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Mathematics is hard for mathematicians to understand too

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Re: Mathematics is hard for mathematicians to understand too

#81
post #80

Earlier quoted context omitted.

> ... It's optimized for rewriting a formula many times. It's not just "rewriting" arbitrarily either, but rewriting according to well-known rules of expression manipulation such as associativity, commutativity, distributivity of various operations, the properties of equality and order relations, etc. It's precisely when you have such strong identifiable properties that you tend to resort to operator-like notation in…

Hmm, I'm not sure whether operator-like notation has any special advantage for commutativity and distributivity other than brevity. a + b and add(a, b) are equally easy to rewrite as b + a and add(b, a). Maybe there is an advantage for associativity, in that rewriting add(a, add(b, c)) as add(add(a, b), c) is harder than rewriting a + b + c as a + b + c. Most of the time you would have just written add(a, b, c) in th…

We do often find add(a, b, c), just written as Σ(a, b, c). Similar for mul and Π. The binary sub operator can be simply rewritten in terms of add and unary minus; the fact that we write (a - b) instead of (a + [-b]) or perhaps Σ(a, [-b]) is ultimately a matter of notational convenience, but comes at some cost in mathematical elegance. Considering operators that are commutative yet not associative is not very useful; ultimately we want more from our expression rewriting than just flipping left and right subexpressions within an expression tree while keeping the overall complexity unchanged.

Re: Mathematics is hard for mathematicians to understand too

#82
The views quoted are just as cryptic as modern mathematics. Did mathematicians lose the ability to convey stuff tin plain simple ways?

Probably they are trying to romanticize something that may not sound good if told plainly.

Face it. Mathematics is one of fields strongly affected by AI, just like programming. You need to be more straight forward about it rather than beating around the bush.

To simply put, it appears to be a struggle for redefining new road map, survival and adoption in AI era.

Re: Mathematics is hard for mathematicians to understand too

#83
> Venkatesh argued that the record on this is terrible, lamenting that “for a typical paper or talk, very few of us understand it.”

> "few of us"

You see, if you plebs are unable to understand our genius its solely due to your inadequacies as a person and as an intellect, but if we are unable to understand our genius, well, that's a lamentable crisis.

To make Mathematics "understandable" simply requires the inclusion of numerical examples. A suggestion 'the mathematics community' is hostile to.

If you are unable to express numerically then I'd argue you are unable to understand.

Re: Mathematics is hard for mathematicians to understand too

#84
post #80

Earlier quoted context omitted.

Hmm, I'm not sure whether operator-like notation has any special advantage for commutativity and distributivity other than brevity. a + b and add(a, b) are equally easy to rewrite as b + a and add(b, a). Maybe there is an advantage for associativity, in that rewriting add(a, add(b, c)) as add(add(a, b), c) is harder than rewriting a + b + c as a + b + c. Most of the time you would have just written add(a, b, c) in th…

We do often find add(a, b, c), just written as Σ(a, b, c). Similar for mul and Π. The binary sub operator can be simply rewritten in terms of add and unary minus; the fact that we write (a - b) instead of (a + [-b]) or perhaps Σ(a, [-b]) is ultimately a matter of notational convenience, but comes at some cost in mathematical elegance. Considering operators that are commutative yet not associative is not very useful;…

Usually you'd have to write that as \sum_{v \in \{a, b, c\}} v; one of the ways I think conventional math notation could in fact be improved would be by separating the aggregate function of summation from the generation of the items, allowing you to write \sum \{a, b, c\}, at the minor cost of having to write \sum_{i = 1}^N i^2 as something like \sum |_{i=1}^N i^2.

It's not conventional to write commutative-but-not-associative functions as infix operators, but I don't think that's due to some principled reason, but just because they're not very common; non-associative operators such as subtraction and function application are almost universally written with infix operators, even the empty-string operator in the case of function application. The most common one is probably the Sheffer stroke for NAND (although Sheffer himself used it to mean NOR in his 01913 paper: https://www.ams.org/journals/tran/1913-014-04/S0002-9947-191...).

You can go a bit further in the direction of logical manipulability, as George Spencer Brown did with "Laws of Form" (LoF): his logical connective, the "cross", is an N-ary negation function whose arguments are written under the operation symbol without separators between them, and he denotes one of the elementary boolean values as the empty string (let's call it false, making the cross NOR). ASCII isn't good at reproducing his "cross" notation, but if we use brackets instead, we can represent his two axioms as:

    [][] = []  (not false or not false is not false)
    [[]] =     (not not false is false)
In this way Spencer Brown harnesses the free monoid on his symbols: the empty string is the identity element of the free monoid, so appending it to the arguments of a cross doesn't change them and thus can't change the cross's value. Homomorphically, false is the identity element of disjunction, which is a bounded semilattice, and thus a monoid.

This allows not only the associative axiom but also the identity axiom to be simple string identity, which seems like a real notational advantage. (Too bad there isn't any equivalent for the commutative axiom.) It allows Spencer Brown to derive all of Boolean logic from those two simple axioms.

