MurphyA/hacker-news huggingface dataset:
by AnthonyMouse | 2025-08-21 19:31:34+00:00
> you just need to make a choice.

This fallacy is at the heart of the failure of modern software.

Making things work for the median user is almost entirely about defaults and intuitiveness. If everybody is sending messages all the time, there should be a conspicuous button for sending messages.

Making things work for power users is about allowing those defaults to be changed. It's fine if this is five deep in a menu somewhere. It's fine if there is an option for "advanced mode" that opens up a bunch of menus that are otherwise hidden. It's fine if this requires you to write your own filter rules etc., as long as that's available. What's not fine is to make the limited interface the only interface.

Simple things should be easy and complex things should be possible.
by PaulDavisThe1st | 2025-08-21 19:31:45+00:00
> Tragedy of the commons.

No, because there is no such thing, at least not as understood by Garrett Hardin, who put forward the phrase.

Commons fail when selfish, greedy people subvert or destroy the governance structures that help control them. If those governance structures exist (and they do for all historical commons) and continue to exist, the commons suffers no tragedy.

This recent slide deck talks about Ostrom's ideas on this, which even Hardin eventually conceded were correct, and that his diagnosis of a "tragedy of the commons" does not actually describe the historical processes by which commons are abused.

https://dougwebb.site/slides/commons

That said ... arguably there is a problem here with a "commons" that does in fact lack any real governance structure.
by raincole | 2025-08-21 19:31:46+00:00
When one side has much more "scalability" than the other, then the other side has very strong motivation to match up.

- People use AI to write cover letters. If the companies don't filter out them automatically, they're screwed.

- Companies use AI to interview candidates. No one wants to spend their personal time talking to a robot. So the candidates start using AI to take interviews for them.

etc.

If you don't at least tell yourself that you don't allow AI PRs (even just as a white lie) you'll one day use AI to review PRs.
by underlipton | 2025-08-21 19:32:06+00:00
Yeah, none of it really works anymore. I'm at the point where my desired approach is, "Give everything away and people be f*cking adults about only taking what's needed, and good stewards of what's taken." It's obvious that all of the socioeconomic guardrails do exactly zero, because downstream of "rich people doing whatever the f*ck they want" is "poor people also doing whatever the f*ck they want, just more desperately". Let there be chaos for a moment, and when everyone realizes that shortages and waste suck, we'll self-organize a better protocol. But these thousand bandages over the festering wound of a culture with a completely disordered relationship to goods can't keep it all together but for so long.
by reactordev | 2025-08-21 19:32:09+00:00
It's all a feedback loop...

Crazy things can be done once you learn it though. It's just math underneath. You don't need to know the math per se but understand what's going on under the hood, what is "world coordinates" vs "local coordinates" vs "device normal coordinates". What is a material, a texture, a light source (how many can I use at once in a single pass?), what is a pass?, what is culling, what is a face, index, weight, or bone? All 3d programs, whether it's 3DS Max, Maya, Blender, Unity, Unreal, Three.js, all share a pretty similar concept of these things. Some abstract it further into just a buffer (vulkan, metal, wgpu) that you can do with as you please on the gpu side.

I had some fun just the other day making earth (again) in three.js (https://gabereiser.github.io/earth) with physically accurate shaders. Once you learn, it's actually really fun.
by devmor | 2025-08-21 19:32:21+00:00
> That’s true, but why should I take on the work of being at the beginning of the pipeline instead of hiring a mid level developer.

Nominally, for the same reason that you pay taxes for upkeep on the roads and power lines. Because everyone capable needs to contribute to the infrastructure or it will degrade and eventually fail.

> My incentives are to meet my quarterly goals and show “impact”.

To me, that speaks of mismanagement - a poorly run company that is a leech on the economy and workforce. In contrast, as a senior level engineer at a large technology company that has remarkably low turnover, one of my core duties is to help enhance the capabilities of other coworkers and that includes mentorship. This is because our leadership understands that it adds workforce retention value.

