MurphyA/hacker-news huggingface dataset:
by phatskat | 2025-09-26 16:11:38+00:00
> Why would I care about "commit A", "change parts of A because I misunderstood a requirement", "improve A based on code review" etc.?

For me it’s because Feature A may largely be fine but one of those intermediary commits introduced a regression. I can bisect and isolate an issue much more easily if I have the full history to step through as opposed to “this big commit intrigued a one-line regression _somewhere_ in a 900 line commit”
by AnotherGoodName | 2025-09-26 16:12:33+00:00
I've started making sure my codebase is "LLM compatible". This means everything has documentation and the reasons for doing things a certain way and not another are documented in code. Funnily enough i do this documentation work with LLMs.

Eg. "Refactor this large file into meaningful smaller components where appropriate and add code documentation on what each small component is intended to achieve." The LLM can usually handle this well (with some oversight of course). I also have instructions to document each change and why in code in the LLMs instructions.md

If the LLM does create a regression i also ask the LLM to add code documentation in the code to avoid future regressions, "Important: do not do X here as it will break Y" which again seems to help since the LLM will see that next time right there in the portion of code where it's important.

None of this verbosity in the code itself is harmful to human readers either which is nice. The end result is the codebase becomes much easier for LLMs to work with.

I suspect LLM compatibility may be a metric we measure codebases in the future as we learn more and more how to work with them. Right now LLMs themselves often create very poor LLM compatible code but by adding some more documentation in the code itself they can do much better.
by sobiolite | 2025-09-26 16:12:46+00:00
> Nakamura responded to Kramnik’s allegations by arguing that focusing on a particular streak while ignoring other games was cherry-picking. The researchers note that there’s a problem with this argument, too, as it violates the likelihood principle. This principle tells us the interpretation should only rely on the actual data observed, not the context in which it was collected.

I don't quite understand this objection? If I won the lottery at odds of 10 million to 1, you'd say that was a very lucky purchase. But if it turned out I bought 10 million tickets, then that context would surely be important for interpreting what happened, even if the odds of that specific ticket winning would be unchanged?
by hedora | 2025-09-26 16:12:50+00:00
> Trans people being an issue.

The transcript of Charlie Kirk's last words are particularly telling on this point. He was pushing the idea that trans people are to blame for mass shootings when they were < 1% of total mass shooters over the last ten years.

https://www.yahoo.com/news/articles/fact-check-yes-charlie-k...
by stockresearcher | 2025-09-26 16:13:01+00:00
To be honest, I am not sure that the hand of god play was offsides! The final touch before Maradona gets it is not clearly a "deliberate play" by the defender. Maradona is not in an offsides position on the final touch by a teammate.

I'm sure that the offside law has been "refined" between 1986 and now, but this is the law as of today and there is a huge difference between touches by teammates and defenders:

https://www.theifab.com/laws/latest/offside/#offside-offence
by kypro | 2025-09-26 16:13:02+00:00
I'm hitting 'x' to doubt hard on this one.

The ICPC is a short (5 hours) timed contest with multiple problems, in which contestants are not allowed to use the internet.

The reason most don't get a perfect score isn't because the tasks themselves are unreasonably difficult, but because they're difficult enough that 5 hours isn't a lot of time to solve so many problems. Additionally they often require a decent amount of math / comp-sci knowledge so if you don't know have the knowledge necessary you probably won't be able complete it.

So to get a good score you need lots of math & comp-sci knowledge + you need to be a really quick coder.

Basically the consent is perfect for LLMs because they have a ton of math and comp-sci knowledge, they can spit out code at super human speeds, and the problems themselves are fairly small (they take a human maybe 15 mins to an hour to complete).

Who knows, maybe OP is right and LLMs are smart enough to be super human coders if they just had the right context, but I don't think this example proves their point well at all. These are exactly the types of problems you would expect a supercharged auto-complete would excel at.
by bluefirebrand | 2025-09-26 16:13:53+00:00
> In engineering I treat it like a junior intern that is very fast, has memorized a huge amount of info, but makes mistakes and has to be hand-held and anything they produce must be examined and tested

So you spend your own experienced dev time chasing down a high volume of junior dev mistakes instead of writing high quality experienced dev code?

