with mainly only features from C), I've always found the following argument quite suspect with respect to programming:

(FWIW I've made the same argument in the context of training programmers, preferring that they have to learn to work with assembly, FORTRAN, and C because the difficulty forced me to understand a lot of useful details that help me even when working in higher level languages that can't be fully appreciated if you are, for example, trying to simulate the experience of managing memory or creating loops with JUMPIF in a language where it's not necessary. Not exactly the same as what's going on here but of the same type.)

It's undoubtedly true that I see some difference before & after "grokking" low-level programming in terms of being able to better debug issues with low-level networking code and maybe having a better intuition for performance. Now in fairness, most of my programming work hasn't been super performance focused. But, at the same time, I found learning lower level programming much easier after having already internalized decent programming practices (like writing tests and structuring my code) which allowed me to focus on the unique difficulties of C and assembly. Furthermore, I was much more motivated to understand C & assembly because I felt like I had a reason to do so rather than just doing it because (no snark intended) old-school programmers had to do so when they were learning.

For these reasons, I definitely would not recommend someone who wants to learn programming start with C & assembly unless they have a goal that requires it. This just seems to me like going to hard mode directly primarily because that's what people used to have to do. As I said above, I'm fairly convinced that the lessons you learn from doing so are things you can pick up later and not so necessary that you'll be handicapped without them.

(Of course, all of this is predicated on the assumption that I have the skills you claim one learns from learning these languages, which I admit you have no reason to believe purely based on my comments / posts.)

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It seems not that conscious. I suspect it's similar to very scrupulous people who just clean / tidy up by default. That said, I am very curious whether it's cultivatable in a less pathological way.

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I'm interested in reading more about what might've been going on in Ramanujan's head when he did math. So far, the best thing I've found is this.

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How to remember everything (not about Anki)

In this fascinating article, Gary Marcus (now better known as a Deep Learning critic, for better or worse) profiles Jill Price, a woman who has an exceptional autobiographical memory. However, unlike others that studied Price, Marcus plays the role of the skeptic and comes to the conclusion that Price's memory is not exceptional in general, but instead only for the facts about her life, which she obsesses over constantly.

Now obsessing over autobiographical memories is not something I'd recommend to people, but reading this did make me realize that to the degree it's cultivate-able, continuously mulling over stuff you've learned is a viable strategy for remembering it much better.

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