I'm not sure where or how to convey this, because I've seen several of these languages designed with AI, documentation created using AI, etc -- posted on Hacker News in the last months or so, and I've responded to each one with roughly the same feedback (and I'm assuming good faith: that the intent is that the poster wishes to grow as a language designer).
Your audience, or whoever you aim your work at, should be treated with respect. Otherwise, why should they give you the time of day? Why would you expect them to respond positively to effort alone when effort (in code and in shit prose) is extremely cheap right now? Their time is not cheap ...
When I read the documentation, and it is extremely clear that you haven't taken the time to clarify your ideas, when much of it is LLM prose, when much of the content introduces highfalutin ideas without motivation, blending categorical concepts (which, by the way, should never be mixed with vague prose claims about the language), violating my reader context model, preventing me from understanding what problem exactly your language design is solving (where is that problem stated clearly?), it is a waste of my time.
> The work took 3 weeks in total ... it's worth a look, and I hope it will win some converts, and that someone will want to help me with its development.
You've gone too fast, too much is vague, nothing is clear.
I'd delete everything, start over, and try and explain just one of the ideas clearly. Seriously. This sounds harsh, but it's honestly the correct approach to something as subtle and nuanced as programming language design.
> Your audience, or whoever you aim your work at, should be treated with respect.
I just want to amplify this point. As I was reading this, the LLMisms kept jumping out at me and each one felt like the author looking at me and deciding that my time spent reading this prose wasn't actually worth anything to them.
OP: I want YOUR thoughts, not the next token predictions of a gigantic pile of matrix multiplications. I want your awkward sentences, grammar mistakes, half-baked thoughts, self-doubt, silly jokes. I don't want this pile of grandiose mechanical slop completely devoid of humanity.
Personally I don't want to read the codebase AND book of someone 3 weeks into a mania focused on a subject it is unclear they have any prior experience with. Its disrespectful for someone to think they can produce something worthy of consuming another human's time under those constraints.
This isn’t about whether the writer uses LLM or not at all, nor is it about respect. The core novelty it tries to introduce is not hard to understand (even if it is not really that novel). If you don’t want to spend time thinking about what interesting idea it is exploring, that is fine, but pretending or insinuating that it is a LLM problem is just lazy.
Just a comment: this sounds a lot like when someone I knew mildly succumbed to AI psychosis, and thought he, with Gemini, had made some physics/metaphysics breakthrough. If you’re losing sleep and feeling distressed or euphoric, maybe lay off for a few days, no matter how hard that is. Talk to friends and/or family about unimportant things. Get outside for a while. Go back to old hobbies (reading, hiking, just going to coffee shops or thrift stores - whatever) and then reassess.
This language looks interesting, but I don’t understand the concepts. Does this stuff make sense to other people?
The heap is content-addressed over Λ₂₄: every value is mapped to a lattice point and canonicalized under the Conway group Co₀ (via libmmgroup), so the same content always lives at the same address.
What is ‘Λ₂₄’? What is a ‘lattice point’?
giving up the GC stopped being a renunciation, since cells are immutable and content-addressed, so there is nothing to trace and nothing to move
This kind of sounds like you’re saying that there’s nothing to free, which implies that nothing takes up memory, which I presume is not the case. Do you mean everything is immutable and content-addressed (like Git)? Doesn’t stuff still need to be freed somehow when the programs done with it, otherwise memory will grow for ever?
Agreed. Everything is a weird mixture of poetry and mathematics jargon. Basically every page of the book contains some esotericism which makes empty claims. It's completely divorced from reality.
Nope, and I actually learned about application of category theory to programming language in university.
I tried to get an idea about the main points, and then stumbled over
> a thing is what you can observe of it.
>
> [...]
>
> Content addressing is extensionality made physical (chapter 11): two values indistinguishable by observation are not merely equal, they are the same slot
That only works in a category because you have enough (a countably or uncountably infinite number) functions that you can compose and "test" so you don't need (or don't care) about the "value" itself.
