MurphyA/hacker-news huggingface dataset:
by miki123211 | 2025-08-22 01:05:42+00:00
For creative writing, you can do the same, you just use human verifiers rather than automatic ones.

LLMs have encountered the entire spectrum of qualities in its training data, from extremely poor writing and sloppy code, to absolute masterpieces. Part of what Reinforcement Learning techniques do is reinforcing the "produce things that are like the masterpieces" behavior while suppressing the "produce low-quality slop" one.

Because there are humans in the loop, this is hard to scale. I suspect that the propensity of LLMs for certain kinds of writing (bullet points, bolded text, conclusion) is a direct result of this. If you have to judge 200 LLM outputs per day, you prize different qualities than when you ask for just 3. "Does this look correct at a glance" is then a much more important quality.
by aprilthird2021 | 2025-08-22 01:05:42+00:00
> Of course nobody knows quite why directing more computation in this way makes them better, and nobody seems to take the reasoning trace too seriously as a record of what is happening. But it is clear that it works!

One thing it's hard to wrap my head around is that we are giving more and more trust to something we don't understand with the assumption (often unchecked) that it just works. Basically your refrain is used to justify all sorts of odd setup of AIs, agents, etc.
by tsuyoshi_k | 2025-08-22 01:06:56+00:00
1. A Gentle Operating System

I’ve been building OS Yamato, a poetic, lightweight web OS where data “blooms and withers” — inspired by nature’s rhythms.

Unlike conventional apps that hoard information endlessly, OS Yamato invites you to let go. Unless opened, data fades and disappears. This is not a bug — it’s a philosophy.

I’d love to hear your thoughts on this approach — technical or philosophical.

Try it: https://hanaco875.com Code: https://github.com/osyamato/os-yamato
by theshackleford | 2025-08-22 01:07:34+00:00
> I get that. But then if that option doesn't help, what I've seen is that the next followup is inevitably "have you tried doing/prompting x instead of y"

Maybe I’m misunderstanding, but it sounds like you’re framing a completely normal proces (try, fail, adjust) as if it’s unreasonable?

In reality, when something doesn’t work, it would seem to me that the obvious next step is to adapt and try again. This does not seem like a radical approach but instead seems to largely be how problem solving sort of works?

For example, when I was a kid trying to push start my motorcycle, it wouldn’t fire no matter what I did. Someone suggested a simple tweak, try a different gear. I did, and instantly the bike roared to life. What I was doing wasn’t wrong, it just needed a slight adjustment to get the result I was after.
by tsuyoshi_k | 2025-08-22 01:08:12+00:00
2. Why Let Data Disappear? •In a world obsessed with saving everything, we rarely ask: Should we? •OS Yamato embraces intentionality and impermanence. •Notes, messages, and journals start as , blossom into , and wither into if left untouched. •Reopening revives them — forgetting lets them go. •There’s no pressure to archive or manage an endless inbox.

This system is inspired by mujo (無常) — the Japanese philosophy that all things change and nothing is permanent.

⸻
by tsuyoshi_k | 2025-08-22 01:08:34+00:00
3. How It Works (Technical Highlights) • Each item (message, post, etc.) has a lastOpenedAt timestamp. • Scheduled jobs (or lazy rechecks) determine expiration. • Opening the item resets its lifespan. • Visual transitions (→→) are animated via CSS. • Data isn’t hard-deleted instantly — it’s softly marked, and revived through interaction. • Download is always available. Nothing is locked in.
by ux266478 | 2025-08-22 01:08:45+00:00
The point is that it's not about connection in the slightest. There's more to community than friendship.

> You like having middlemen?

Consider this, there still has to be someone to maintain that machine. What's the point then, exactly, except to pretend like the people around us don't exist? And just because they're not the closest people to us? I'm afraid I don't see the upside, actually.
by tsuyoshi_k | 2025-08-22 01:09:14+00:00
4. Philosophy & UX

Traditional operating systems emphasize archiving — keeping everything forever. OS Yamato flips that. It offers a seasonal, emotionally lighter, and more mindful digital space.

No addictive loops. No algorithmic feeds. Just calm tools for slow living.

