MurphyA/hacker-news huggingface dataset:
by quotemstr | 2026-02-23 17:19:54+00:00
Technologists engage in an understandable, but ultimately harmful behavior: when they don't want outcome X, they deny that the technology T(X) works. Consider key escrow, DRM, and durable watermarking alongside age verification. They've all been called cryptographically impossible, but they're not. It's just socially obligatory to pretend they can't be done. And what happens when you create an environment in which the best are under a social taboo against working on certain technologies? Do you think that these technologies stop existing?

LOL.

Of course these technologies keep existing, and you end up with the worst, most wretched people implementing them, and we're all worse off. Concretely, few people are working on ZKPs for age verification because the hive mind of "good people" who know what ZKPs are make working on age verification social anathema.
by mghackerlady | 2026-02-23 17:20:25+00:00
I once did something similar for car wash doors. there's a car wash door company out there that has a control panel accessible over VNC and uses the same defaults for every one they set up, so I used to connect to random ones and open and shut the car wash doors for the fun of it. The best part was when someone noticed and tried to shut it only for me to open it again, resulting in a battle where neither of us knew anything more than someone or something keeps undoing my actions
by tinco | 2026-02-23 17:20:54+00:00
My company helps companies do migrations using LLM agents and rigid validations, and it is not a surprising goal. Of course most projects are not as clean as a compiler is in terms of their inputs and outputs, but our pitch to customers is that we aim to do bug-for-bug compatible migrations.

Porting a project from PHP7 to PHP8, you'd want the exact same SQL statements to be sent to the server for your test suite, or at least be able to explain the differences. Porting AngularJS to Vue, you'd want the same backend requests, etc..
by Sharlin | 2026-02-23 17:21:06+00:00
That's not how it works… They aren't able to literally regurgitate everything they've read, no matter how you prompt them. That would obviously violate the pigeonhole principle. LLMs are, of course, a lossy compression format, and figuring out just how lossy the format is, and the degree of lossiness depends on the frequency of the given string in the training data. It's clearly worthwhile to investigate how exactly it depends.
by meowface | 2026-02-23 17:21:46+00:00
Adults are nearly as susceptible to such addiction. If this is the goal then the actual legislation should be to prohibit social media companies from doing it to anyone. (I think this would be government overreach and a possible first amendment violation, though. I say this as a center-left person who deeply hates what Musk has done to Twitter. I would even describe myself as an anti-free speech person; I just respect the nation's laws and the principle that the state should not be able to imprison you just for speech.)
by simoncion | 2026-02-23 17:22:03+00:00
> no, it is exactly as protective as the protections for purchasing alcohol or buying smokes...

Right. That's exactly as protective as that tickbox. [0] As I mentioned, any of-age person can distribute those UUIDs to people who are not of-age. Unlike with the proposed ID-collection-and-retention schemes (that are authoritarian's wet dreams) the vendor of the UUID is not responsible for ensuring that that UUID is not later used by someone who is not of-age.

If you were to -say- make alcohol vendors liable for the actions of of-age people who pass on alcohol to not-of-age people, then you'd see serious attempts to control distribution.

[0] Don't forget the existence of preexisting parental controls in every major OS. IME, this is a hurdle that's at least as difficult to surmount as the ID check done in non-chain convenience stores.
by vidarh | 2026-02-23 17:22:03+00:00
They acknowledge that in their paper ("Some might qualify our experiments as atypical use, as we deliberately tried to surface memorized books. Adversarial use, like the use of jailbreaks, may matter for copyright infringement analysis", page 19 - their discussion continues and seems quite reasonable)

From a technical point of view, in terms of ability to reproduce text verbatim, I don't think it is very interesting that they can produce long runs of text from some of the most popular books in modern history. It'd be almost surprising if they couldn't, though one might differ on how much they could be expected to recall with precision.

Even then, as they note, to get most of Harry Potter 1, they needed to spend around $120 on extensive prompting, and a process that they also freely acknowledge is more complex than it probably would be worth if the goal is to get a copy.