But on a real computer that doesn't work, because you can't go beyond a countable number, and even then you run into the halting problem pretty soon. So equality in this model is not computable. Which is sort of bad if you want to somehow store values "in the same slot" just based on observability. It might work for string literals, and even for concatenated strings, but not in general.
Picking some random lattice (a lattice is a partially ordered structure with some extra conditions) as a base of addressing doesn't help...
So yes, crackpot AI slop. The words sort of make sense, but there's nothing solid behind it, and as soon as you look at details it falls apart.
Maybe I just don’t have the mathematics knowledge to understand it, but that doesn’t really tell me how you could represent one in memory, or use one as a backing store for a hash-addressed data structure.
There is nothing physics/metaphysics about this. If you don’t understand the terms, don’t pretend you do and write slop as a comment, it is really not that different from using LLM to generate slop.
The parent comment is not suggesting that Yon is about physics/metaphysics.
Understanding is important for readers. Demonstrating understanding is important for writers of both technical documentation and internet comments, and of critical importance in the era of AI.
What if it's pure nonsense, therefore impossible for anyone to understand. Does that mean all criticism is "slop" and nobody's allowed to comment on it?
"If you don’t understand the terms, don’t pretend you do"
The comment you're replying to explicitly says "This language looks interesting, but I don’t understand the concepts." so I'm not sure what you're trying to say. Their note about physics/metaphysics was about "someone [they] knew", not TFA.
I have a PhD in category theory and know what the Leech lattice is and I still don't understand what is going on here. What is the value of using the Leech lattice to store memory?
The documentation is a work of art. Every time I try to work out what just one of the unexplained ideas is, it just introduces new unexplained ideas. I don't know where these ideas came from, how they fit together, or why putting them together is useful. I certainly don't know why I would want to write a program in this language, as opposed to any other language I already know.
> Content addressing is extensionality made physical (chapter 11)
Actually, that's in chapter 12; 11 is the standard library. Maybe the LLM got confused because the chapters are 0-indexed.
I was curious about that topic but it seems over my head. I don't think it works outside of mathematics? In programming, one can have two objects that are identical in both structure and value but have different identities. It's why lisp has eq, eql, equal, etc. How'd you get around that other than adding an identity property?
Also:
> A handle, what your variables actually hold for strings, sections, lists, trees, is that slot index, carried as an f64
I don’t know if Yon does this (the documentation is gibberish) but it’s possible to use f64 NaNs to hold convenient metadata. I had a professor who wrote a bespoke teaching language (roughly based on Scheme) that did that.
As I understand it, content addressing function content is problematic because it does not actually "normalise" the content of functions into something interchangeable. A function of input A and output B with performance signature X can still be very different in terms of actual code, but the actual comparison between both is hard to specify.
I was exploring this as a means to solving the open source, or rather the github conundrum, the problem of sharing code socially is that we need a canonical source, and this is sociologically driven than performance driven, and as it turns out, have devastating consequences for FOSS funding. I wanted to explore sharing code "interchangeably" in some sense to avoid this problem, but ultimately this seems unsolveable, even with exploration by Unison etc.
As someone genuinely interested in programming language design, type theory, and category theory this sort of thing really saddens me. There is so much passion and rigor that has gone into developing these fields. Chucking all their jargon into an ai slop blender, imo, is actually incredibly disrespectful to those who have worked so hard.
Imagine someone honestly interested in learning about category theory but not yet knowing where to start. Projects like this only serve to muddy the waters obscuring paths to actual learning and giving the impression that the subject is a joke.
Honestly, as someone who has at least a moderate tolerance for PL jargon, most of this is completely impenetrable. It's like someone put the whole field of PL in an LLM-powered blender.
A few notes, because this is obviously vibe coded, and does not work in many ways.
