MurphyA/hacker-news huggingface dataset:
by lunar-whitey | 2026-02-26 06:55:54+00:00
You cannot sustain a population center of any size on rainfall. For that, you need electricity to operate municipal pumps (which will likely be absent, as above - if not immediately after generation and distribution is destroyed, then a few weeks later when fuel for the generators is exhausted). Without that the bulk of the population is dead in under a week.

Repurposing feed grain reserves is interesting, but you need fuel for that as well (plus significant coordination, which seems unlikely in a scenario where many people with the required knowledge and authority may be dead and telecommunications infrastructure is destroyed).
by nekusar | 2026-02-26 06:57:05+00:00
There's 2 completely different ways to understand how a Ouija board works. Occult, and Scientific.

Scientific: It's a combined response from everyone's collective unconscious blend of everyone participating. In other words, its a probabilistic result of an "answer" to the question everyone hears.

Occult: If an entity is present, it's basically the unshielded response of that entity by collectively moving everyone's body the same way, as a form of a mild channel. Since Ouija doesn't specific to make a circle and request presence of a specific entity, there's a good chance of some being hostile. Or, you all get nothing at all, and basically garbage as part of the divination/communication.

But comparing Ouija to LLMs? The LLM, with the same weights, with the same hyperparameters, and same questions will give the same answers. That is deterministic, at least in that narrow sense. An Ouija board is not deterministic, and cannot be tested in any meaningful scientific sense.
Show HN: Programmatic (and self-updating) SaaS demo videos
by guico | 2026-02-26 06:57:13+00:00
Hey guys!

While building another SaaS we got fed up with recording and, re-recording demos for help-center so decided to try and automate it using Playwright. Turns out it's not that easy, but we got it to a point that's usable, and quite useful for us already.

Feel free to try and send feedback. Every new account gets some free credits so you can see what it can do.

Thanks!

PS: Because this is heavy on infra we have a waitlist thing but I'm monitoring and will let you in within minutes/hours, just need to space people out a bit. Thanks

PPS: Here's an example video made with Rundown https://www.rundown.video/011fb9da-72f7-41d1-bdce-f187f398e0...
by devinda-dilshan | 2026-02-26 06:58:02+00:00
Hey HN,

I'm Devinda, creator of CleverMock. I built this because I was frustrated with existing interview prep tools. They feel like passive Q&A bots. They let you ramble on, but real interviews aren't like that. Interviewers interrupt, they ask follow-up questions, they push you to be concise.

CleverMock is designed to simulate that pressure. It's an AI-powered voice interviewer for system design and behavioral rounds that actually listens to what you're saying and will cut you off if you start going off-track or rambling. It forces you to be clear and to the point.

It's still in beta, and I'd love to get your feedback. You can try it out without signing up. Let me know what you think!
by unohee | 2026-02-26 06:58:04+00:00
The worker-reviewer pipeline typically runs 1–2 self-revision iterations. In my experience, agents handle most tasks fine, but they tend to miss quality gates — docstrings, minor business logic edge cases, that kind of thing. The reviewer catches what slips through on the code quality side.
This is all based on observed behavior from daily Claude Code CLI usage, where I've added hooks specifically to catch systematic failure patterns. OpenSwarm is essentially a productized version of those scaffoldings from my actual workflow — packaged into a more reusable architecture.
On context drift — good call, and yeah, that's exactly why the shared memory layer matters. LanceDB keeps the grounding consistent across the chain so each agent isn't just working off its own drifting interpretation.
As for disagreements: right now the reviewer blocks and the worker retries with feedback, with a hard cutoff to prevent infinite loops. It's simple but it works — the revision depth rarely needs to go beyond 2 rounds. And when it does fail, that's actually the useful signal — especially when you're triaging larger projects, the points where agents break down are exactly where a human engineer needs to step in.
At this point, what OpenSwarm really needs is broader testing from other users to validate these patterns outside my own workflow.
by bandrami | 2026-02-26 06:58:48+00:00
Yesterday I asked mistral to list five mammals that don't have "e" in their name. Number three was "otter" and number five was "camel".

phi4-mini-reasoning took the same prompt and bailed out because (at least according to its trace) it interpreted it as meaning "can't have a, e, i, o, or u in the name".