Sorting through large amounts of junior intern code does not seem like a valuable use of an experienced dev's time.
by magicalhippo | 2025-09-26 16:15:14+00:00
I asked Gemini 2.5 Flash to just write me a function to do it, and it used regex.

In a separate chat, I asked it to suggest some ways to do it first, and it provided three alternatives, but suggested I started with regex.

FWIW I used Open WebUI, which uses the API (via OpenRouter). I've seen people here mentioning that the API produces much better results than the chat app, for whatever reason.

For reference, here's prompt and the zero-shot result, minus the rigorous comments it added:

I need a Python function that will take in markdown in a string and return a string with ansi codes for bold, italics and underline. Can you write me such a function?

import re def markdown_to_ansi(markdown_string: str) -> str: ansi_string = markdown_string ANSI_BOLD = "\033[1m" ANSI_ITALIC = "\033[3m" ANSI_UNDERLINE = "\033[4m" ANSI_RESET = "\033[0m" ansi_string = re.sub(r'\*\*(.*?)\*\*', f'{ANSI_BOLD}\\1{ANSI_RESET}', ansi_string) ansi_string = re.sub(r'__(.*?)__', f'{ANSI_BOLD}\\1{ANSI_RESET}', ansi_string) ansi_string = re.sub(r'\*(.*?)\*', f'{ANSI_ITALIC}\\1{ANSI_RESET}', ansi_string) ansi_string = re.sub(r'\_(.*?)\_', f'{ANSI_ITALIC}\\1{ANSI_RESET}', ansi_string) ansi_string = re.sub(r'\+\+(.*?)\+\+', f'{ANSI_UNDERLINE}\\1{ANSI_RESET}', ansi_string) # A more robust solution for nesting would require a parsing library or a more complex state machine. # However, for simple cases, applying in order can layer them correctly. return ansi_string
by phatskat | 2025-09-26 16:15:16+00:00
I tend to read intermediate commits because it can be helpful in understanding how the engineer thought through developing the feature. This is especially informative when reviewing more junior/mid-level code, or when a feature grows beyond what I would consider acceptable scope - obviously, avoiding these kinds of branches is the ideal state, and unfortunately the realty doesn’t let me always push back for smaller PRs.
Show HN: DevToolsHub – A curated directory of free developer tools
by guomengtao | 2025-09-26 16:15:26+00:00
I built DevToolsHub as a simple, curated directory of free developer tools. The idea is to save developers time by collecting useful resources in one place, instead of searching across the web. It’s lightweight, free, and I’m continuously expanding the list. Feedback and suggestions are welcome!
by psunavy03 | 2025-09-26 16:15:38+00:00
The fact that this person put a snarky (???) next to the concept of measuring airspeed in knots makes me wonder just how familiar they are with aerospace in general. A knot is a standard measurement in part because one nautical mile is equal to one minute of latitude. Which is useful until the day we decide to start measuring lat/long in radians.

I know it's fashionable in some circles to dump on everything non-metric, but these things are they way they are because of reasons, and airspeed is generally measured in either knots or Mach.
by molvqingtai | 2025-09-26 16:15:50+00:00
When developing browser extensions with React, you often need to inject React components into host web pages. However, the target mounting points in these pages are frequently dynamic - they may not exist when your extension loads, or they might be created and destroyed as users navigate and interact with the page.

React Magic Portal solves these challenges by automatically detecting when target elements appear or disappear in the DOM, ensuring your React components are always rendered in the right place at the right time.
by loudmax | 2025-09-26 16:16:04+00:00
LLMs certainly don't experience time like we do. They live in a uni-dimensional world that consists of a series of tokens (though it gets more nuanced if you account for multi-modal or diffusion models). They pick up some sense of ordering from their training data, such as "disregard my previous instruction," but it's not something they necessarily understand intuitively. Fundamentally, they're just following whatever patterns happen to be in their training data.
by hirako2000 | 2025-09-26 16:16:18+00:00
How has it ever worked. I have thousands of threads with various LLMs, none have that role play cue, yet the responses always sound authoritative and similar to what one would find in literature written by experts in the field.