It's still worth exploring to what extent the models are able to "memorize", though.

But personally I'd be more interested in seeing to what extent they can handle less popular books, that are less likely to be present in multiple copies, and repeated quotes, in the training data.
by rawgabbit | 2026-02-23 17:22:18+00:00
I would focus on the Oracle problem. If the cost of a believable deep fake is cheaper than the cost of verifying provenance, the fakers win.

I believe the issue is better served by exploring how to raise the cost of making a believable deep fake? That is as an industry we need to agree a legally valid digital document would have the following digital water marks, hanko, signatures, whatever that makes the cost of these things more expensive than the cost of verifying their provenance.
by jibal | 2026-02-23 17:22:37+00:00
> It's honest.

It's not, nor is it well informed. People are currently developing languages specifically for use by LLMs.

> It's not the best tool for the job for a lot of things

Then how could it possibly be the final language?

> if the LLMs make writing it as fast as anything else - whelp, I can't see any reason not to do it in Rust

This has nothing to do with the claim that it's the final language.
Show HN: Tastebuds AI – recipe generator with USDA-backed nutrition data
by marcosinghof | 2026-02-23 17:23:15+00:00
I built this because I wanted a clean recipe browsing experience without ads, life stories, or SEO bloat. However, I still needed accurate nutrition info. Tastebuds AI calculates nutrition by mapping every ingredient to the USDA Food Data Central database, so the numbers are actually trustworthy.
You tell it your dietary restrictions, cuisine style (healthy, easy, adventurous, etc.), ingredients you dislike, and what kitchen equipment you have. It then generates ideas and subsequently a full recipe with ingredients, step-by-step instructions, an AI-generated image, and an accurate macro breakdown.
The app is still fresh so I can pivot in any direction — would love feedback, especially from people tracking macros or managing dietary restrictions where accuracy matters.
by scythe | 2026-02-23 17:23:25+00:00
It's crazy to me that we want to force age verification on every service across the Internet before we ban phones in school. I could understand being in favor of both, or neither, but implementing the policy that impacts everybody's privacy before the one that specifically applies within government-run institutions is just so disappointingly backwards it's tempting to consider conspiracy-like explanations.

The advantage, I think, of age verification by private companies over cellphone bans in public schools is that cellphone bans appear as a line-item on the government balance sheet, whereas the costs of age verification are diffuse and difficult to calculate. It's actually quite common for governments to prefer imposing costs in ways that make it easier for the legislators to throw up their hands and whistle innocently about why everything just got more expensive and difficult.

And the argument over age verification for merely viewing websites, which is technically difficult and invasive, muddles the waters over the question of age verification for social media profiles, where underage users are more likely to get caught and banned by simple observation. The latter system has already existed for decades -- I remember kids getting banned for admitting they were under 13 on videogame forums in the '00s all the time. It seems like technology has caused people to believe that the law has to be perfectly enforceable in order to be any good, but that isn't historically how the law has worked -- it is possible for most crimes to go unsolved and yet most criminals get caught. If we are going to preserve individual privacy and due process, we need to be willing to design imperfect systems.
by s_dev | 2026-02-23 17:23:26+00:00
Cloud Act directly conflicts with GDPR. To really rub salt in the wound Trump overtly threatening to invade the EU (Greenland) basically turned the whole of Europe off seeing the US as a reliable ally. I don't think Americans have caught up to how much damage he has done to the image of the US amongst allies. They seem blissfully unaware of what's happening. Of course there are plenty of astute Americans who are aware but not the public at large.
by seertaak | 2026-02-23 17:23:33+00:00
Sorry, when you say "gloriously free market", do you mean whatever it takes EU, helicopter money (or, rewinding a decade, Greenspan put) US, or factory of the world China? :)

My point is that it's not a real market economy if the risk premium -- and in China's case, the exchange rate -- is rigged. And it has been, since the 90s.

EDIT: For clarity, I'm agreeing with you, since you were being facetious.
by hnfong | 2026-02-23 17:23:36+00:00
If you look carefully at the graph on the readme page, you'd see it compares Dijkstra's algorithm, a "DMMSY(res)", and a "DMMSY(opt)".