> To a first approximation, no company pays internal employees at market rates in an increasing comp environment after a couple of years especially during the first few years of an employee’s career where their marker rate rapidly increases once they get real world experience.

That's why I mentioned it being a cross-industry symbiotic relationship. Your company may not retain the juniors that you help train, but the mid level engineers you hire are the juniors that someone else helped train. If you risk not mentoring juniors, you encourage other companies to do the same and reduce the pool of qualified mid level engineers available to you in the future.

> On the other hand, the startup I worked for pre-AWS with 60 people couldn’t, wouldn’t and shouldn’t have paid me the amount I made when I got hired at AWS.

While unrelated to my point, I do have a different experience that you may find interesting in that the most exorbitant salary I have ever been paid was as a contractor for a 12-person startup, not at the organizations with development teams in the hundreds or thousands.
by jug | 2025-08-21 19:32:27+00:00
Yeah, it truly IS transformative for industries, no denying anymore at this point. What we have will remain even after a pop. But I think AI was special in how there were massive improvements the more compute you threw at it for years. But then we ran out of training material and suddenly things got much harder. It’s this ramping up of investments to spearhead transformative tech and suddenly someone turns off the tap that makes this so conflicted. I think.
by mothballed | 2025-08-21 19:33:05+00:00
There's definitely a rural element to it. I left probably $10,000 worth of construction equipment out for the stealing for 2 years while building my house in the country. Just totally unmonitored vacant property, surrounded by poor people in trailers who badly could have used the money if they cared to steal it. Of course neighbors would never think to steal it because burning your name in a small town is the same thing as banishment or starving to death because you'll never get another job / lover / friend / help.

It would have been gone in 15 minutes at my house in the city.
by andrew_lettuce | 2025-08-21 19:34:12+00:00
Most of the companies where I've had first hand experience test customer experience in the aggregate, ie NPS and similar. Part of this is scale, but a big part is also CS is viewed as a cost center and it's a rare individual who does what you're suggesting. There's also seldom any sorry if pay off for making that one customer incredibly happy, CS people are not usually tested very well by anyone
by deegles | 2025-08-21 19:34:37+00:00
> We're clearly seeing what AI will eventually be able to do

Are we though? Aside from a narrow set of tasks like translation, grammar, and tone-shifting, LLMs are a dead end. Code generation sucks. Agents suck. They still hallucinate. If you wouldn't trust its medical advice without review from an actual doctor, why would you trust its advice on anything else?

Also, the companies trying to "fix" issues with LLMs with more training data will just rediscover the "long-tail" problem... there is an infinite number of new things that need to be put into the dataset, and that's just going to reduce the quality of responses.

For example: the "there are three 'b's in blueberry" problem was caused by so much training data in response to "there are two r's in strawberry". it's a systemic issue. no amount of data will solve it because LLMs will -never- be sentient.

Finally, I'm convinced that any AI company promising they are on the path to General AI should be sued for fraud. LLMs are not it.
by Nadya | 2025-08-21 19:34:44+00:00
If a user holds an ice cream cone upside-down and their ice cream falls to the floor, do you blame the user for not holding their ice cream cone upright or the creator of the ice cream cone for a stupid design that allows the ice cream to so easily fall out of the ice cream holding device and onto the floor?

I find far more often that bad UX is the result of someone trying to use a tool for something it wasn't designed for. They might even clob several different tools together in an unholy abomination to get it to do what they actually want instead of having a tool built to do precisely what they want (and once that tool has been built - people will inevitably misuse it to do things other than what it was designed for and then complain about its poor UX for doing those things).
by Al-Khwarizmi | 2025-08-21 19:34:55+00:00
I was quite successful learning Mandarin by using Anki in the way that is typically discouraged, i.e., with a downloaded deck (SpoonFedChinese). I have very little time per day to devote to learning so building my own cars isn't an option, but with this and a couple of last-minute classes I went from HSK2 to HSK3.