Local is the only inference paradigm I'm interested in, but these things have a way to go.
by bryanrasmussen | 2026-02-26 07:00:27+00:00
OK but then that goes back to their other assertion that it gives a huge hint at what is going on behind the scenes, is that huge hint just "more data gives better results!" if so, that doesn't seem at all important since that is the absolutely central idea of an LLM. That is not behind the scenes at all, that is the introduction to the play as written by the author.

Not your fault obviously, but they have not yet described what that huge hint is, and I'm just at the edge of my seat with anticipation here.
by hn_throwaway_99 | 2026-02-26 07:00:51+00:00
Well then, why didn't you come up with it first?

I'm serious. The world is rife with things the "don't seem like a big deal" only in retrospect, when people downplay innovations as "no big deal/anyone can do that" when something comes on the scene that a lot of people connect with.

Heck, I feel like your response is the art equivalent of this top comment on the original Dropbox Show HN submission by Drew Houston:

> For a Linux user, you can already build such a system yourself quite trivially by getting an FTP account, mounting it locally with curlftpfs, and then using SVN or CVS on the mounted filesystem. From Windows or Mac, this FTP account could be accessed through built-in software.

https://news.ycombinator.com/item?id=9224
by FarmerPotato | 2026-02-26 07:01:29+00:00
I don't see much difference when you consider the condition of farming and mining slaves in Roman society.

Slaves were spoils of war since before the Republic.

Even if a slave had valuable skills, and were treated better, they had no legal recourse against a Roman citizen. Their owner could sell them like chattel, break up families (slave marriage had no legal basis) and kill them outright.

The highly skilled could enter into a kind of indentured servitude. That's a separate category.

You hear romantic stories about household servants gaining high esteem and a few being granted or buying their freedom. These were the exception, against the backdrop of menial labor.
by pllbnk | 2026-02-26 07:02:08+00:00
ChatGPT has a good name. It's weird and awkward but it still rolls off the tongue. And I am saying that as a non native English speaker because the name has been migrated to other languages with the English pronunciation.

In comparison, Claude's name is very bad, it just doesn't sound right and people might mishear me when I say it. I never say "Claude" when talking to other, especially non-technical people, and instead say "ChatGPT" even though I am using Claude exclusively.

Google has another problem - they advertise their models as separate products. There is Gemini and there is Nano Banana, also Nano Banana Pro. But they are all somehow under the same product which is still called Gemini. I understand the distinction but I am sure many non-technical people find it confusing.
by brookst | 2026-02-26 07:02:27+00:00
I don’t see it.

Imagine for a moment the there is no oversight. Every intern can ship prod code with their own homemade crypto.

How do you, in a retail business, agree to accept credentials that anyone can mint for free?

I mean obviously it happened. But… this doesn’t even seem like a compliance mistake. It’s a business-level mistake.
by gammalost | 2026-02-26 07:02:38+00:00
It is really interesting how great and also how terrible LLMs can be at the same time. For example, I had a really annoying bug yesterday, I missed one character, "_". Asking ChatGPT for help led to a lot of feedback that was arguably okay but not currently relevant (because there was a fatal flaw in the code).

Remade the conversation with personal information stripped here https://chatgpt.com/share/699fef77-b530-8007-a4ed-c3dda9461d...
by Imustaskforhelp | 2026-02-26 07:02:39+00:00
Nah I totally get that, I think my point was a little intended as ironical more than anything.

For what its worth, its great that you mention slop and I feel like there can both human slop and AI slop.

Had to look up cambridge for definition of slop there but slop in this context means, content on the internet that is of very low quality, especially when it is created by artificial intelligence:

Quality essentially sums down to being "good" whose definition is "very satisfactory, enjoyable, pleasant, or interesting"

I guess in retrospect, My comment can be considered unsatisfactory/less-interesting as you mention as well, that can be totally true.

