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John D. Cook Profile picture
John D. Cook
@JohnDCook
Simple kind of man
Jul 13 • 4 tweets • 1 min read
Of course academic exercises are artificial: they’re exercises.

That’s necessary. The only harm is in pretending they’re more realistic than they are. Complaining about unrealistic exercises is an intermediate growth stage.

You know enough to start to seeing the simplifications but not enough to not need them and not enough to appreciate them.
Mar 13 • 6 tweets • 2 min read
I did an experiment this morning, asking Grok and ChatGPT to reproduce sheet music from a photo. The results were hilariously bad. 🧵 1/n Here's the first clip I tried. 2/ Image
Apr 15, 2025 • 5 tweets • 2 min read
It’s telling that the equation associated with chaos theory is a canonical EXAMPLE, not a model, a definition, or a theorem. There are theorems in chaos theory, but for most people chaos theory is a set of examples.

Not models per se, but cautionary tales. Image
Nov 2, 2023 • 6 tweets • 2 min read
Visualizing a 4200 km circle around Paris under various projections.

First, Robinson.

🧵 1/6 Image Winkel-Snyder projection 2/6 Image
Oct 11, 2023 • 6 tweets • 1 min read
The key to resolving an argument over percentage calculations is to insist that every time someone says “percent” they immediately follow it by “of.”

In grammatical lingo, the argument very likely boils down to ambiguous antecedents.

1/n For example, what does 20% profit mean?

Does it mean the supplier adds 20% of the retail cost to his charge, or does it mean 20% of what the customer pays is the supplier’s profit?

2/n
May 28, 2022 • 4 tweets • 1 min read
Why memorize anything you can look up? Some reasons:

(1) Maintain flow
(2) Recognize patterns
(3) Combine idea

1/4 If looking something up disrupts your concentration, it may be worth memorizing.

2/4
Feb 14, 2022 • 4 tweets • 1 min read
Gell-Mann amnesia: This source is dead wrong about things I understand, but they’re probably right about everything else.

Gell-Mann memory: This source is dead wrong about things I understand, so my default assumption is they’re wrong about everything else. Gell-Mann meets Bayes: This source was right (wrong) about what I can verify, and so I will update my prior probability in the direction of more (less) default trust.