I also find Du Chinese and The Chairman's Bao quite useful, although indeed for the writing, nothing seems to substitute actually writing. Right now I can read much more Mandarin than I can write.
by tucnak | 2025-08-21 19:35:01+00:00
> Is the borrow checker a pain in the ass? Yeah. But is it necessary?

You've missed the primary point of the post entirely. Borrow checker per se is not the problem; it's the sheer amount of everything. There's multiple ideas of perfection. Those of us to have very much enjoyed ostensibly imperfect Rust of 2018 find this particular, current flavour unappealing. It may as well be capable tool in deft hand, however, as-is the case with everything in life, you cannot help but ask yourself THE question; is it worth my effort? For me personally, if I were looking for better C/C++ in 2025, I would choose Zig before Rust any day of the week (one exception being Postgres stuff, pgrx ecosystem that is really special!)

But then again, anything beats writing C for a living.
by blaufuchs | 2025-08-21 19:35:06+00:00
> Will it lighten maintainer load?

Yes that is the stated purpose, did you read the linked GitHub comment? The author lays out their points pretty well, you sound unreasonably upset about this. Are you submitting a lot of AI slop PRs or something?

P.S Talking. Like. This. Is. Really. Ineffective. It. Makes. Me. Just. Want. To. Disregard. Your. Point. Out. Of. Hand.
by otterley | 2025-08-21 19:35:22+00:00
> I'm a one man band who wants to be scalable, but doesn't want to get married to a particular cloud.

(AWS employee, but opinions are my own)

Just pick a cloud provider and move on. All of the top-tier providers can scale. Choose the one you're most comfortable with and move on. Focus on the things that matter for your business like building the right product and getting customers. If you have regret later, it's going to be because you were so wildly successful that it is now an actual business risk and/or your customers demand it. But don't make this decision based on a problem you don't have and are unlikely to have in the next 12-24 months, if ever. Cloud agnosticism is rarely a functional or strategic requirement of any given business, and it's usually very expensive to implement--more than any savings you might achieve by pitting providers against each other (which you can't do anyway unless you are big enough to be a strategic customer).
by trod1234 | 2025-08-21 19:35:22+00:00
Up to the first or second chapter, depending on the book being used is more than sufficient to cover the foundational concepts. Sets, and Properties such as closure over given operations, and mathematical relabeling which is a function (f(x), the requirements for it (uniqueness of x, and projection onto) along with the tests for the presence of these, and common mathematic systems properties.

This naturally provides easily understood limitations of math systems which can be tested if there is a question, and allows recognition when they violate the properties that naturally lead to common mistakes, as well as providing a space where they can use numbers/geometry/reasoning at play.
by jauntywundrkind | 2025-08-21 19:35:33+00:00
(2012)

Amazing technique. Previous submissions, and another good one on load balancing via PoTRC

https://news.ycombinator.com/item?id=39283595 https://news.ycombinator.com/item?id=24877341 https://news.ycombinator.com/item?id=37143376
by hinkley | 2025-08-21 19:35:42+00:00
> I would think the engineers usually get their kick out of making things fast or easy to maintain

Is your company hiring? Because I've spent 30 years being this engineer and nearly everyone looks at me like I've got horns growing out of my head.

That's not where most engineers find their job satisfaction, more's the pity. And they think they know better than users. There's a reason UX has been around for at least four decades longer than DX. Developers think both are made up.
by glenstein | 2025-08-21 19:35:50+00:00
>But the other common denominator is Nguyen

You could say the same of James Randi. But the explanation in Randi's case was that he really was dealing with charlatans, mentalists, etc. I don't think there's enough signal just from Nguyen disagreeing to think that he is the common denominator, though it's possible and you're being thoughtfully tentative about the possibility.

I would also say that scientifically non-respectable theories finding big traction in the online influencer space is the norm, and not especially difficult to explain.
by mystraline | 2025-08-21 19:36:17+00:00
Doubly so since the 13th amendment enshrined slavery as a sole ownership by the state, if found guilty of a crime.

And who's the group who is overpoliced in this country? And who up-thread said to target black women? Yep.