1. Yon's documentation mentions "Homotopy type theory:"
> the runnable HoTT fragment is refl/pair/fst/snd
These are basic features of martin-lof type theory, not homotopy type theory. The documentation makes no reference of an interval type, which is generally the way to go for decidable type-checking in HoTT without univalence as an opaque axiom.
Pi types are mentioned, but Yon does not have dependent types. From what I can tell, they are polymorphic, maybe even just simply-typed (except for identity types under Pi). See here in the repo: https://github.com/yon-language/yon/blob/523e363a4a00e8da1410a2521b1d7d1309d360ce/frontend/ast.ml#L37
The datatype Ty only refers to other Ty's. Thus, it is not dependent. Terms cannot appear in types. Pi is explicitly indexed by a type defining its domain and codomain. A pi type is not a pi type if its codomain cannot depend on its domain.
2. Normalization can fail in Yon.
Yon's docs say that its universe of propositions has booleans (https://yon-lang.org/book/heyting-core?_highlight=prop). It also says its logic is intuitionistic (AKA, constructive). However, it also says the logical connectives on booleans are CLASSICAL. This implies law of excluded middle, which is NOT constructive without careful sandboxing (e.g., Linear logic).
Yon dangerously allows propositions to be lifted to booleans. If I am interpreting correctly (docs are very vague), this means propositions can be lifted to terms. This causes an obvious failure of normalization due to assumed proof irrelevance (otherwise Prop would not be distinguished) (also see Coquand's paper on this https://arxiv.org/abs/1911.08174).
3. Yon's type definitional equality does not actually reduce types.
See here. This is the function used by the type-checker to check if types are equal. https://github.com/yon-language/yon/blob/523e363a4a00e8da141...
No reduction actually occurs, conveniently because none of the types actually contain terms (that is, it is simply typed).
Yon claims to be dependently-typed. See this in the repo: https://github.com/yon-language/yon/blob/523e363a4a00e8da1410a2521b1d7d1309d360ce/frontend/ast.ml#L21
> Types in Yon Core kernel — the small dependent type theory used for the operational semantics.
Suppose I'm reading the source code wrong. Conveniently, the comment one line below reveals, once again, that the "type theory" is simply-typed:
> * T, U ::= Type_n universe of level n
> * | Pi(x:T). U dependent function
Pi types eliminate into a FIXED type that does not depend on x. This means there is also no purpose for having a universe hierarchy.
To confirm, I scoured the docs a bit for any examples using Pi types or Sigma types. I searched the docs, and could not find any, besides this example:
> world W { Code is X }
> place Account in W { balance number }
> fun takes_sub(s: { a : Account where Pi(x: Account). Pi(y: Account). Id(Account, x, y) }): number { return 0 }
> fun main(): number { return 0 }
Notably, the identity is the only constructor for Ty indexed by a term. That is, Pi types can ONLY eliminate into the identity. What if I want my Pi type to eliminate into anything else living in Prop? e.g., an existential like \forall (x : Nat), \exists (y : Nat), x < y. Unfortunately impossible in Yon.
This project is clearly produced by AI, and clearly dangerously incorrect. Do not use this for anything serious.
As a mathematician, this reads to me as the most informed comment.
Various priors inoculate me from feeling some of the rejection expressed in other comments. I knew Sammy Eilenberg, perhaps the most famous mathematician to work at Columbia University. He hired me. With friends, I ran into him one night out in NYC, and in his 70's we all stayed out past dawn. His late career focused on topos theory, and everyone in the building politely rolled their eyes. Those are working mathematicians having an understandable reaction; most reactions to topos theory here are simply uninformed. The evolution of programming languages has lead from the lambda calculus to many forms of category theory. Topos theory would not be a surprise.
The Leech lattice? Could be a brilliant idea. Compare Lenstra's elliptic curve factorization algorithm. Sometimes famous landmarks in mathematics have remarkable properties; mining them for algorithmic advantage is no different than mining asteroids for rare metals.
