MurphyA/hacker-news huggingface dataset:
by johnea | 2025-06-14 22:40:52+00:00
So, drone strike bombings are totally on topic, but US wing nut assassins shooting politicians, DHS tackling senators and arresting mayors, and the marines deployed to US cities, is all flagged out of existence.

It's been made quite clear, that HN is fundamentally a right wing-nut controlled forum.

I think there are a lot of woke-nut people in the mix as well, maybe even an equal amount, but the wing-nut mode of the highly bimodal distribution just flags anything that demonstrates that we've elected a criminal to the office of US president. Whereas the woke-nut mode is tolerant of allowing discussion to carry on, even on topics they don't agree with.

I guess it was to be expected, given the vulture capital origins of the platform...
by anon373839 | 2025-06-14 22:41:00+00:00
The term was coined by Andrej Karpathy on Twitter:

> There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists. It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper so I barely even touch the keyboard. I ask for the dumbest things like "decrease the padding on the sidebar by half" because I'm too lazy to find it. I "Accept All" always, I don't read the diffs anymore. When I get error messages I just copy paste them in with no comment, usually that fixes it. The code grows beyond my usual comprehension, I'd have to really read through it for a while. Sometimes the LLMs can't fix a bug so I just work around it or ask for random changes until it goes away. It's not too bad for throwaway weekend projects, but still quite amusing. I'm building a project or webapp, but it's not really coding - I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works.

https://xcancel.com/karpathy/status/1886192184808149383?lang...
Show HN: A reflex training web app built with Next.js and TypeScript
by itsk3nny | 2025-06-14 22:42:01+00:00
"Show HN: A reflex training web app built with Next.js and TypeScript I built a simple web app to test and improve reaction times. Features include: Reaction time measurement Global leaderboard Rank system based on performance Local storage for username persistence Tech stack: Next.js, TypeScript, Tailwind CSS https://reflex.kennyt.me Looking for feedback on the game mechanics and potential improvements."
by jakkos | 2025-06-14 22:42:04+00:00
> Manufacturers want to keep the sales boom that large cheap TVs brought when we moved away from CRTs. That was probably a “golden age” for screen makers.

IMO the difference between LCD and OLED is massive and "worth buying a new tv" over.

I've never tried doing an 8-bit vs 10-bit-per-color "blind" test, but I think I'd be able to see it?

> What really cheeses me on things like this is that TV and monitor manufacturers seem to gate the “blacker blacks” and “whiter whites” behind HDR modes and disable those features for SDR content. That is indefensible.

This 100%. The hackery I have to regularly perform just to get my "HDR" TV to show an 8-bit-per-color "SDR" signal with it's full range of brightness is maddening.
Show HN: I coded this AI visibility tool in VR (Meta Quest 3) – meet Winglytics
by ogulcanunal | 2025-06-14 22:42:24+00:00
Hey HN

I built Winglytics, a tool that scans your website and tells you how visible you are inside ChatGPT, Perplexity, Claude, and Gemini.

Get an AI Visibility Score

See if you're cited in LLMs

Track prompt rankings

Get LLM-ready content suggestions

Coded mostly inside a Meta Quest 3 headset using VR — because why not? Would love your feedback!

https://winglytics.com
by nico | 2025-06-14 22:42:27+00:00
The closest there is to a definition is the original Tweet by Karpathy[1]

However, if you go to /r/vibecoding (which has grown from 14k to 22k members in the last 3 weeks), it seems like any coding/programming you do, with assistance of AI, can be considered vibecoding there

Apparently, most people doing AI-assisted coding are developers, but there is also a rapidly-growing group of people that don't have a background in coding and are getting into it using AI

[1] https://substackcdn.com/image/fetch/w_1456,c_limit,f_webp,q_...
by majormajor | 2025-06-14 22:42:51+00:00
The example starting this discussion was not "avoid talking to a taxi driver." It was "book the taxi with an app at higher cost vs using the phone." No Waymos in Europe for them to avoid the drivers with just yet. Simply spending to avoid a phone call.

