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Cake day: June 12th, 2023

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  • Kogasa@programming.devtoMemes@lemmy.mlMath
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    14 days ago

    Stokes’ theorem. Almost the same thing as the high school one. It generalizes the fundamental theorem of calculus to arbitrary smooth manifolds. In the case that M is the interval [a, x] and ω is the differential 1-form f(t)dt on M, one has dω = f’(t)dt and ∂M is the oriented tuple {+x, -a}. Integrating f(t)dt over a finite set of oriented points is the same as evaluating at each point and summing, with negatively-oriented points getting a negative sign. Then Stokes’ theorem as written says that f(x) - f(a) = integral from a to x of f’(t) dt.


  • Going to almost certainly be less than 1. Moving further up the food chain results in energy losses. Those fish are going to use energy for their own body and such

    For sure, which is why I said “another food source would be needed.” I had in mind something like the wild-caught fish being processed into something useful as part of a more efficient food chain, e.g. combined with efficiently-farmed plant material.

    Moreover there’s high mortality rates inside of fish farms for fish themselves.

    I don’t have any context on the other pros and cons of fish farming, so definitely not arguing whether they’re a net positive or not.



  • We aren’t trying to establish that neurons are conscious. The thought experiment presupposes that there is a consciousness, something capable of understanding, in the room. But there is no understanding because of the circumstances of the room. This demonstrates that the appearance of understanding cannot confirm the presence of understanding. The thought experiment can’t be formulated without a prior concept of what it means for a human consciousness to understand something, so I’m not sure it makes sense to say a human mind “is a Chinese room.” Anyway, the fact that a human mind can understand anything is established by completely different lines of thought.



  • This fails to engage with the thought experiment. The question isn’t if “the room is fluent in Chinese.” It is whether the machine learning model is actually comparable to the person in the room, executing program instructions to turn input into output without ever understanding anything about the input or output.










  • “Measure” is meant in the specific sense of measure theory. The prototypical example is the Lebesgue measure, which generalizes the intuitive definition of length, area, volume, etc. to N-dimensional space.

    As a pseudo definition, we may assume:

    1. The measure of a rectangle is its length times its width.

    2. The measure of the disjoint union of two sets is the sum of their measures.

    In 2), we can relax the assumption that the two sets are disjoint slightly, as long as the overlap is small (e.g. two rectangles overlapping on an edge). This suggests a definition for the measure of any set: cover it with rectangles and sum their areas. For most sets, the cover will not be exact, i.e. some rectangles will lie partially outside the set, but these inexact covers can always be refined by subdividing the overhanging rectangles. The (Lebesgue) measure of a set is then defined as the greatest lower bound of all possible such approximations by rectangles.

    There are 2 edge cases that quickly arise with this definition. One is the case of zero measure: naturally, a finite set of points has measure zero, since you can cover each point with a rectangle of arbitrarily small area, hence the greatest lower bound is 0. One can cover any countably infinite set with rectangles of area epsilon/n^(2) so that the sum can be made arbitrarily small, too. Even less intuitively, an uncountably infinite and topologically dense set of points can have measure 0 too, e.g. the Cantor set.

    The other edge case is the unmeasurable set. Above, I mentioned a subdivision process and defined the measure as the limit of that process. I took for granted that the limit exists. Indeed, it is hard to imagine otherwise, and that is precisely because under reasonably intuitive axioms (ZF + dependent choice) it is consistent to assume the limit always exists. If you take the full axiom of choice, you may “construct” a counterexample, e.g. the Vitali set. The necessity of the axiom of choice in defining this set ensures that it is difficult to gain any geometric intuition about it. Suffice it to say that the set is both too “substantial” to have measure 0, yet too “fragmented” to have any positive measure, and is therefore not well behaved enough to have a measure at all.


  • By performing measure-preserving transformations to non-measurable sets and acting surprised when at the end of the day measure isn’t preserved. I don’t blame AC for that. AC only implies the existence of a non-measurable set, which is in itself not totally counter-intuitive.