The involvement of AI is most problematic. Mathematics fears being swamped by mediocre AI-authored papers, but the truth is "publish or perish" has long lead to mathematics being swamped by mediocre papers. Bad artists are losing jobs, but good artists are working faster.
I welcome a new era of programming language design, where AI makes rapid prototyping a reality. We just have to take sharing this work with a grain of salt. Stop reading when you lose interest, but welcome the churn!
Rapid prototyping was always possible in PL design. It was very possible to go from idea to a working proof of concept language with a couple weeks' work. There are thousands of POC projects like this that popped up before LLMs existed.
What LLMs are doing now is allowing people to take prototypes and to publish them with an entire 200 page book no one (not even the author) has read, and a polished-looking website filled with marketing verbiage and a cute logo.
What would be interesting to me would be to see the process of rapidly refining the design, but I keep checking back on these "Here's my exciting new 400kLOC LLM language project I made in 3 weeks" and they all seem to die very shortly after the splashy announcements a few weeks later, as the author seemingly lost interest.
Which is not surprising because that's the way it always went with little languages -- writing a language has always been a marathon, not a sprint. It's just before, a 200 page book was an indicator of author dedication. Now, a 200 page book is just more bytes for digital kindling.
Yeah, early on in my evaluation of this thing was to check out the contributors and their work. Was expecting this to be the product
of at least a small group. Imagine my surprise to see… one person…
I really appreciate this comment. It is easy to dismiss something as AI slop when it looks and smells like AI slop, but pinpointing actual errors is much more valuable. As solomonb said in a sibling comment, "Imagine someone honestly interested in learning about category theory".
You must not mix up technical mathematical words with softer prose words. For instance, "Yon's data model is categorical. A world is a category, a semantic site;"
So if you want to define a world, I expect you to tell me how to supply objects + morphisms + the composition law + the site structure. I don't know what a "semantic site" is, just what a "site" is. You'd need to define it. Anyway, we then get to our first examples of declaring worlds:
world Currency { Code is EUR, USD }
world Status { State is on, off }
This maybe gives me the first bit of data we need for a site. Definitely not the rest. Then we hit this
world Sub subset of Currency
Two issues with this. One is stylistic. Why on earth would you call it a "subset"? It's not a set! "subworld" is the obvious choice... But the real issue is that like the initial definition, this doesn't tell me how to build `Sub`. I need to know which objects and morphisms of Currency to include into the category Sub? What's the site structure?
So now I think, "OK, maybe you just declare part of the structure and fill it in later, before you actually use it..."
But then your example disproves that notion! You have
world Shop { Code is X }
place Account in Shop {
balance number
owner String
}
with no mention of Account when you declared Shop, I'm still not sure what Code or X are, and then you give what is seemingly supposed to be some working code
fun main(): number {
be a holds new Account { balance 40 owner "ada" }
be _p holds String.print(a.owner)
return a.balance + 2
}
So your motivating example really kills off the interest from your two main communities that would use this thing: 1) category theorists have no idea what you're talking about, because nothing here looks like categories - there are no morphisms, no site structure 2) computer/software folks look at your example and think "why on earth would I learn topos theory to do something that sure looks like OOP"
I think a "topos inspired programming language" would be kind of cool if you could pull it off, but I think you really need to figure out how to sell it in the docs to at least one of the two communities above.
Could you name a few languages you had in mind while developing this, their respective problems, and how your language improves them, feature by feature?
> Yon allocates into xleech2, a content-addressed heap whose geometry is the Leech lattice Λ24: exactly 196,560 slots per heap.
What is the computational complexity of memory allocation into this Leech lattice? What applications did you have in mind where making allocation a maths problem in order to save time on comparisons makes sense? What is going to happen when a program exhausts your little heap?
I have trouble with the idea that these lattice structures could be less computationally complex or less likely to collide than a good simple hash table. I guess they could be more guaranteed to have stable access times?