I'm skeptical we save a lot of time with our technology-mediated world. I think I could say "one medium pizza with pepperoni" and hear back "ok it'll be ready in 20 minutes" on a phone call quicker than I can put that order in with a device. Apps/websites are only better for group orders that require coordination. That's after I've picked out the restaurant, of course, but there is no shortage of literature on how the huge menu of choices presented by modern app-based services usually slows down people's decision making. (Amusingly this may swing back the other way, just with us talking to LLM-backed machines soon, but I find it hard to believe "we don't want to talk to the guy at the pizza place because we value our time THAT MUCH.") Compared to the phenomenon discussed in all sorts of media from https://www.reddit.com/r/memes/comments/15ecqat/phonephobia/ to https://www.thecut.com/article/psychologists-explain-your-ph... to https://www.cbsnews.com/newyork/news/gen-z-developing-fear-o...

Very curious if you have a source for that time value bit. I find it hard to believe. We Americans often have EXTREMELY long commutes using a mode of transportation that allows less multitasking than most others. I don't mind my car-based commute personally - it lets me listen to music in peace - but that's similar to how I don't mind making small talk while getting my hair cut - it's a peaceful respite from the usual noise of modern life. Certainly a nice change of pace from using that time to scroll social media or argue on the internet even more.
by Zigurd | 2025-06-14 22:43:12+00:00
This is the thing of it: "for most applications."

LLMs are not thinking. They way they fail, which is confidently and articulately, is one way they reveal there is no mind behind the bland but well-structured text.

But if I was tasked with finding 500 patents with weak claims or claims that have been litigated and knocked down, I would turn into LLMs to help automate that. One or two "nines" of reliability is fine, and LLMs would turn this previously impossible task into something plausible to take on.
by ashishb | 2025-06-14 22:43:53+00:00
I love Makefile. It is the easiest build system.

In my projects, whether the language is Go, Rust, Python, typescript, or even Android, there are standard make commands, if applicable, always work

- make format - make lint - make build - make docker_build - make docker_run

Once might migrate from one build system eg pipenv to poetry to uv, but the high level `make format` commands doesn't change.
by mickelsen | 2025-06-14 22:44:41+00:00
Hey. I also fell through the cracks during the pandemic, laid off at the height of the hiring market, but unable and unwilling to go back, developed tinnitus (gone, phew!), had cognitive issues too that really took a lot of time to improve, and I'm only in my 30s.

But it got better, and I'm in a better place now. It felt like I'd never get there; always tiny improvements but not quite there. Last year I finally felt the burnout gone. I stopped being so cynical. My life was better already, but still my mind was not quite there yet.

Now just this year I've rekindled my curiosity, using my free time again for little projects, not leaving piles of unfinished stuff around the house, it's something that's even noticeable from the outside - the little things. So now, moving forward, I take it easy, forgive myself, try again and don't subject myself to unattainable benchmarks.
by johnea | 2025-06-14 22:45:39+00:00
I live in California, the largest state in the continental US.

I know people that routinely travel in EVs between Mendocino county and San Diego county. Roughly the distance between NY and Georgia.

As far as the cold goes, somehow Norway is dealing with it, given they have the highest ratio of EVs of any country at this point. The battery tech is also catching up to this, and charge times in general, at least in China 8-/
by autobodie | 2025-06-14 22:46:02+00:00
> I'm also tired of people becoming parents without considering the financial aspects ahead of time. If you're making minimum wage and are barely surviving, don't have kids until you're on steadier ground.

Young is abolutely the best age to have kids. Ask biology.

If you want a society (I do) then you want a society that supports people having children.