What does work is to provide clues for the agent to impersonate a clueless idiot on a subject, or a bad writer. It will at least sound like it in the responses.

Those models have been heavily trained with RLHF, if anything today's LLMs are even more likely to throw authoritative predictions, if not in accuracy, at least in tone.
by ThrowawayR2 | 2025-09-26 16:16:27+00:00
I'm pretty sure it's not. There's over half a dozen entries in the HN guidelines that ask for thoughtful and insightful posts and not "flippant criticism":

"Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes.

Comments should get more thoughtful and substantive, not less, as a topic gets more divisive.

Don't be curmudgeonly. Thoughtful criticism is fine, but please don't be rigidly or generically negative.

Please don't fulminate. Please don't sneer, including at the rest of the community.

Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith.

Eschew flamebait. Avoid generic tangents. Omit internet tropes.

Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something.

Please don't pick the most provocative thing in an article or post to complain about in the thread. Find something interesting to respond to instead."
by cameldrv | 2025-09-26 16:16:48+00:00
Yeah the biggest idea was essentially to do the scheduling of instructions upfront in the compiler instead of dynamically at runtime. By doing this, you can save a ton of die area for control and put it into functional units doing math etc.

The problem as far as I can tell as a layman is that the compiler simply doesn't have enough information to do this job at compile time. The timing of the CPU is not deterministic in the real world because caches can miss unpredictably, even depending on what other processes are running at the same time on the computer. Branches also can be different depending on the data being processed. Branch predictors and prefetchers can optimize this at runtime using the actual statistics of what's happening in that particular execution of the program. Better compilers can do profile directed optimization, but it's still going to be optimized for the particular situation the CPU was in during the profile run(s).

If you think of a program like an interpreter running a tight loop in an interpreted program, a good branch predictor and prefetcher are probably going to be able to predict fairly well, but a statically scheduled CPU is in trouble because at the compile time of the interpreter, the compiler has no idea what program the interpreter is going to be running.
by kerpal | 2025-09-26 16:17:06+00:00
The product/website itself is interesting as a founder who believes heavily in implementing simulations to rigourously test complex systems. However I noticed lots of screenshots and less substance about how it actually works. If your ICP is technical, the frontend and marketing shouldn't be overdone IMO.

I need substance and clear explanations of models, methodology, concepts with some visual support. Screenshots of the product are great but a quick real or two showing different examples or scenarios may be better.

I'm also skeptical many people who are already technical and already using AI tools will now want to use YOUR tool to conduct simulation based testing instead of creating their own. The deeper and more complex the simulation, the less likely your tool can adapt to specific business models and their core logic.

This is party of the irony of AI and YC startups, LOTS of people creating this interesting pieces of software with AI when part of the huge moat that AI provides is being able to more quickly create your own software. As it evolves, the SaaS model may face serious trouble except in the most valuable (e.g. complex and/or highly scalable) solutions already available with good value.

However simulations ARE important and they can take a ton of time to develop or get right, so I would agree this could be an interesting market if people give it a chance and it's well designed to support different stacks and business logic scenarios.
by nico | 2025-09-26 16:17:07+00:00
You can definitely build an agent and have it use tools like you mention. That’s the equivalent of making 2 requests to Gemini, one to get the initial answer/content, then another to get it formatted as proper json

The issue here is that Gemini has support for some internal tools (like search and web scraping), and when you ask the model to use those, you can’t also ask it to use application/json as the output (which you normally can when not using tools)

Not a huge issue, just annoying
by tracker1 | 2025-09-26 16:17:25+00:00
Can't speak for GP, but in the 5-6 months or so I've been using it, most of my issues have been with keyboard navigation breaking or not working in some of the apps. It's gotten better with regular updates though and has been pretty solid. Other stability issues seem to have been deeper as since switching to a mainline kernel install (6.16.x) I haven't noticed any deep issues.