Presumably the claimed contribution was the optimized version, but note that whatever DMMSY(res) is, it should still be O(m log^{2/3} n) or whatever DMMSY's time complexity is supposed to be.

But DMMSY(res)'s run times follow Dijkstra closely in the graph.

The only conclusion is that something is off -- either the author measured the wrong thing, or he was able to optimize the implementation of the algorithm to the extent that the optimizations over-powers any asymptotic gains. Or the implementation is wrong.

At any rate, as you mentioned, the difference between `m log n` and `m log^{2/3} n` is insignificant at n=1M (and TBH won't be significant at any practical n). If the results and the implementation are both correct, it just means the author simply found a way to reduce the constant time factor of the implementation.
by mendrugory | 2026-02-23 17:23:48+00:00
Hi,

I built Naiply, a browser-based multiplayer platform for traditional Spanish card games like Brisca and Tute.
It’s built entirely with Phoenix LiveView — no SPA frontend, minimal JavaScript. All game state lives on the server.
Some interesting challenges:
Handling real-time turn synchronization
Preventing race conditions in trick resolution
Designing the bidding (puja) AI for Tute Subastado
Managing latency without client-side prediction
Keeping the UI reactive with server-driven updates
One particularly tricky part was designing a bidding algorithm that estimates expected trick value before trump is chosen.
Happy to answer technical questions — especially about architecture decisions.

https://naiply.com
by m4rtink | 2026-02-23 17:23:49+00:00
The "Bank identity" system in Czech Republic (and likely other countries) can be used to log into to various government services. The idea is that you already authenticated to the bank when getting the account, so they can be sure it is really sou when you log in - so why not make it possible for you to log in to other services as well if you want to ?
by dgacmu | 2026-02-23 17:23:54+00:00
The performance results seem a little, uh, disingenuous?

First, using a 4ary heap means the performance is closer to O((E+V)logV) instead of the E + VlogV you can get using a Fibonacci heap. So it removes the drawback to the new method, which is that it goes from VlogV to ELog2/3 V.

If you look at that term, it means the new method is only asymptotically faster when log1/3(n) > m/n, IF you're comparing to the actual VlogV version of Dijkstra's...

For m/n = 3, that cutover is at about 140M nodes.

Second, the "opt" seems to be applied only to the new method. There's no apples to apples comparison here.
by menzoic | 2026-02-23 17:23:58+00:00
> get the best results when the context window is right around 70%

I used to be trigger happy with /compact or using the hand off technique to transfer knowledge between sessions with a doc. But lately the newer generation of models seem to be handling long context pretty well up to around 20% remaining context.

But this is when I'm working on the same focused task. I would instantly reset it if I started implementing an unrelated task. Even if there was 90% left, since theres just no benefit to keeping the old context
by holly01 | 2026-02-23 17:24:02+00:00
Coco coir is very cheap and is what I use. If you want more of a project, you can make the inoculation jars and sterilize the grain yourself. That way you’ll be taking a spore/liquid culture syringe from a tiny blob of mycelium to a whole network of fruiting bodies. Doing that will also be much cheaper in the long run if you stick with the hobby
by orwin | 2026-02-23 17:24:05+00:00
It's a few points, but consumers confidence is low and debt is _really_ high, saving rates are excruciatingly low (especially when compared to developing economies).

If I had to bet, US growth should be driven by AI investment, high-earner spending and net exports (a bit like China). Being a net exporter basically mean suppressing workers wages, so that tracks.

If tariffs are stopped all at once without being careful about it, I'm a bit wary of the chain reaction. We might see negative growth for a quarter (temporarily), but since the economy is vibe-based these days, that could end up really bad.
by jmye | 2026-02-23 17:24:18+00:00
Sorry, I know it's a hard line for parents to tread and it's really easy to criticize parenting decisions other people are making, but the "everyone else is doing it so I have to" always seems as lazy to me today, as it probably did to my parents when I said it to them as a teenager.