The more I try to understand, the more it appears that they are a hash table (hash-addressed-structure to be pedantic), but with way more complicated backing than a hash table.
It's such a weird mixture of poetry and math that it's hard to tell what's going on. I suspect the author does not speak English as a first language (or at all?) and has used an LLM to generate this stuff.
I'm not sure where or how to convey this, because I've seen several of these languages designed with AI, documentation created using AI, etc -- posted on Hacker News in the last months or so, and I've responded to each one with roughly the same feedback (and I'm assuming good faith: that the intent is that the poster wishes to grow as a language designer).
Your audience, or whoever you aim your work at, should be treated with respect. Otherwise, why should they give you the time of day? Why would you expect them to respond positively to effort alone when effort (in code and in shit prose) is extremely cheap right now? Their time is not cheap ...
When I read the documentation, and it is extremely clear that you haven't taken the time to clarify your ideas, when much of it is LLM prose, when much of the content introduces highfalutin ideas without motivation, blending categorical concepts (which, by the way, should never be mixed with vague prose claims about the language), violating my reader context model, preventing me from understanding what problem exactly your language design is solving (where is that problem stated clearly?), it is a waste of my time.
> The work took 3 weeks in total ... it's worth a look, and I hope it will win some converts, and that someone will want to help me with its development.
You've gone too fast, too much is vague, nothing is clear.
I'd delete everything, start over, and try and explain just one of the ideas clearly. Seriously. This sounds harsh, but it's honestly the correct approach to something as subtle and nuanced as programming language design.
This reads to me like someone's mania project. I wish OP the best and hope they can get some rest.
> Your audience, or whoever you aim your work at, should be treated with respect.
I just want to amplify this point. As I was reading this, the LLMisms kept jumping out at me and each one felt like the author looking at me and deciding that my time spent reading this prose wasn't actually worth anything to them.
OP: I want YOUR thoughts, not the next token predictions of a gigantic pile of matrix multiplications. I want your awkward sentences, grammar mistakes, half-baked thoughts, self-doubt, silly jokes. I don't want this pile of grandiose mechanical slop completely devoid of humanity.
Personally I don't want to read the codebase AND book of someone 3 weeks into a mania focused on a subject it is unclear they have any prior experience with. Its disrespectful for someone to think they can produce something worthy of consuming another human's time under those constraints.
I have to second this. I find the AI written documentation extremely loathsome, hard to read, and somehow both pretentious and lazy.
Please, I beg everyone, stop posting AI slop.
Regrettably, the beatings are going to continue until morale improves.
This isn’t about whether the writer uses LLM or not at all, nor is it about respect. The core novelty it tries to introduce is not hard to understand (even if it is not really that novel). If you don’t want to spend time thinking about what interesting idea it is exploring, that is fine, but pretending or insinuating that it is a LLM problem is just lazy.
Explain away then my friend: surely your clear explanation will benefit many other readers who came away with similar confusion?
What is the core novelty?
Just a comment: this sounds a lot like when someone I knew mildly succumbed to AI psychosis, and thought he, with Gemini, had made some physics/metaphysics breakthrough. If you’re losing sleep and feeling distressed or euphoric, maybe lay off for a few days, no matter how hard that is. Talk to friends and/or family about unimportant things. Get outside for a while. Go back to old hobbies (reading, hiking, just going to coffee shops or thrift stores - whatever) and then reassess.
This language looks interesting, but I don’t understand the concepts. Does this stuff make sense to other people?
The heap is content-addressed over Λ₂₄: every value is mapped to a lattice point and canonicalized under the Conway group Co₀ (via libmmgroup), so the same content always lives at the same address.
What is ‘Λ₂₄’? What is a ‘lattice point’?
giving up the GC stopped being a renunciation, since cells are immutable and content-addressed, so there is nothing to trace and nothing to move
This kind of sounds like you’re saying that there’s nothing to free, which implies that nothing takes up memory, which I presume is not the case. Do you mean everything is immutable and content-addressed (like Git)? Doesn’t stuff still need to be freed somehow when the programs done with it, otherwise memory will grow for ever?