If you want a healthy society (I do) then you want a society that supports people having children at a young age.
by em-bee | 2025-06-14 22:46:39+00:00
almost all packages in any linux distribution are not created by the actual developers of the applications. this is what linux distributions do. they take applications they find useful and package them for their distribution. i have been a maintainer of such packages myself.

this behavior is expected and what you want because you probably don't want to keep up with all the distributions out there and maintain packages of your application for them. most distributions also won't allow you to submit a package unless you are a verified member of their packaging team.

consider those packagers as contributors to your application
by wongarsu | 2025-06-14 22:46:51+00:00
There are already inference providers like DeepInfra or inference.net whose entire business model is hosted inference of open-source models. They promise not to keep or use any of the data and their business model has no scaling effects, so I assume they are already charging a fair market rate where the price covers the costs and returns a profit.

The GPU market will probably take a hit. But the flip side of that is that the market will be flooded with second-hand enterprise-grade GPUs. And if Nvidia needs sales from consumer GPUs again we might see more attractive prices and configurations there too. In the short term a market shock might be great for hobby-scale inference, and maybe even training (at the 7B scale). In the long term it will hurt, but if all else fails we still have AMD who are somehow barely invested in this AI boom
by woopsn | 2025-06-14 22:46:51+00:00
If the claims about AI were that it is a great or even incredible chat app, there would be no mismatch.

I think normal people understand curing all disease, replacing all value, generating 100x stock market returns, uploading our minds etc to be hype.

I said a few days ago, LLM is amazing product. Sad that these people ruin their credibility immediately upon success.
by thomasahle | 2025-06-14 22:47:00+00:00
> 1. Humans have trouble with complex problems and memory demands. True! But incomplete. We have every right to expect machines to do things we can’t. [...] If we want to get to AGI, we will have to better.

I don't get this argument. The paper is about "whether RLLMs can think". If we grant "humans make these mistakes too", but also "we still require this ability in our definition of thinking", aren't we saying "thinking in humans is a illusion" too?
by nico | 2025-06-14 22:47:24+00:00
> Startups would struggle to attract investors without developers building complex systems, he said

As long as the startups can get traction, grow quickly and/or generate money, it doesn't matter if they used AI to build it. That might attract investors even more... a super lean company that can go to market faster and gain a lot of ground, before needing big bucks for hiring a heavier development team... that sounds pretty good
by FINDarkside | 2025-06-14 22:50:37+00:00
I don't think most of the objections are poor at all apart from 3, it's this article that seems to make lots of strawmans. Especially the first objection is often heard because people claim "this paper proves LLMs don't reason". The author moves goalposts and is arguing against about whether LLMs lead to AGI, which is already a strawman for those arguments. And in addition, he even seems to misunderstand AGI, thinking it's some sort of super intelligence ("We have every right to expect machines to do things we can’t"). AI that can do everything at least as good as average human is AGI by definition.

It's especially weird argument considering that LLMs are already ahead of humans in Tower of Hanoi. I bet average person will not be able to "one-shot" you the moves to 8 disk tower of Hanoi without writing anything down or tracking the state with the actual disks. LLMs have far bigger obstacles to reaching AGI though.

5 is also a massive strawman with the "not see how well it could use preexisting code retrieved from the web" as well, given that these models will write code to solve these kind of problems even if you come up with some new problem that wouldn't exist in its training data.

Most of these are just valid the issues in the paper. They're not supposed to be some kind of arguments that try to make everything the paper said invalid. The paper didn't really even make any bold claims, it only concluded LLMs have limitations in its reasoning. It had a catchy title and many people didn't read past that.
by majormajor | 2025-06-14 22:51:02+00:00
Yeah it sounds like "LLMs are bad at interacting with lay humans compared to being prompted by experts or being given well-formed questions like from licensing exams."

Feels to me like how two years ago "prompt engineering" got a bunch of hype in tech companies, and now is nonexistent because the models began being trained and prompted specifically to mimic "reasoning" for the sorts of questions tech company users had. Seems like that has not translated to reasoning their way through the sort of health conversations a non-medical-professional would initiate.
by gjm11 | 2025-06-14 22:52:57+00:00
No specific critique here other than "it was written by an LLM and this seems worth pointing out given that LLMs are bad at actually understanding difficult mathematics".