I guess I can (try?) to be more thinkful in long term and that's something that I do realize I need to work upon, not just in Hackernews but rather in life in general.

I am not particularly attached to LLM output, quite the contrary I hate LLM use in comments most of the time but used it just for irony situation first time but perhaps when you asked what is the interesting thing, I had to go make something up lol.

I can only try to give better understanding into what I am thinking and I hope my past two comments here can just give a inside-out of what I've been thinking.

Have a nice day.

[Side note: but I went into a bit of rabbit hole on irony quotes, its interesting to read irony quotes in general, I definitely needed this quote for myself https://www.azquotes.com/quote/379798?ref=irony, not sure why its in irony section tho. But yea]
by phoronixrly | 2026-02-26 07:03:13+00:00
It's been a headscratcher for me... The EU and the US have an issue with CCP-subsidised tech giants, but their sole reaction is banning them in some form or other? In the EU it is from public tenders, in the US it's from dealing with US companies.

This does not really help EU and US businesses to be competitive though, neither does it stop consumers going for the cheapest option...
by throwworhtthrow | 2026-02-26 07:04:18+00:00
Coincidentally, I just used hn.algolia to look up one of your old comments where you describe being sandblasted, and was surprised to find the most recent use of "sandblasted" on HN is by you, linking to an algolia search of you saying "sandblasted".

Thank you sincerely for your sacrifice, Dan. Whenever I have an urge to flame, I picture my impending comment as one more grain of sand speeding towards your cranium, and instead I step away from the keyboard.
by loayabdalslam | 2026-02-26 07:04:19+00:00
Actually, we're not like JSX; we offer a capsule solution. I can't show you my complete vision for the project right now, but if we could create a code generator using that language, it would be about 1000 times faster than normal because everything it generates would be in one place, in one way, and with one method, without retraining—just one agents.md file explaining the language.
by tikotus | 2026-02-26 07:04:20+00:00
I hear the claim that people already have their conversation on ChatGPT and can't move them. I'm curious, what are these discussions like? I've never continued an old discussion, I just start a new one every time I have a question. If the discussion is long, I often start a new chat to get a blank slate. My experience is that the chat history just causes confusion.

So I'm curious to understand: What are the discussions like that people go back to and would lose if they moved to another platform?
by jjmarr | 2026-02-26 07:04:26+00:00
I created a code review pipeline at work with a similar tradeoff and we found the cost is worth it. Time is a non-issue.

We could run Claude on our code and call it a day, but we have hundreds of style, safety, etc rules on a very large C++ codebase with intricate behaviour (cooperative multitasking be fun).

So we run dozens of parallel CLI agents that can review the code in excruciating detail. This has completely replaced human code review for anything that isn't functional correctness but is near the same order of magnitude of price. Much better than humans and beats every commercial tool.

"scaling time" on the other hand is useless. You can just divide the problem with subagents until it's time within a few minutes because that also increases quality due to less context/more focus.
by friendzis | 2026-02-26 07:04:54+00:00
> You can test hypotheses and learn things even about chaotic or emergent systems.

Ah yes, the famous "Cut GDP in half, abolish public schooling and use that as a control" experiment. Majority of economic "models" are entirely correlational without any mechanistic explanation whatsoever or an explanation so superficial that it contradicts either itself or observed reality.

If you look deeper and read explanatory notes of economic laws, the model may refer some publications, but then the actual figures plugged in the model are explained as "these values have been observed to lead to the desired outcomes, therefore are set without any modeling or validation, hope for the best, lesssgoooo".
by GolfPopper | 2026-02-26 07:05:07+00:00
>The producer(s) of the old data had an asking price, which was taken by the LLM trainers.

This is... blatantly untrue?

https://arstechnica.com/tech-policy/2026/02/microsoft-remove...

https://www.theatlantic.com/technology/archive/2025/03/libge...
by theptip | 2026-02-26 07:05:10+00:00
If capabilities stop increasing for some reason, then yeah, Anthropic is screwed.

