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e.g. The only three practical applications of a gravity gradiometer are like: (1) Answer fundamental physics questions about the Earth and the universe. (2) Obtain navigational data for inertial guidance system to nuke someone else with nuclear ballistic missiles. (3) Find oil.

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Time is the most scarce resource in my field. And yours too, probably.

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@lisyarus Turing completeness is the empirically unique reasonable notion of computability for functions Nat -> Nat, but for (Nat -> Nat) -> Nat (aka type-2 computability) there are multiple reasonable notions of computation that are not equivalent, so there is no such thing as “Turing completeness” there

Put a hot woman into a rationalist party—most flagrant simping I've ever seen

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#30daymapchallenge Day 2 (Lines): Sequential postcodes of Germany, making use of the unpopular 🌈 rainbow color map. This map was inspired by Kate, aka @pokateo_maps on the bird site.

x.com/pokateo_maps/status/1587

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expression of frustration about people who touch other while sleeping next to each other

Category Mech for mechanisms, and Incen for incentive-compatible mechanisms

Is this anything? (I don't know category theory)

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I'm going to be in the PRC autumn 2025, anyone can (self-)recommend people to meet up with?

(or places to visit, but I'm less interested in places)

Interests: AI, geopolitics, daygame/deliberate-getting-laid, algorithms, meditation, futurism/forecasting, building comprehensive world-models, reading, weightlifting

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Algebraic derivatives living over vector spaces with tensor product would probably be the easiest thing to figure out, surely some commutative algebraists would care about such a thing

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I feel like a lot of mathematicians would be interested in the fact that we know how to generalise the chain rule to non-cartesian settings using optics, if only we had examples that they'd be interested in. The first thing I can think of is trying to get a chain rule for the derivative of a function that's a stochastic process, where the value of the function and its derivative are probabilistically correlated

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@niplav Mistakes are where you learn. Successes are where you celebrate.

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