The 13th amendment was terrible. It should have never had an exception for punishment for a crime. Instead, we have a states controlled slave state.
by qoez | 2025-08-21 19:36:29+00:00
The motivation of getting attention about the problems he believes exists in institutions (eg lack of heterodox thinking) doesn't seem like a grift to me (how broad does that definition get to be before it's just "they're doing stuff I don't like"). It seems more like he wants heterodox thinking to be able to flourish within the academics and is fighting for that, nothing grift-y about that.

> obscurantist

Nothing he says sounds obscure or hard to decipher in my reading, I never get the people who make this critique (other than try harder to decipher it, he's just using a lot of extra words/high vocabulary to be very clear about what he's saying in a compact way in order to not be misinterpreted).
by timr | 2025-08-21 19:36:46+00:00
> Interestingly, that's the "trick" behind a lot of the seemingly magic skill of geo guessers. The best players have played so much, that they now "see" things that a regular person wouldn't even consider to look for, like the camera quality, what year the car was from, and so they narrow down the possible countries by those aspects, before even looking at the "picture".

Slightly OT, but this happens constantly with ML classifiers on any highly multi-dimensional problem. At first it seems like magic, and then someone digs into the principal components of the prediction, and finds a mixture of a few highly specific factors that -- in the worst case -- is an artifact of the dataset itself (image blur or color bias, for example).

Also common is that the predictive factors aren't pathological -- they're just "boring" -- and therefore the performance of the model is dismissed by the practitioner ("oh, I'd have thought of that, since it's only using a few common traits that are well-understood.")
by ch4s3 | 2025-08-21 19:36:49+00:00
The app I work on is fairly highly modular, to the point that we split the app in half and unwinding the two halves of the code only took about 2 weeks.

> The LLM codebase 'navigation' becomes near-free with good naming and structure

I have not found this to be true. They seem to break badly if you have a lot of files with similar-ish names even if they're descriptive.
by DrewADesign | 2025-08-21 19:36:51+00:00
Maybe I’ve misunderstood this, so correct me if I’m wrong… do actual professional developers let enough code be generated to include entire libraries that handle things as important as authentication, and then build on top of it without making sure the previously generated code actually does what it’s supposed to? Just accept local PRs written by AI, with a very sternly worded “now you better not make any bullshit” system prompt? All this just in time to ramp up AI penetration tools. Jesus.

It’s kind of crazy to me how the cool kid take on software development, as recent as 3 years ago, was: strictly-typed everything, ‘real men’ don’t use garbage collection, everything must be optimized to death even when it isn’t really necessary, etc. and now it seems to be ‘you don’t seriously expect me to look at ‘every single line of code’ I submit, do you?’
by underlipton | 2025-08-21 19:37:01+00:00
Well, if you're actually paying for delivery. What's happening these days seems to be more of an offloading of that expense onto the deliverypeople. It "works" until a working vehicle becomes too expensive. Then, if you're lucky, you're paying the same amount to get your item in a week, when your house hits their algorithmically-generated route. Alternatively, deliveries could actually be priced marginally above cost (instead of below), and a lot of people can't afford it anymore. Good thing those retailers are still open. /s
by devmor | 2025-08-21 19:37:11+00:00
I'm right there with you, and having a similar experience at my day job. We are doing a bit of a "hack week" right now where we allow everyone in the org to experiment in groups with AI tools, especially those that don't regularly use them as part of their work - and we've seen mostly great applications of analytical approaches, guardrails and grounded generation.

It might just be my point of view, but I feel like there's been a sudden paradigm shift back to solid ML from the deluge of chatbot hype nonsense.
by guptadeepak | 2025-08-21 19:37:16+00:00
I wrote this piece after comparing different approaches to long-term memory in LLMs. Most current systems either rely on external vector databases or attempt to extend context windows, but both approaches hit scalability and efficiency bottlenecks.

MemGPT’s architecture stood out because it treats memory as a hierarchical resource: short-term scratchpad, mid-term recall buffer, and long-term persistent memory. This reduces redundant retrieval calls and improves coherence in multi-session tasks.