If METR task times double twice into the multi-day range in 12 months, then it’s plausible to me that Anthropic can charge $1k/mo or more by automating large chunks of the SWE role. (They have 10x’d their revenue every year, perhaps “value of enterprise contracts” is a better way of intuiting their growth rather than “$/seat” since each seat gets way more productive in this world-branch.)
by simoncion | 2026-02-26 07:05:57+00:00
If the government is being too obvious about the fact that the entity in question is nothing more than its puppet, then something can be done about that. Entities that are government entities in everything but name can be considered to be government entities and become subject to all the relevant restrictions. There's some fancy-ass phrase for this, but I can't remember it at the moment.

Also, the third-party doctrine hasn't been good enough for certainly the last thirty and maybe the last hundred years. But, authoritarians aren't easily separated from their tools of oppression, so I expect to not see that cluster of regulations updated to be actually protective within my lifetime.
by mattnewton | 2026-02-26 07:06:06+00:00
Models will always struggle with this specific task without tool use, because of the way they tokenize things. I think a bit of prompt engineering, asking it to spell out each work or giving it the ability to run a “contains e” python function on a lot of animal names it generates or searches for solves this.

Lots of local ai use cases I think are solvable similarly once local models get good at tool use and have the proper harness.
by GodelNumbering | 2026-02-26 07:06:22+00:00
It is probably the first-time aha moment the author is talking about. But under the hood, it is probably not as magical as it appears to be.

Suppose you prompted the underlying LLM with "You are an expert reviewer in..." and a bunch of instructions followed by the paper. LLM knows from the training that 'expert reviewer' is an important term (skipping over and oversimplifying here) and my response should be framed as what I know an expert reviewer would write. LLMs are good at picking up (or copying) the patterns of response, but the underlying layer that evaluates things against a structural and logical understanding is missing. So, in corner cases, you get responses that are framed impressively but do not contain any meaningful inputs. This trait makes LLMs great at demos but weak at consistently finding novel interesting things.

If the above is true, the author will find after several reviews that the agent they use keeps picking up on the same/similar things (collapsed behavior that makes it good at coding type tasks) and is blind to some other obvious things it should have picked up on. This is not a criticism, many humans are often just as collapsed in their 'reasoning'.

LLMs are good at 8 out of 10 tasks, but you don't know which 8.
by fc417fc802 | 2026-02-26 07:07:13+00:00
No, as I said, we have _lots_ of theories about exactly that at various levels of detail. The theories vary based on (at least) the specifics of the loss function being employed to construct the gradient. Giving an overview of that is far beyond the scope of this comment section (but it's well trodden ground so you can just go ask an LLM).

The "black box" bit refers to a generic, interchangeable optimization algorithm that simply makes the number go down (or up or whatever).

There are certainly various details about the internal workings of models that we don't properly understand but a blanket claim about the whole is erroneous.
by keeda | 2026-02-26 07:07:37+00:00
Was thinking more about cognition than neuroscience, but sure, even there. Think of any counter-examples -- I'm guessing things like symbolic reasoning or pre-existing structures in the brain -- and then consider the origins of those concepts.

Admittedly I'm an absolute layman just dabbling in this, but I could find not a single concept that cannot be traced to statistical origins. Like, symbols are essentially "vectors" of thousands of neurons firing simultaneously, and the pre-existing structures in the nervous system originate from evolution, which is a statistical process.

"Just statistics", as far as I can tell! ;-)
by jspdown | 2026-02-26 07:07:39+00:00
On my personal coding agent I've introduced a setup phase inside skills.

I distribute my skills with flake.nix and a lock file. This flake installs the required dependencies and set them up. A frontmatter field defines the name of secrets that need to be passed to the flake.

As it is, it works for me because I trust my skill flakes and skills are static in my system:
-I build an agent docker image for the agent in which I inject the skills directory.
-Each skill is setup when building the image
-Secret are copied before the setup phase and removed right after

All in all, Nix is quite nice for Skills :)
by modeless | 2026-02-26 07:07:43+00:00
It's clear that in the general case "predict the next word" requires arbitrarily good understanding of everything that can be described with language. That shouldn't be mysterious. What's mysterious is how a simple training procedure with that objective can in practice achieve that understanding. But then again, does it? The base model you get after that simple training procedure is not capable of doing the things described in the article. It is only useful as a starting point for a much more complex reinforcement learning procedure that teaches the skills an agent needs to achieve goals.