⸻

A Personal Note

I’m not here to trap anyone in subscriptions. I don’t want you addicted to OS Yamato. I don’t want your data to sell ads.

I just want to build a gentle digital garden, where tech gives us space to breathe.

This is an early project, growing with every bit of feedback. Built solo, evolving daily.
by LargoLasskhyfv | 2025-08-22 01:09:15+00:00
Actually it wasn't about the hydrogen that much. More like the hull painted with flammable stuff. With todays materials it couldn't have burned like that. So any airship design of today NOT using hydrogen is wasting buoyancy, and a rare (on earth) element, which could be put to use for more important things.

Out of irrational fear...
by whatevertrevor | 2025-08-22 01:09:16+00:00
I agree with that.

I think part of the issue with the lack of "real" quantification in the results of LLMs is that the output and problem domain is so ill-defined. With standard neural nets (and other kinds of ML) classifiers, regression models and reinforcement models all had very narrow, domain specific problems they were solving. It was a no-brainer to measure directly how your vision classifier performs against a radiologist in determining whether an image corresponds to lung cancer.

Now we've opened up the output to a wide variety of open-ended domains: natural languages, programming languages, images and videos. Since the output domain is inherently subjective, it's hard to get a good handle on their usefulness, let alone getting people to agree on that. Hence the never-ending discourse around them.
by mattbee | 2025-08-22 01:09:35+00:00
LLMs can't count letters, their writing is boring, and you can trick them into talking gibberish. That is a long way off the Turing test, even if we were fooled for a couple of weeks in 2022.

IMO when people declare that LLMs "pass" at a particular skill, it's a sign that they don't have the taste or experience to judge that skill themselves. Or - when it's CEOs - they have an interest in devaluing it.

So yes if you're trying to fool an experienced open source maintainer with unrefined LLM-generated code, good luck (especially one who's said he doesn't want that).
by danielhanchen | 2025-08-22 01:09:37+00:00
Oh hey I'm assuming this is for conversion to GGUF after a finetune? If you need to quantize to GGUF Q4_K_M, we have to compile llama.cpp, hence apt-get and compiling llama.cpp within a Python shell.

There is a way to convert to Q8_0, BF16, F16 without compiling llama.cpp, and it's enabled if you use `FastModel` and not on `FastLanguageModel`

Essentially I try to do `sudo apt-get` if it fails then `apt-get` and if all fails, it just fails. We need `build-essential cmake curl libcurl4-openssl-dev`

See https://github.com/unslothai/unsloth-zoo/blob/main/unsloth_z...
by recursivecaveat | 2025-08-22 01:12:09+00:00
In general I recommend people stay away from static typing for a first language. I'm a static typing booster, but for beginners it is unnecessarily confusing.

Compiler errors are by nature often counterfactual: "compiler couldn't prove that this wasn't none" or "once you pass through this generic method it's no longer known that your list of Animal only contains members of Dog" is usually more confusing and less tractable than a concrete test case that craps out your program. Then you can start poking away with prints at the stacktrace.

If you step through every single line of your execution carefully and inspect all the data, you're virtually certain to unstick yourself. I can't say the same if you get some gobbledygook from the compiler.
by furyofantares | 2025-08-22 01:12:25+00:00
Something I've experienced with multiple new model releases is plugging them into my app makes my app worse. Then I do a bunch of work on prompts and now my app is better than ever. And it's not like the prompts are just better and make the old model work better too - usually the new prompts make the old model worse or there isn't any change.

So it makes sense to me that you should try until you get the results you want (or fail to do so). And it makes sense to ask people what they've tried. I haven't done the work yet to try this for gpt5 and am not that optimistic, but it is possible it will turn out this way again.
by arduanika | 2025-08-22 01:13:21+00:00
Ah, okay. I understand where the "some" was coming from now. Leaving my earlier comment as-is to keep the chain coherent, but I now see that it wasn't conspiratorial.

Let me see if I can put my point a little more politely. There is basically no economic difference between dividends and buybacks, apart from some tax technicalities. When people talk as if dividends are good and pure whereas buybacks are somehow evil and decoupled from reality, it is almost always drivel.

You seem to have a notion that shares, in their untampered state, should be "conduits to return money to shareholders via dividends". But it really makes ~no economic difference whether the shareholders get direct returns via dividends, versus indirect returns via buybacks.