Is it more important to prevent your son from being weaponized and turned into a little ball of hate and anger, and your daughter from spending her teen years depressed and encouraged to develop eating disorders, or to make sure they can binge the same influencers as their "friends"?
by john_strinlai | 2026-02-23 17:24:22+00:00
>Right. That's exactly as protective as that tickbox. [0]

no, it isn't, for reasons already mentioned but i will say it again for clarity:

- a 14 year old can click "im of age" on a checkbox.

- a 14 year old cannot go into a gas station and buy smokes. they will be declined.

>As I mentioned, any of-age person can distribute those UUIDs to people who are not of-age.

again... same with smokes and alcohol! but we are okay with how smokes and alcohol are regulated right now.

tiktok is not worse than a bottle of vodka. we are okay with how vodka is regulated. tiktok does not need even more strict age-verification than vodka.

it is not perfect, but it is absolutely more stringent than a checkbox. if you still doubt me, please send one of your 12-14 year old family members to buy a pack of smokes or a bottle of vodka at the nearest store. i will wait for your report.
by eightysixfour | 2026-02-23 17:24:25+00:00
> Would we describe being Roman, a Briton or an Austro-Hungarian as a "job"? I don't think so.

I think this is the articles point. We would not consider being Roman a job, but we would consider being a Legionary a job.

The article is arguing “Viking” is more “Legionary” than “Roman.”
by aibuildersdig | 2026-02-23 17:24:33+00:00
For the past three years, the dominant paradigm in AI has been \"bigger is better.\" But if you are building an application today—whether it's a customer support chatbot or an automated coding assistant—massive models are often overkill. They are slow, expensive, and prone to unpredictable hallucinations. \n\nSmall Language Models (7B to 14B parameters like Llama 3 or Mistral) are dominating the developer space because of:\n1. Cost Efficiency\n2. Low Latency \n3. Fine-Tuning Superiority (fine-tuning an 8B model on proprietary data for a specific task often outperforms GPT-4 on that specific task).\n\nThe Playbook: Stop trying to prompt-engineer a massive model. Generate a high-quality dataset of 1,000 examples using a massive model, and use that dataset to fine-tune a small, open-source model. \n\nIf you found this helpful, I write a weekly newsletter for AI builders covering deep dives like this, new models, and tools.
by bondarchuk | 2026-02-23 17:24:40+00:00
Yes, it's hard work to build a society where people behave responsibly and in their best interests. But I'd prefer we actually put in the effort rather than go for the easy authoritarian option out of basically laziness and contempt for your fellow man.

(fwiw I regularly talk to parents who are quite aware of various parental controls and use them effectively, combined with talking to their kids and just general good parenting practices)
by input_sh | 2026-02-23 17:24:42+00:00
> "in any meaningful capacity"

Building a factory is one thing, they can have 50 of them built, but that doesn't mean much if all 50 together amount to like 0.1% of the company's output.

Once those factories scale up to 1-2%, then we can start considering that they've actually built a domestic supply, but that's a whole different goal than simply building the factories. Building factories is trivial. Making them output something is also "trivial". Scaling that up to a meaningful amount is a whole different, much harder goal to accomplish.
by MontyCarloHall | 2026-02-23 17:24:48+00:00
>Waymo benefits from Google's unparalleled geospatial data.

How much of Waymo's training data is based on LIDAR mapping versus satellite/aerial/street view imagery? Before Waymo deploys in a new city, it deploys a huge fleet of cars that spend months of driving completely supervised, presumably to construct a detailed LIDAR map of the city. The fact that this needs to happen suggests Google's geospatial data moat is not as wide as it seems.

If LIDAR becomes cheap, you could imagine other car manufacturers would add it cars, initially and ostensibly to help with L2 driver aids, but with the ulterior motive of making a continuously updated map of the roads. If LIDAR were cheap enough that it could be added to every new Toyota or Ford as an afterthought, it would generate a hell of a lot more continuous mapping data than Waymo will ever have.
by anon291 | 2026-02-23 17:24:52+00:00
This is incorrect.