Pop has kept kernel updates well ahead of Ubuntu though, I just switched sooner than they seem to have.
by parliament32 | 2025-09-26 16:17:48+00:00
Meh, one could also complain they don't have control over backbone networks, transit, peering agreements, and intermediary routing therefore hosting a service on k8s is futile without using a managed provider / PaaS.

> People say "I don't have deliverability problems!" but how do you know?

Because people reply to my emails.. because I email documents to family/friends/landlord/etc and they receive it as expected..

> Most places don't tell you they rejected your email.

Of course they do, this is what DMARC is for.
by mellosouls | 2025-09-26 16:17:52+00:00
Original @simonw article here:

https://simonw.substack.com/p/the-lethal-trifecta-for-ai-age...

https://simonwillison.net/2025/Aug/9/bay-area-ai/

Discussed:

https://news.ycombinator.com/item?id=44846922
by mft_ | 2025-09-26 16:18:08+00:00
> It's not that good for top-level chess because a Magnus or Hikaru or basically anyone in the top few hundred players can bang out a series of extremely accurate moves in a critical spot - that's why they're top chess players, they're extremely good.

Interesting; I thought I'd read that even the very best players only average ~90% accuracy, whereas the best engines average 99.something%?
by Nursie | 2025-09-26 16:19:29+00:00
Agreed, but unfortunately at times when things seem not to be going so well in general, people are prone to electing the person that promises them large positive changes by throwing out the stale old rulebook. Even if it’s not credible. Even when large parts of what’s apparently going wrong have been invented by that same bad actor…

I think this is part of why Brexit got through as well, some people felt it was a way to shake up a crusty, unresponsive establishment. That didn’t go so great!
by ISL | 2025-09-26 16:19:49+00:00
If not now, soon, the bottleneck will be responsibility. Where errors in code have real-world impacts, "the agentic system wrote a bug" won't cut it for those with damages.

As these tools make it possible for a single person to do more, it will become increasingly likely that society will be exposed to greater risks than that single person's (or small company's) assets can cover.

These tools already accelerate development enough that those people who direct the tools can no longer state with credibility that they've personally reviewed the code/behavior with reasonable coverage.

It'll take over-extensions of the capability of these tools, of course, before society really notices, but it remains my belief that until the tools themselves can be held liable for the quality of their output, responsibility will become the ultimate bottleneck for their development.
by maxdevai | 2025-09-26 16:19:50+00:00
VoiceMeetAI is a Chrome extension that provides real-time AI coaching during video interviews. I built it for interview anxiety and it's genuinely helped, but has limitations worth discussing.

What works well: - Real-time question transcription - Structured response suggestions for behavioral questions - Confidence boost from having backup - Privacy-focused architecture

Current limitations: - Occasional transcription errors in noisy environments - Generic responses for highly specific technical questions - Works better for behavioral than deep technical interviews - Still requires good judgment about when/how to use suggestions

Used it successfully in 4 recent interviews (3 offers), but it's a tool that augments preparation—not a replacement for actually knowing your stuff.

Technical challenges were fascinating: sub-3-second latency requirements, cross-platform audio handling, privacy constraints.

Sharing because interview anxiety is common among developers but rarely addressed with practical tools.