That raised a question for me: how do others see the trade-off between embedding-based search vs. structured memory hierarchies for scaling persistent AI agents?
by potato3732842 | 2025-08-21 19:37:42+00:00
At 7? Really? I was allowed to roam dilapidated industrial sites and ride my bike on the streets around at age 7-10 but I wasn't allowed anywhere near a 4-lane boulevard with high speed traffic like that. Heck, the highway I wasn't allowed to cross didn't even have four lanes.

There's a pretty big difference between random streets and a 4-lane arterial road like this one. I would take great care crossing it as an adult and I would only consider letting a kid cross it with explicit instructions to use a marked crossing or wait for traffic to stop for them and practice doing it accompanied.
by tracker1 | 2025-08-21 19:38:10+00:00
I didn't read the article as being particularly critical of Rust at all, only demonstrating that it has a lot of concepts that you need to know in a coupled way in order to do most functional things in the language. It just means it's a slightly harder language to learn.

I've experienced this myself when starting out and just wanting to make $THING in Rust. A lot of looking things up... then trying it out... then seeing the compiler errors.. then looking up WTF they mean when you don't have solid grasp on X, Y and Z in Rust. Then going down the rabbit hole of mut and clone in order to do what you want... often just cloning because it's easier, even if less performant, only later to understand (a)rc etc.

In another language, you may well get something to run, even if not correct, which can be far more satisfying to correct an incorrect behavior/bug then to have the compiler yelling at you from the start (slowly)... it's a slower and more painful feedback loop to work with. It isn't bad so much as different. That doesn't mean it isn't real, or that I or TFA are bashing Rust.
by ramesh31 | 2025-08-21 19:38:54+00:00
>Cash parked in money markets (which is just a click away) hasn't done that badly. Getting 4-5% has kept pace with inflation for the most part.

This sounds good on paper until you realize that inflation numbers like core CPI are tied almost entirely to consumptive costs. For anyone saving cash with the hope of buying assets like a home at some point, you're watching that move further and further away every day. So you're left to either deal with the stress of taking part in the madness of this market, or watch your chances of ever owning anything slip away.
by mvieira38 | 2025-08-21 19:39:05+00:00
Appropriate use of Anki isn't so simple, it's a skill in itself. Here's my strategy specifically to learn vocabulary. TL = target language, NL = native language.

1- front: image+subtitle (in TL) back: word in TL.

2- fill-in-the-blank phrases for the word, fully in TL, translation shows up after completion (you HAVE to use the function where you actually type it out)

3- front: word in TL back: translation in NL with an image, also the inverse, but the image is always in the back. Making it a different picture as the one for 1 is essential

So each new word would generate me about 6 to 8 new cards. At a fast enough rate of card creation, you won't run into the problem of memorizing each card because you will be creating like 100 cards in a day. The "fatal mistake" (to quote the author) of this article is underestimating how much this process of card creation and organization aids in learning. Creating your own study material IS studying in itself.

That is, assuming the strategy being compared to LLMs here is the correct one of actually studying the language and creating your own Anki deck while you study the material, instead of the incorrect strategy of downloading a deck
by kccoder | 2025-08-21 19:39:11+00:00
Sounds like a man in need of a real-life educational experience! Really show us how enjoyable the experience is. Perhaps they could have masked officials without identification round up other politicians with the slavery-wasn't-so-bad mindset, put them in chains without due process, and ship them to the areas of the country where the crops are rotting in the fields due to their immigration policy. At night they could be housed in Alligator Alcatraz / Speedway Slammer / Deportation Depot / Cornhusker Clink / ...
by leutersp | 2025-08-21 19:39:26+00:00
Chrome Dev console shows that the italics font is indeed named "dm" just like the rest of the content. It is not really a cursive, only a few letters are stylized ("f", "s" and "l").

It is possible (and often desirable) to use different WOFF fonts for italics, and they can look quite different from the standard font.