And I really don't understand what connection you see between this minute distinction, and your point about Palantir being a "nearly sovereign entity". Perhaps you could spell that out.
by TylerE | 2025-08-22 01:13:33+00:00
The nice ones are almost all old business cars. The business car was used by the railroads for senior executives to move around their systems, and hold meetings.. usually contain a couple of executive bedrooms, a staff bedroom (they typically carried a cook and a steward, although the roles were sometimes combined). The rear half or so of the car is an open plan lounge/meeting room.

The cars were usually built by a company like Pullman, usually from a time frame of roughly 1900 +/- 20 years.

Huge money pits, with tons of (often quite ornate) wood m, etc. then add the cost of restoration (again almost all of these cars are 100+ years old), retrofitting modern electrical systems, air conditioning. Could easily be a million dollar project.
by spc476 | 2025-08-22 01:14:20+00:00
A decade ago a friend of mine rented a private rail car (for cost---he knows the owner) for a family trip/birthday present, and I got to ride on it for a few hours as it was being positioned (https://boston.conman.org/2015/08/05.4). I didn't get a price from him, but it was clear it was pretty much the cost of a new car. The car he was renting came with a lounge, three state rooms, bathroom, dining room, kitchen and two crew members (cook and porter, with their own sleeping quarters).

Their trip was from Miami to Chicago back to Jacksonville (where the car is stored---I rode on it from central Florida to Boca Raton as it was being positioned prior to the start of the family trip; because it was running late, I didn't get a chance to eat lunch on it, sigh) over the course of a week or so. If I could, this is how I would travel, but of course, this being the US, it's not really a viable means of transportation.
by SnuffBox | 2025-08-22 01:14:29+00:00
Whenever I see an otherwise civil and mature project utilize something outwardly childish like this I audibly groan and close the page.

I'm sure the software behind it is fine but the imagery and style of it (and the confidence to feature it) makes me doubt the mental credibility/social maturity of anybody willing to make it the first thing you see when accessing a webpage.

Edit: From a quick check of the "CEO" of the company, I was unsurprised to have my concerns confirmed. I may be behind the times but I think there are far too many people in who act obnoxiously (as part of what can only be described as a new subculture) in open source software today and I wish there were better terms to describe it.
by marc_abonce | 2025-08-22 01:14:40+00:00
Yes, even OP admits it in a comment down the thread:

> Commenter: Sounds like you have no product managers [...]

> OP: haha we don't :) we pride ourselves in not hiring any product folks until after we raised our series A. this helped us stay super lean, move fast, and build exactly what our customers want. our platform is definitely not dead simple. but in the early early days, we did rebuild our product 3 times and the 3rd rewrite scaled us to where we are now
by jynelson | 2025-08-22 01:14:59+00:00
I think we are using different meanings of the term "cohere" and I am not sure how to reconcile them. I agree that Rust with async is a more useful language. I don't think being useful implies anything about how coherent a language is (I would point to bash and perl as examples of useful languages with very little coherence). "Coherence" to me means that all the features fit together tightly and are designed with each other in mind, and I don't think that's the case for async and const in Rust—simply because they aren't finished being designed.
by lmm | 2025-08-22 01:15:05+00:00
The joke is you're using the banana but you didn't actually want the gorilla, much less the whole jungle. E.g. you might have an object that represents the single database row you're doing something with, but it's keeping alive a big result set and a connection handle and a transaction. The same thing happening with just an in-memory datastructure (e.g. you computed some big tree structure to compute the result you need) is less bad, but it can still impact your memory usage quite a lot.
by derektank | 2025-08-22 01:15:15+00:00
I've found South Park's comedy and commentary to have both been incredibly on point this season. It does require some previous investment in the characters from the last two decades, so it might not be as accessible to new viewers, but making Donald Trump a reincarnation of Saddam Hussein and having Craig beat Cartman at being a right wing podcast grifter, are incredibly satisfying arcs that play on the established lore and character traits very well. And it hasn't been above making an earnest point e.g. about when is it worth selling out your values in episode 2 with Mr. Mackey
by sifar | 2025-08-22 01:15:20+00:00
>> And as much you want to tout IT services, overall GDP contribution is 11.47% and pharma is 1.72%. Someone has told me that the remittances from India to US is 3%. All that combines to less than 19% contributed by agriculture.

