This was planned as a submission to the Gravity Research Foundation for 2027.
The Dirac Spinor equation is extremely standard, and GR would be the more famous one. The only "leap of faith" here is having the metric to be the functional of the matter wave, and not just the stress-energy tensor (which is the mainstream semi-classical approach).
Simply sharing here to prove authorship + sharing something interesting to HN.
edit: Though I note that I should have quoted Birkhoff's theorem instead, thanks for the pointer.
>> The demand for software most certainly has an upper limit.
> No, it does not. There is no ceiling for complexity.
There's an upper limit on everything. Maybe there's no ceiling on incidental complexity for s/ware development, but there sure as shit a ceiling on the essential complexity.
There are certainly limits to complexity people are willing to pay for. So if you are looking to make a living in development the fact that anyone will soon be able to do the basics and customise it for themselves is going to be a problem for you. Not directly, but because you'll be competing for fewer and fewer more interesting jobs that pay less and less over time (as development increasingly becomes a commodity task like waiting tables and stacking shelves), with the rest of us (maybe not me, I've already been unhappy in tech for years as remote work isn't good for my mental health, so I might bail early and beat the rush for those cushy table waiting jobs!).
You're assuming the current ensemble of commonly used software stacks is the most optimal there is. This assumption is simply wrong. Even looking at something simple like the office suite you can probably find countless areas where improvements can be made.
> You're assuming the current ensemble of commonly used software stacks is the most optimal there is.
No, I'm assuming that the level of practical complexity has a much lower bound than people seem to be trying to service, and that while that bound will grow with time it doesn't grow at the rate the available “solutions” do.
Exactly and this is true of many things. Much of the world is not zero sum, otherwise we'd have fallen into the "malthusian trap" several productivity booms ago.
We have thought that a few times with earlier technologies - a smaller chip requires less local reduction of entropy than a room sized computer. This may keep going for a long time yet.
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.
Understanding goes both ways. OP was just sharing something they thought was interesting. The Ted Chiang piece was horribly written logically and yet it was "written well" in prose. We should look past the writing and learn (if any) the interesting parts.
"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 indeed was insinuating that OP may be in the early stages of AI psychosis - or, if you don’t believe that’s a thing, at least in a mildly delusional or hyperactive state.
If I’m wrong, I don’t think any of the advice I gave was harmful. Really it’s good advice for anyone sunk deep into a problem to periodically take space, relax and recharge - and potentially allow their brain to work on it in the background while they do.
My questions came from a genuine place of wanting to understand the system though.
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?
This is multiple logical fallacies in one comment and definitely a comment I would mark in the "pure nonsense" bin. Not all criticism is slop, but anything ad hominem (personal attacks), argumentum ad populum (appeal to popularity), or argumentum ad verecundiam (appeal to authority) is not useful.
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.
Exploring if it makes sense to use maths (or, to be precise, this particular construction) to drive content addressable content + other exploration around the memory space. IMO, no.
Exploring if it makes sense to use maths (or, to be precise, this particular construction) to drive content addressable content + other exploration around the memory space. IMO, no.
I have a strong understanding of content addressing, memory allocation, data structures, and a superficial understanding of lattices. It is not clear how one has anything to do with the other. If there is any meaningful link or benefit, it has not been explained.
Perhaps some magical insight is waiting for me if I understand the Leech lattice better, but given PhD category theorists are also scratching their heads I think I'll pass https://news.ycombinator.com/item?id=48436251
Still writing the docs. Content addressing is the mechanism, that is: same content lands in the same slot, equality is a handle compare. The allocator is provably extensional so distinct content never aliases even though the hash itself can collide. The Leech part: the heap is sized to the lattice's 196,560 minimal vectors, the coordinate-to-slot map is a collision-free perfect hash built from the Conway group's mm_op tables, and that fixed universe is what makes sets into 196,560-bit bitmaps with O(1) membership and bitwise ops.
I understand that you can hash any object into a 196,560-slot space (that's how regular hash tables work), but I'm not sure why you'd want to do that. Regular hash tables can be resized when they get full (or less-full), yours cannot. How is this any different from a hash table with a fixed capacity of 196,560 entries?
"provably extensional" is not an established term in this context and communicates nothing about the design. I simply do not believe that this design doesn't have trivial collision issues, or that it makes efficient use of memory.
Are you saying that two distinct pieces of content can never collide? That seems obviously incorrect.
For example, take the integers 0 - 196,561, and put them into your lattice-based map. Something’s got to give. There are only 196,560 containers in the map (right?)
The only relation to the Leech group appears to be the number of slots.
When a table gets full they allocate a second one, and so on, up until 256 tables when allocations start silently failing (after exactly 50319104 allocations).
I hope OP is seriously considering what’s actually been built here, and how their interactions with whatever LLM they’ve been using really reflects that. I’m genuinely a bit concerned for them.
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.
The article is a farce. Is this really the sort of slop we want to use as a proof that humans write better articles than AI?
> "If a company builds a machine that, when fed descriptions of assorted ethical dilemmas, emits sentences either of the form “Compromise your values” or “Don’t compromise your values,” it is not building a tool that assists people in their decision making; it is encouraging people to stop making decisions. "
A human is not diminished by access to tools or other humans.
As much as we want to pretend that decision-making is what makes us human, the economy and governments are built on delegation. Choice paralysis is a thing.
There is so many logical fallacies in the article I don't even know where to begin.
1. For juniors, any sort of proof you have passion is enough.
2. Treat mid-levels as seniors.
3. Seniors have to show proof of passion (with longevity and intensity, AI and consultants exist for expertise and menial work) and competence (Take home problems with a long time scale with whatever tools they need. Use AI. I don't care, but be expected to be scrutinized for your design decisions, depth of exploration, and architectural write-ups.)
The Bar is also a not-great signal of actual ability. It is a great signal for 1) base knowledge and reasoning capacity and 2) sticktoitiveness / willingness to meet ~arbitrary expectations to work in a given industry ... which is all these 'technical' interviews are really measuring. By revealed preferences that's what management wants at those companies, so better to save people time and stress and make it a one time thing?
Proper bot operators already run long-lived sessions in order to avoid detection. So this inflicts additional financial penalities on basic bots (brute force) but not the more advanced ones, as they're already paying it.
Not all bots are bad, and the economic incentive of playing nice in a long lived session bot is much more stronger otherwise, which is kind of the point. It is the same with humans.
The Dirac Spinor equation is extremely standard, and GR would be the more famous one. The only "leap of faith" here is having the metric to be the functional of the matter wave, and not just the stress-energy tensor (which is the mainstream semi-classical approach).
Simply sharing here to prove authorship + sharing something interesting to HN.
edit: Though I note that I should have quoted Birkhoff's theorem instead, thanks for the pointer.
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