Agreed. Everything is a weird mixture of poetry and mathematics jargon. Basically every page of the book contains some esotericism which makes empty claims. It's completely divorced from reality.
> Does this stuff make sense to other people?
Nope, and I actually learned about application of category theory to programming language in university.
I tried to get an idea about the main points, and then stumbled over
> a thing is what you can observe of it. > > [...] > > Content addressing is extensionality made physical (chapter 11): two values indistinguishable by observation are not merely equal, they are the same slot
That only works in a category because you have enough (a countably or uncountably infinite number) functions that you can compose and "test" so you don't need (or don't care) about the "value" itself.
But on a real computer that doesn't work, because you can't go beyond a countable number, and even then you run into the halting problem pretty soon. So equality in this model is not computable. Which is sort of bad if you want to somehow store values "in the same slot" just based on observability. It might work for string literals, and even for concatenated strings, but not in general.
Picking some random lattice (a lattice is a partially ordered structure with some extra conditions) as a base of addressing doesn't help...
So yes, crackpot AI slop. The words sort of make sense, but there's nothing solid behind it, and as soon as you look at details it falls apart.
I didn't even get that far; I found the syntax annoying.
https://en.wikipedia.org/wiki/Leech_lattice
Maybe I just don’t have the mathematics knowledge to understand it, but that doesn’t really tell me how you could represent one in memory, or use one as a backing store for a hash-addressed data structure.
There is nothing physics/metaphysics about this. If you don’t understand the terms, don’t pretend you do and write slop as a comment, it is really not that different from using LLM to generate slop.
The parent comment is not suggesting that Yon is about physics/metaphysics.
Understanding is important for readers. Demonstrating understanding is important for writers of both technical documentation and internet comments, and of critical importance in the era of AI.
What if it's pure nonsense, therefore impossible for anyone to understand. Does that mean all criticism is "slop" and nobody's allowed to comment on it?
"If you don’t understand the terms, don’t pretend you do"
The comment you're replying to explicitly says "This language looks interesting, but I don’t understand the concepts." so I'm not sure what you're trying to say. Their note about physics/metaphysics was about "someone [they] knew", not TFA.
I have a PhD in category theory and know what the Leech lattice is and I still don't understand what is going on here. What is the value of using the Leech lattice to store memory?
The documentation is a work of art. Every time I try to work out what just one of the unexplained ideas is, it just introduces new unexplained ideas. I don't know where these ideas came from, how they fit together, or why putting them together is useful. I certainly don't know why I would want to write a program in this language, as opposed to any other language I already know.
Sibling comment suggests maybe it’s AI psychosis and that would clarify a lot.
Reminds me a lot of Urbit docs in that sense.
> Content addressing is extensionality made physical (chapter 11)
Actually, that's in chapter 12; 11 is the standard library. Maybe the LLM got confused because the chapters are 0-indexed.
I was curious about that topic but it seems over my head. I don't think it works outside of mathematics? In programming, one can have two objects that are identical in both structure and value but have different identities. It's why lisp has eq, eql, equal, etc. How'd you get around that other than adding an identity property?
Also:
> A handle, what your variables actually hold for strings, sections, lists, trees, is that slot index, carried as an f64
Why does the handle need floating point?
> Why does the handle need floating point?
I don’t know if Yon does this (the documentation is gibberish) but it’s possible to use f64 NaNs to hold convenient metadata. I had a professor who wrote a bespoke teaching language (roughly based on Scheme) that did that.
Here's an implementation of such: https://docs.rs/nanval/latest/nanval/
I noticed since 5.5 GPT has been adding "lattice" to a lot of things. Not sure if it is the new Gremlins.
I'm starting to think AI was a bad idea.
As I understand it, content addressing function content is problematic because it does not actually "normalise" the content of functions into something interchangeable. A function of input A and output B with performance signature X can still be very different in terms of actual code, but the actual comparison between both is hard to specify.