(1) Religions are treated no differently than any other non-profit.

(2) No non-profit may endorse a particular candidate. They are free to comment on particular issues and policies and referenda.

A priest can say 'vote no on marijuana'. They cannot say 'vote yes to Mary Sue because she doesn't like marijuana'.
by thewebguyd | 2026-02-23 17:25:00+00:00
The alternative is progressive disclosure and contextual actions, mostly. Only show buttons and options when they are functional (e.g., a fixed bottom nav bar changes to copy/cut/paste only when text is selected, otherwise it displays nav icons, or changes to something else entirely on some other action).

For overflow, have the bottom nav bar slide up (kind of like old iOS control center) to reveal more options, just have to be cautious not to re-create the three dots menu junk drawer in there too.

I think the three-dot menu junk drawer is just a result of lazy design from a goal of re-using the same UI everywhere, no matter the OS.

If we want good design, then (collective) we need to start making unique native UIs per platform, using that platform’s toolkits and HIG instead of “branded” experiences using cross platform UIs.

That’s for mobile, for desktop just dump mobile design entirely. Go full on information density, menus, etc. Make it designed to be navigated with a keyboard and a mouse.
by luxuryballs | 2026-02-23 17:25:20+00:00
this is the biggest problem, so many parents are head-in-the-sand when it comes to things that can damage a child’s mind like screen time, yet no matter how much you protect them if it’s not a shared effort it all goes out the window, then the kid becomes incentivized to spend more time with friends just for the access, and can develop a sense that maybe mom and dad are just wrong because why aren’t so-and-so’s parents so strict?

because their parents didn’t read the research or don’t care about the opportunity cost because it can’t be that big of a deal or it would not be allowed or legal right? at least not until their kid gets into a jam or shows behavioral issues, but even then they don’t evaluate, they often just fall prey to the next monthly subscription to cancel out the effects of the first: medication
by toomuchtodo | 2026-02-23 17:26:04+00:00
I think you misunderstand. The slop can come from anywhere, including captive apps like Pinterest, so why use Pinterest? The ask is: how can you get a similar experience on non tech controlled systems? That does not mean you won't get slop, it means that Pinterest is not the gatekeeper to the user experience. There will likely be slop, but that is a distinct problem statement to solve for.

My concern is the gatekeeper (in this case, Pinterest), and avoiding them at all costs using the ability to build replacements swiftly using vibe coding on open protocols (although vibe coding is not required of course, it will simply speed time to market). ATProto cannot be controlled by design, so it is ideal for building apps that need social rails (as a Pinterest replacement might). What is Pinterest besides an app, a search engine, and an object storage system after all?

Tangentially, ATProto moderation primitives might be of use in detecting, tagging, and filtering AI slop (via media, metadata, and author/publisher signal), but more research is required on this topic.
by chr1 | 2026-02-23 17:26:20+00:00
Well it kinda is the same, in any transaction today two people vote to transfer goods and the rest of the people in the country vote to take a percentage of that as tax.

We only need to make sure that decisions affect the smallest number of people possible and only those who make decision bear its good or bad consequences.

Same can work with other issues, like do we want to build a road or stadium, how do we want to deal with homeless in our part of the city etc.

Online, open voting, with possibility to trade votes, and requirement to reach almost 100% accept vote for decisions, can work much better than systems we have now.

As for average person being not smart, average buyer poorly understands biology, and ends up buying things that are harmful to eat or eats to much, but we do not have representative doctors who will decide who eats how much in restaurants. The important thing is to create an arrangement where poor choices of a person do not affect others.
by nateb2022 | 2026-02-23 17:26:32+00:00
Wouldn't the example code:

from openai import OpenAI

client = OpenAI(
base_url="https://agentready.cloud/v1", # ← only change
api_key="ak_...", # AgentReady key
default_headers={
"X-Upstream-API-Key": "sk-..." # your OpenAI key
}
)

# Every call is now compressed automatically
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": your_long_prompt}]
)

provide you our OpenAI key (via the X-Upstream-API-Key header)?