That is the direct GDP contribution of IT/allied services. The indirect societal contribution is significant. Most real estate in big cities, transportation, food and other services rely on the IT industry. Expect a lot of pain in India when this is impacted.
by miki123211 | 2025-08-22 01:15:24+00:00
> We are already at the limit of how small we can scale chips

I strongly suspect this is not true for LLMs. Once progress stabilizes, doing things like embedding the weights of some model directly as part of the chip will suddenly become economical, and that's going to cut costs down dramatically.

Then there's distillation, which basically makes smaller models get better as bigger models get better. You don't necessarily need to run a big model al of the time to reap its benefits.

> so unless the price of electricity comes down exponentially

This is more likely than you think. AI is extremely bandwidth-efficient and not too latency-sensitive (unlike e.g. Netflix et al), so it's pretty trivial to offload AI work to places where electricity is abundant and power generation is lightly regulated.

> Most companies are already running AI models at a loss, scaling the models to be bigger(like GPT 4.5) only makes them more expensive to run.

"We're profitable on inference. If we didn't pay for training, we'd be a very profitable company." Sam Altman, OpenAI CEO[1].

[1] https://www.axios.com/2025/08/15/sam-altman-gpt5-launch-chat...
by jiggawatts | 2025-08-22 01:16:19+00:00
An example of this ideal can go horribly wrong is CERN.

There's one apparatus (of each type) and each "experiment" ends up with its own team. Each team develops their own terminology, publishes in one set of papers, and the peer reviews are by... themselves.

I don't work at CERN, but that criticism was from someone who does.

They were complaining that they could not understand the papers published by a team down the hall from them. Not on some wildly unrelated area of science, but about the same particles they were studying in a similar manner!

If nobody else can understand the research, if nobody else can reproduce it, then it's not useful science!

Note that this isn't exactly the same as Sabine's criticism of CERN and future supercolliders, but it's related.
by JoshTriplett | 2025-08-22 01:16:23+00:00
That's a fair distinction. For the specific case of CC-by-sa 4.0, it's possible to convert to GPLv3. That doesn't help with prior versions of CC-by-sa.

So, for the specific case of material contributed to StackOverflow on or after 2018-05-02, it's possible to use it under GPLv3 (including appropriate attribution), so any project compatible with GPLv3 can copy it with attribution. Any material before that point is not safe to copy.
by tomrod | 2025-08-22 01:16:44+00:00
I like d3 and echarts. Everything else feels a bit hacky.

I tried for a few years to help Streamlit deployments in production. Never will go that direction again. Litestar + React with echarts or d3 is the way to go. Or use your favorite application backend, but REST is almost certainly the way your use case needs to go.
by ehnto | 2025-08-22 01:17:16+00:00
The MIT report that has everyone talking was about 95% of companies not seeing return on investment in using AI, and that is with the VC subsidised pricing. If it gets more expensive that math only gets worse.

I can't predict the future, but one possibility is that AI will not be a general purpose replacement for human effort like some hope, but rather a more expensive than expected tool for a subset of use cases. I think it will be an enduring technology, but how it actually plays out in the economy is not yet clear.
by johnnyanmac | 2025-08-22 01:17:18+00:00
>will accelerate that journey of discovery and learning,

Okay, but what about work output? That's seems to be the only thing business cares about.

Also, maybe it's the HN bias but I don't see this notion where old engineers are rejecting this en masse. More younger people will embrace it. But most younger people haven't mucked in legacy code yet (the lifeblood of any businesses).
by bruhwha | 2025-08-22 01:17:37+00:00
My uncle was/is friends with Tim Keck since he started the Onion at UW Madison.

Used to get handed a stack and asked to spread them around high school.

Years later uncle texts asking if I have weed. At the time yeah I always did. He says bring it to the Berrymore and I smoked up Tim, Eric, and John C Reilly like nbd.