(In a different comment I make some actual criticisms of what you wrote. I see you replied to my comment there, and that's a more appropriate place to discuss actual ideas. I don't see much point in criticizing LLM output in a field LLMs are bad at.)

Anyway: (1) no, it wasn't clear. I wouldn't generally take "I nerd-sniped myself. Here's a more fleshed-out sketch of ..." to mean "Here's something written for me by an LLM". I'd take it to imply that the person had done the fleshing-out themself. And (2) no, the problem wasn't that you used words I don't understand. It's certainly possible that your ideas are excellent and I just don't understand them, but I'm a mathematician myself and none of the words scare me.
by sshine | 2025-06-14 22:53:26+00:00
I read ESR’s jargon files as a teenager and was very inspired. It wasn’t until a week ago that I learned about the original hacker’s dictionary via the Scheme community. Interestingly, the preserved copy comes with this preamble addressing ESR’s copy:

[This file, jargon.txt, was maintained on MIT-AI for many years, before being published by Guy Steele and others as the Hacker's Dictionary. Many years after the original book went out of print, Eric Raymond picked it up, updated it and republished it as the New Hacker's Dictionary. Unfortunately, in the process, he essentially destroyed what held it together, in various ways: first, by changing its emphasis from Lisp-based to UNIX-based (blithely ignoring the distinctly anti-UNIX aspects of the LISP culture celebrated in the original); second, by watering down what was otherwise the fairly undiluted record of a single cultural group through this kind of mixing; and third, by adding in all sorts of terms which are "jargon" only in the sense that they're technical. This page, however, is pretty much the original, snarfed from MIT-AI around 1988. -- jpd.]

https://www.dourish.com/goodies/jargon.html
by thomasahle | 2025-06-14 22:53:58+00:00
> 5. A student might complain about a math exam requiring integration or differentiation by hand, even though math software can produce the correct answer instantly. The teacher’s goal in assigning the problem, though, isn’t finding the answer to that question (presumably the teacher already know the answer), but to assess the student’s conceptual understanding. Do LLM’s conceptually understand Hanoi? That’s what the Apple team was getting at. (Can LLMs download the right code? Sure. But downloading code without conceptual understanding is of less help in the case of new problems, dynamically changing environments, and so on.)

Why is he talking about "downloading" code? The LLMs can easily "write" out out the code themselves.

If the student wrote a software program for general differentiation during the exam, they obviously would have a great conceptual understanding.
by AndyKelley | 2025-06-14 22:55:08+00:00
That's fully expected - consider when you do multiple things at the same time, it necessarily requires separate memory.

For a simple example consider if you are editing a photo. Your photo editing application requires X amount of memory. Now you leave that running and begin editing a second photo at the same time. To do this requires somewhere between X and X * 2 amount of memory, depending on how much application state can be shared between the two instances.
by hedora | 2025-06-14 22:55:24+00:00
The $3 often makes the difference between someone that should not be allowed to have a drivers license, and a someone that's been driving high-end limos for years.

For example, I once had a driver that heard regenerative breaking was good for fuel economy, so decided to cycle their busted prius between 60mpg and 70mph every few seconds on the freeway. I was carsick for 2 hours after that ride. Another time, I had an angry line of people tapping the windows and politely giving the driver some unsolicited advice. (The mob was right; I mostly just tried to hide my face.)

So, the $3 is a big problem, but has nothing to do with money.
by majormajor | 2025-06-14 22:57:10+00:00
Where are you getting that from? (And again, no more "human in the loop" in "reading WebMd" than "talk to chatbot.")

> Participants using an LLM identified relevant conditions less consis- tently than those in the control group, identifying at least one relevant condition in at most 34.5% of cases compared to 47.0% for the control.

So good old "do your own research" (hardly a gold standard, still, too, at 47%) is doing like 35% better for people than "talk to the chatbot."