However, so far, I haven't found that the LoF notation is an actual improvement over conventional algebraic notation. Things like normalization to disjunctive normal form seem much more confusing:

    a(b + c)  → ab + ac          (conventional notation, rewrite rule towards DNF)
    [[a][bc]] → [[a][b]][[a][c]] (LoF notation)
It's a little less noisy in Spencer Brown's original two-dimensional representation (note that the vertical breaks between the U+2502 BOX DRAWINGS LIGHT VERTICAL characters are not supposed to be there; possibly if you paste this into a text editor or terminal it will look better)

    ┌─────    ┌────┌────
    │┌─┌──  → │┌─┌─│┌─┌─
    ││a│bc    ││a│b││a│c
but not, to my eye, any less confusing.

Re: Mathematics is hard for mathematicians to understand too

#85

A lot of people here suggesting they'd be great mathematicians if only it wasn't for the pesky notation. What they are missing is that the notation is the easy part..

Indeed, confused people say things that don't make sense.

Re: Mathematics is hard for mathematicians to understand too

#86
post #24

Earlier quoted context omitted.

> I’ve long thought that more of us could devout time to serious maths problems if they were written in a language we all understood. That assumes it’s the language that makes it hard to understand serious math problems. That’s partially true (and the reason why mathematicians keep inventing new language), but IMO the complexity of truly understanding large parts of mathematics is intrinsic, not dependent on terminol…

Precisely. Think of mathematics like a game. Players of magic the gathering will say a creature "has flying" by which they mean "it can only be blocked by other creatures with reach or flying". Newcomers obviously need to learn this jargon, but once they do, communication is greatly facilitated by not having to spell out the definition. Just like games, the definitions in mathematics are ethereal and purely formal as…

Well said.

I'd say the ability to take complicated definitions and to not have to through a rigorous definition every time the ideas are referenced are, in a sense a form of abstraction, and a necessary requirement to be able to do advanced Math in the first place.

Re: Mathematics is hard for mathematicians to understand too

#87
post #24

Earlier quoted context omitted.

> I’ve long thought that more of us could devout time to serious maths problems if they were written in a language we all understood. That assumes it’s the language that makes it hard to understand serious math problems. That’s partially true (and the reason why mathematicians keep inventing new language), but IMO the complexity of truly understanding large parts of mathematics is intrinsic, not dependent on terminol…

Precisely. Think of mathematics like a game. Players of magic the gathering will say a creature "has flying" by which they mean "it can only be blocked by other creatures with reach or flying". Newcomers obviously need to learn this jargon, but once they do, communication is greatly facilitated by not having to spell out the definition. Just like games, the definitions in mathematics are ethereal and purely formal as…

My entire being is anthithetical to this type of gatekeeping.

> You expect the players of the game to learn the rules before they play.

TFA is literally from a 'player' who has 'learned the rules' complaining that the papers remain indecipherable.

> You expect the players of the game to learn the rules before they play.

Actually, I expect to have to teach rules to new players before they play. We are different.

Re: Mathematics is hard for mathematicians to understand too

#88

A lot of people here suggesting they'd be great mathematicians if only it wasn't for the pesky notation. What they are missing is that the notation is the easy part..

> What they are missing is that the notation is the easy part.

This is so wrong it can only come from a place of inexperience and ignorance.

Mathematics is flush with inconsistent, abbreviated, and overloaded notation.

Show a child a matrix numerically and they can understand it, show them Ax+s=b, and watch the confusion.

Re: Mathematics is hard for mathematicians to understand too

#89
I find software engineers spend too much time focused on notation. Maybe they are right to do so and notation definitely can be helpful or a hindrance, but the goal of any mathematical field is understanding. It's not even to prove theorems. Proving theorems is useful (a) because it identifies what is true and under what circumstances, and (b) the act of proving forces one to build a deep understanding of the phenomenon under study. This requires looking at examples, making a hypothesis more specific or sometimes more general, using formal arguments, geometrical arguments, studying algebraic structures, basically anything that leads to better understanding. Ideally, one understands a subject so well that notation basically doesn't matter. In a sense, the really key ingredient are the definitions because the objects are chosen carefully to be interesting but workable.

If the idea is that the right notation will make getting insights easier, that's a futile path to go down on. What really helps is looking at objects and their relationships from multiple viewpoints. This is really what one does both in mathematics and physics.

Someone quoted von Neumann about getting used to mathematics. My interpretation always was that once is immersed in a topic, slowly it becomes natural enough that one can think about it without getting thrown off by relatively superficial strangeness. As a very simple example, someone might get thrown off the first time they learn about point-set topology. It might feel very abstract coming from analysis but after a standard semester course, almost everyone gets comfortable enough with the basic notions of topological spaces and homeomorphisms.

One thing mathematics education is really bad at is motivating the definitions. This is often done because progress is meandering and chaotic and exposing the full lineage of ideas would just take way too long. Physics education is generally far better at this. I don't know of a general solution except to pick up appropriate books that go over history (e.g. https://www.amazon.com/Genesis-Abstract-Group-Concept-Contri...)

Re: Mathematics is hard for mathematicians to understand too

#90

Earlier quoted context omitted.

Well, then poetry is not literature.

No, the argument is even dumber than that. The person who writes a poem hasn't created any literature. The person who hears that poem in circulation and records it in his notes has created literature; an anthology is literature but an original work isn't.

> No, the argument is even dumber than that. The person who writes a poem hasn't created any literature.

Sure they have, by virtue of writing it down. It becomes literature when it hits the paper (or computer screen, as it were).

(Unless you mean to imply that formulating an original poem in your mind counts as "writing", in which case I guess we illustrate the overarching point of value in shared symbols and language and the waste of time in stating our original definitions for every statement we want to make)

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