I was exploring this as a means to solving the open source, or rather the github conundrum, the problem of sharing code socially is that we need a canonical source, and this is sociologically driven than performance driven, and as it turns out, have devastating consequences for FOSS funding. I wanted to explore sharing code "interchangeably" in some sense to avoid this problem, but ultimately this seems unsolveable, even with exploration by Unison etc.
As someone genuinely interested in programming language design, type theory, and category theory this sort of thing really saddens me. There is so much passion and rigor that has gone into developing these fields. Chucking all their jargon into an ai slop blender, imo, is actually incredibly disrespectful to those who have worked so hard.
Imagine someone honestly interested in learning about category theory but not yet knowing where to start. Projects like this only serve to muddy the waters obscuring paths to actual learning and giving the impression that the subject is a joke.
Advanced AI psychosis.
Professional help might be necessary.
Honestly, as someone who has at least a moderate tolerance for PL jargon, most of this is completely impenetrable. It's like someone put the whole field of PL in an LLM-powered blender.
> No garbage collector
> Slots are stable for the life of the process; the heap grows with distinct content only.
So how is a program supposed to handle lots of unique content? Like a web server handling user requests?
I apologize, you’re absolutely right!
Taking it at face value, you'd spawn a subprocess to handle each web request and exit once it's done.
A few notes, because this is obviously vibe coded, and does not work in many ways.
1. Yon's documentation mentions "Homotopy type theory:"
2. Normalization can fail in Yon. Yon's docs say that its universe of propositions has booleans (https://yon-lang.org/book/heyting-core?_highlight=prop). It also says its logic is intuitionistic (AKA, constructive). However, it also says the logical connectives on booleans are CLASSICAL. This implies law of excluded middle, which is NOT constructive without careful sandboxing (e.g., Linear logic). 3. Yon's type definitional equality does not actually reduce types. See here. This is the function used by the type-checker to check if types are equal. https://github.com/yon-language/yon/blob/523e363a4a00e8da141... No reduction actually occurs, conveniently because none of the types actually contain terms (that is, it is simply typed). > world W { Code is X }> place Account in W { balance number }
> fun takes_sub(s: { a : Account where Pi(x: Account). Pi(y: Account). Id(Account, x, y) }): number { return 0 }
> fun main(): number { return 0 }
Notably, the identity is the only constructor for Ty indexed by a term. That is, Pi types can ONLY eliminate into the identity. What if I want my Pi type to eliminate into anything else living in Prop? e.g., an existential like \forall (x : Nat), \exists (y : Nat), x < y. Unfortunately impossible in Yon.
This project is clearly produced by AI, and clearly dangerously incorrect. Do not use this for anything serious.
As a mathematician, this reads to me as the most informed comment.
Various priors inoculate me from feeling some of the rejection expressed in other comments. I knew Sammy Eilenberg, perhaps the most famous mathematician to work at Columbia University. He hired me. With friends, I ran into him one night out in NYC, and in his 70's we all stayed out past dawn. His late career focused on topos theory, and everyone in the building politely rolled their eyes. Those are working mathematicians having an understandable reaction; most reactions to topos theory here are simply uninformed. The evolution of programming languages has lead from the lambda calculus to many forms of category theory. Topos theory would not be a surprise.
The Leech lattice? Could be a brilliant idea. Compare Lenstra's elliptic curve factorization algorithm. Sometimes famous landmarks in mathematics have remarkable properties; mining them for algorithmic advantage is no different than mining asteroids for rare metals.
The involvement of AI is most problematic. Mathematics fears being swamped by mediocre AI-authored papers, but the truth is "publish or perish" has long lead to mathematics being swamped by mediocre papers. Bad artists are losing jobs, but good artists are working faster.
I welcome a new era of programming language design, where AI makes rapid prototyping a reality. We just have to take sharing this work with a grain of salt. Stop reading when you lose interest, but welcome the churn!