Ahh the old days.
Ask HN: Should I migrate off of Brave Browser?
by dcreater | 2025-08-22 01:17:56+00:00
I've been mostly a happy Brave user - I havent appreciated the crypto, AI, ads etc. they have been subtly pushing and I am not as highly confident as I need to be regarding privacy etc.

Are there any better options out there? The chromium extension ecosystem is another reason im staying on Brave but it seems Zen Browser + Firefox extensions is workable. The only issue with that it doesnt have an Android browser.
by joegibbs | 2025-08-22 01:18:09+00:00
I disagree on the AI 2027 thing, I don't think that we've seen any evidence of self-improvement or a rate of increase in abilities that it suggests. If anything I think that the rate of improvement has slowed since GPT3, without some entirely new architecture I don't see any takeoff scenario. The only way I can imagine AI killing everyone is if somebody decided, for some inscrutable reason, to put an LLM in charge of nuclear missile launches.

The psychosis is worrying but I think an artefact of a new technology that people don't have an accurate mental model around (similar to but worse than the supernatural powers attributed to radio, television etc). Hopefully AI companies will provide more safeguards against it but even without them I think that people will eventually understand the limitations and realise that it's not in love with them, doesn't have a genius new theory of physics and makes things up.
by tialaramex | 2025-08-22 01:18:09+00:00
Which x? There are two in your code, one for each time you introduce a pattern Some(x) and each x has scope which of course ends when that pattern is done with

Notice that the Python doesn't work this way, we didn't make a new variable but instead changed the existing one.

Also, the intent in the Python was a constant, in Rust we'd give this constant an uppercase name by convention, but regardless it's a constant and so of course matching against a constant does what you expect, it can't re-bind a constant, 404 is a constant and so is `const NOT_FOUND: u16 = 404;`
by neilv | 2025-08-22 01:18:29+00:00
> Not for a dozen lines here or there, even if it could be found and identified in a massive code base. That’s like quoting a paragraph of a book in another book, non infringing.

It's potentially non-infringing in a book if you quote it in a plausible way, and properly.

If you copy&paste a paragraph from another book into yours, it's infringing, and a career-ending scandal. There's plenty of precedent on that.

Just like if you manually copied a function out of some GPL code and pasted it into your own.

Or if you had an LLM do it for you.
by btown | 2025-08-22 01:19:34+00:00
My favorite Python "crime" is that a class that defines __rrshift__, instantiated and used as a right-hand-side, lets you have a pipe operator, regardless of the left-hand-side (as long as it doesn't define __rshift__).

It's reasonably type-safe, and there's no need to "close" your chain - every outputted value as you write the chain can have a primitive type.

x = Model.objects.all() >> by_pk >> call(dict.values) >> to_list >> get('name') >> _map(str.title) >> log_debug >> to_json

It shines in notebooks and live coding, where you might want to type stream-of-thought in the same order of operations that you want to take place. Need to log where something might be going wrong? Tee it like you're on a command line!

Idiomatic? Absolutely not. Something to push to production? Not unless you like being stabbed with pitchforks. Actually useful for prototyping? 1000%.
by almostgotcaught | 2025-08-22 01:20:16+00:00
> Which x? There are two in your code, one for each time you introduce a pattern Some(x) and each x has scope which of course ends when that pattern is done with

if each x's scope ends at the end of each case doesn't that mean there's only one x?

> we didn't make a new variable but instead changed the existing one.

so because python doesn't have scopes except for function scopes it shouldn't ever have any new features that intersect with scope?
by doorhammer | 2025-08-22 01:21:10+00:00
As a whole the incentives of capitalism are aligned as you suggest, but every major corp I've worked with has not-so-rare pockets of savvy middle managers that know how to play the game and also care about the welfare of their employees--even if the cultural incentives don't lean that way. (I'm assuming a US market here--and I'm at least tangentially aware that other cultures aren't identical)

E.g., when I worked in call centers I was directly part of initiatives that saved millions and made agents lives better, with an intentionality toward both outcomes.

I also saw people drive agents into the ground trying to maximize utilization and/or schedule adherence with total disregard for the negative morale and business value they were pushing.

It makes me wonder if there are any robust org psych studies about the prevalence and success of middle managers trying to strategically navigate those kinds of situations to benefit their employees. I'd bet it's more rare than not, but I have no idea by how much.