The more interesting part is:

> We found that the LLMs suggested at least one relevant condition in at least 65.7% of conversations with participants [...] with observed cases of participants providing incomplete information and LLMs misinterpreting prompts

since this is nearly double the rate at which participants actually came away with a relevant condition identification, suggesting that the bots are way worse at the interactions than they are at the information. That's presumably trainable, but it also requires a certain patience and willingness on the part of the human, which seems like a bit of a black art for a machine to be able to learn how to coax out of everyone all the time.

But it's not just a failure to convince, it's also a failure to elicit the right information and/or understand it - the LLM being prompted in a controlled fashion, vs having to have a conversation with the participant, found at least one relevant condition even more often still!
by paulgb | 2025-06-14 23:01:10+00:00
> Their determination? I wasn't entitled to a $3 refund.

Frustratingly, Lyft’s position on this is that if you don’t like the car that arrives you should reject it when it arrives, otherwise you’re not entitled to a (even partial) refund, even when they know on their end that the car they sent doesn’t match what you paid extra for.
by wongarsu | 2025-06-14 23:01:18+00:00
That's an interesting result. I would love to see a follow-up with two control groups: humans with assistance from an LLM, humans with assistance from a doctor and humans with no assistance.

This study tells us that LLM assistance is as good as no assistance, but any investigation of the cause feels tainted by the fact that we don't know how much a human would have helped.

If we believe the assertion that LLMs are on a similar level as doctors on finding the conditions on their own, does the issue appear in the description the humans give the LLM, the way the LLM talks to the human, or the way the human receives the LLM suggestions? When looking at chat transcripts they seem to identify issues with all three, but there isn't really a baseline on what we would consider "good" performance
by bryanrasmussen | 2025-06-14 23:01:24+00:00
OK maybe, although not having experience to describe it sounds somewhat worrisome for a scientific project.

where your point 1 is concerned, again, since the brain has many redundancies one can totally have brain tissue destroyed and with some slight therapy get back to normal functionality, but when Alzheimer's is too advanced I suppose you will not be able to fully revert, but maybe revert to some earlier stage - sure.
by spondylosaurus | 2025-06-14 23:03:07+00:00
IIRC the birth control and migraine relationship is twofold: (1) unlike traditional BC pills, mini-pills don't contain estrogen, which is beneficial because of the link between estrogen and migraine frequency; and (2) unlike most traditional BC pills, most mini-pills are "monophasic," which means you have less dramatic hormonal fluctuations throughout each cycle.

I do know some people see an improvement on migraines even on traditional BC, but the hierarchy is pretty much: nothing < traditional BC < mini-pills.
by ThrowawayR2 | 2025-06-14 23:04:33+00:00
There is a link at the bottom of the page to the HN guidelines (https://news.ycombinator.com/newsguidelines.html) which says:

"Off-Topic: Most stories about politics, or crime, or sports, or celebrities, unless they're evidence of some interesting new phenomenon. Videos of pratfalls or disasters, or cute animal pictures. If they'd cover it on TV news, it's probably off-topic."

Some have tried to argue that these stories gratify intellectual curiosity and are therefore on topic but this view does not seem to have been accepted by the site moderators or user base.
by gjm11 | 2025-06-14 23:04:34+00:00
The comment you're replying to already explained what aleph, beth and Betti numbers are. (But a few nitpicks: 1. Beth numbers are not ordinals, they're cardinals. They're indexed by ordinals, just as the alephs are, but if that's what you care about why not use the ordinals themselves? 2. I'm not seeing how you get from "Beth numbers are indexed by ordinals" to "they generalize infinitesimals" to "you can think of them as a dual". Not saying there isn't something there, but I think you could stand to unpack it a bit if so. 3. Betti numbers are not only for persistent (co)homology; they were around long before anyone had thought of persistent (co)homology.)

It's certainly possible (as I explicitly said before) that my bad-math-alarms have hit a false positive here. You haven't convinced me yet, for what it's worth. (You need not, of course, care whether you convince me or not. It's not as if my opinion is likely to have any effect on you beyond whatever you might feel about it.)