RL is where the magic comes from, and RL is more than just "predict the next word". It has agents and environments and actions and rewards.
by TrueGeek | 2026-02-26 07:08:14+00:00
> monetary requirements, which are actually quite low

Technically, yes - you are required to hold only €4,500 as an "investment" in the business you create. In reality you will need a lot more. My wife and I spent about €40k to move over which is inline with what others on the DAFT program have said they spent.

Completely worth it though!
by brookst | 2026-02-26 07:08:16+00:00
It’s taken me a while to get good at using them.

My advice: ask for more than what you think it can do. #1 mistake is failing to give enough context about goals, constraints, priorities.

Don’t ask “complete this one small task”, ask “hey I’m working on this big project, docs are here, source is there, I’m not sure how to do that, come up with a plan”
by fodkodrasz | 2026-02-26 07:08:29+00:00
Where does current Notepad store its settings? How could I distribute settings to new users, eg. by applying a reg file?

It looks like to me that it stores its settings at "%LOCALAPPDATA%\Packages\Microsoft.WindowsNotepad_8wekyb3d8bbwe\Settings\settings.dat", which is some binary format.

Why is registry being abandoned? If it is, why isn't ini or json or a plain text format used? Who are working at Microsoft now, abandoning both the windows ways to approach tasks, and also the other generic sane default approaches?
by coppsilgold | 2026-02-26 07:08:35+00:00
If you are on Linux you can 'download' some RAM. Enable zram, configure sysctl variables to make good use of it.

Note that it won't help you if your workload makes use of all your RAM at once.

If you have a bunch of stuff running in the background it will help a lot.

I get 2 to 3 compression factor at all times with zstd. I calculated the utility to be as if I had 20GB extra RAM for what I do.
by jltsiren | 2026-02-26 07:09:18+00:00
Public transit depends on the assumption that some trips are more common than others. If any given person is equally likely to go to any direction, public transit becomes too expensive to build. And it becomes impossible to make the city dense without turning the traffic into a nightmare.

A typical direct bus line starts from somewhere, goes through a number of neighborhoods, reaches a major street, and follows it to a central location. The number of directions that need a bus line is typically much higher than the number of streets reaching the central location. (For example, you need ~10-degree intervals at 10 km from the center to guarantee a reasonable walking distance to the nearest bus stop.) Hence the bus lines eventually converge.

Once you have enough bus traffic that a dedicated lane makes sense, transforming an ordinary lane into a bus lane will make the traffic faster for the average person. It's not a Pareto improvement, as the traffic will become worse for those who drive on that route. But it's not a huge loss for them either. If you already have 20+ buses/hour making frequent stops during the rush hour, the throughput for that lane will already be much lower than for the other lanes.
by globular-toast | 2026-02-26 07:10:04+00:00
I've been thinking about the "human signal" ever since the first GPT. Interestingly, a few years ago I would get people questioning whether my posts were written by GPT, but that's stopped now. I'm not sure if it's because they no longer think that or because it's not interesting any more.

I wonder if there's a way we can communicate that LLMs fundamentally can't keep up with. If LLMs have hit on being exactly the way our brains work then I guess not. But maybe we still have something special. I haven't tried how well LLMs understand language written like in Iain M. Banks's Feersum Endjinn.
by theptip | 2026-02-26 07:10:10+00:00
The point is that in this hypothetical you can get public access to Claude Opus 6, but they internally use Claude Opus 7 (Accounting Finetune) which is both cheaper to operate and higher IQ.

So they (or their wholly owned subsidiary) can sell accounting services cheaper than anyone on the outside.

Regarding the diffusion/distillation time, I assume it gets harder to distill in the world where frontier labs don’t give API access to their newest models.