Rapid prototyping was always possible in PL design. It was very possible to go from idea to a working proof of concept language with a couple weeks' work. There are thousands of POC projects like this that popped up before LLMs existed.
What LLMs are doing now is allowing people to take prototypes and to publish them with an entire 200 page book no one (not even the author) has read, and a polished-looking website filled with marketing verbiage and a cute logo.
What would be interesting to me would be to see the process of rapidly refining the design, but I keep checking back on these "Here's my exciting new 400kLOC LLM language project I made in 3 weeks" and they all seem to die very shortly after the splashy announcements a few weeks later, as the author seemingly lost interest.
Which is not surprising because that's the way it always went with little languages -- writing a language has always been a marathon, not a sprint. It's just before, a 200 page book was an indicator of author dedication. Now, a 200 page book is just more bytes for digital kindling.
Yeah, early on in my evaluation of this thing was to check out the contributors and their work. Was expecting this to be the product of at least a small group. Imagine my surprise to see… one person…
How does `refl` work if its not even dependently typed?
I really appreciate this comment. It is easy to dismiss something as AI slop when it looks and smells like AI slop, but pinpointing actual errors is much more valuable. As solomonb said in a sibling comment, "Imagine someone honestly interested in learning about category theory".
You must not mix up technical mathematical words with softer prose words. For instance, "Yon's data model is categorical. A world is a category, a semantic site;"
So if you want to define a world, I expect you to tell me how to supply objects + morphisms + the composition law + the site structure. I don't know what a "semantic site" is, just what a "site" is. You'd need to define it. Anyway, we then get to our first examples of declaring worlds:
This maybe gives me the first bit of data we need for a site. Definitely not the rest. Then we hit this Two issues with this. One is stylistic. Why on earth would you call it a "subset"? It's not a set! "subworld" is the obvious choice... But the real issue is that like the initial definition, this doesn't tell me how to build `Sub`. I need to know which objects and morphisms of Currency to include into the category Sub? What's the site structure?So now I think, "OK, maybe you just declare part of the structure and fill it in later, before you actually use it..."
But then your example disproves that notion! You have
with no mention of Account when you declared Shop, I'm still not sure what Code or X are, and then you give what is seemingly supposed to be some working code So your motivating example really kills off the interest from your two main communities that would use this thing: 1) category theorists have no idea what you're talking about, because nothing here looks like categories - there are no morphisms, no site structure 2) computer/software folks look at your example and think "why on earth would I learn topos theory to do something that sure looks like OOP"I think a "topos inspired programming language" would be kind of cool if you could pull it off, but I think you really need to figure out how to sell it in the docs to at least one of the two communities above.
Hmm. Only responder taking this seriously and the account is created minutes ago.
I took it seriously in so far as I made a good faith attempt to understand a piece of it and wrote something about why I failed...
Can't help I've just been a HN lurker so far :)
Could you name a few languages you had in mind while developing this, their respective problems, and how your language improves them, feature by feature?
> Yon allocates into xleech2, a content-addressed heap whose geometry is the Leech lattice Λ24: exactly 196,560 slots per heap.
What is the computational complexity of memory allocation into this Leech lattice? What applications did you have in mind where making allocation a maths problem in order to save time on comparisons makes sense? What is going to happen when a program exhausts your little heap?
I have trouble with the idea that these lattice structures could be less computationally complex or less likely to collide than a good simple hash table. I guess they could be more guaranteed to have stable access times?
The more I try to understand, the more it appears that they are a hash table (hash-addressed-structure to be pedantic), but with way more complicated backing than a hash table.
I found this page, https://yon-lang.org/book/coming-from
It's such a weird mixture of poetry and math that it's hard to tell what's going on. I suspect the author does not speak English as a first language (or at all?) and has used an LLM to generate this stuff.
The buzzwords are strong in this one.
this has templeOS vibes
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