Try it: https://voicemeetai.com

What features would make AI interview assistance more helpful?
by cameldrv | 2025-09-26 16:19:53+00:00
The DEC Alpha actually did provide very good performance, and you could even run Windows NT on it. As far as I can tell, the biggest problem was just that Alpha systems were very expensive, and so they had a limited customer base. There were some quirks, but the main thing was just that you'd be paying $2000 for a PC and $10,000 for an Alpha based system, and most people didn't need the performance that badly.
Show HN: I built a website to visualize Terraform code using Claude AI
by autotune | 2025-09-26 16:19:55+00:00
Wondering if I can get some opinions on it. Already aware the icons could use some work. Built with AWS S3 and AWS Amplify hosting so it stays super cheap as all assets are static for the time being. Built using Claude AI. Kept having to re-explain at times to avoid bugs. Very interesting what you can do with Claude AI prompt engineering with just an idea.
by moffkalast | 2025-09-26 16:20:07+00:00
That's not how attention works though, it should be perfectly able to figure out which parts are important and which aren't, but the problem is that it doesn't really scale beyond small contexts and works on a token to token basis instead of being hierarchical with sentences, paragraphs and sections. The only models that actually do long context do so by skipping attention layers or doing something without attention or without positional encodings, all leading to shit performance. Nobody pretrains on more than like 8k, except maybe Google who can throw TPUs at the problem.
by chickenpotpie | 2025-09-26 16:20:58+00:00
At least in the short term, I think the economics will prevent stores from using this for marketing data. Operating these drones has to very, very expensive and I don't think knowing about your driving habits for a few miles is worth the cost.

The only reason these things could be economical in the short term is because theft costs retail companies an insanely high amount of money.

However, this might change if these drones become cheaper to operate and purchase.

I would think there's some crime that would prevent people from using these to the extremes. I am almost certain it's illegal to put an air tag on someone to track their whereabouts and I would also think those laws would apply here.
by unquietwiki | 2025-09-26 16:21:02+00:00
Hey there. Came across this a while ago, but glad to see it alive & kicking. Two questions...

1. Is there going to be a disk image/installer for 25.08, or is that supposed to be self-compiled?

2. Does the OS download missing components on its own or something? The 25.04 image on the website is only 30+ MB.

Thanks!
by DoctorOW | 2025-09-26 16:21:09+00:00
> Is this fictitious Nazi working with a fictitious Jewish person acting on those views or discussing them at work?

There's a reason I say "ticking time bomb" in my comment. Hypothetical Jewish person keeps kosher for instance. Is that "acting on" being Jewish at work? What about wearing a yarmulke? If that is, how do you rectify it? If you allow yarmulke, is a swastika armband okay? Both are clothing choices depicting "views".
by hedora | 2025-09-26 16:21:21+00:00
Basically, take any transcript from the election where JD Vance or Trump said they were going to fix some US domestic crisis that Biden had created.

They were lying through their teeth. Biden had already fixed the crisis. Trump's undone that work, and is now going around claiming to have fixed stuff.

One example is how Trump is going to get a bunch of people to build factories in the US:

https://fred.stlouisfed.org/series/C307RC1Q027SBEA

Biden also got the inflation caused by Trump's ZIRP + deficit spending under control, despite digging us out of COVID. (The inflation surge during Biden's term had already been predicted by most economists by the middle of Trump's first term. NPR even ran a series about "printing unlimited money bad" in 2018 or 2019.)

Also, Trump inherited the lowest crime rates in living memory, and then declared a national emergency about surging crime.
by jofla_net | 2025-09-26 16:21:26+00:00
Relax friend! I can't see why you'd be peeved in the slightest! Remember, the CEOs have it all figured out and have 'determined' that we don't need all those eyeballs on the code anymore. You can simply 'feed' the machine and do the work of forty devs! This is the new engineering! /s
by exmadscientist | 2025-09-26 16:21:37+00:00
Soldering does not generate metal vapor. Soldering fumes are burnt flux residues, which are often acidic and quite nasty.

Laser cutting or engraving makes even worse fumes and requires seriously good filtering. I personally think they're nasty enough that it is irresponsible to just dump this stuff outside into the environment without cleanup but it's certainly better than breathing it.
by binary132 | 2025-09-26 16:21:47+00:00
In my opinion human beings also do not have unlimited cognitive context. When a person sits down to modify a codebase, they do not read every file in the codebase. Instead they rely on a combination of working memory and documentation to build the high-level and detailed context required to understand the particular components they are modifying or extending, and they make use of abstraction to simplify the context they need to build. The correct design of a coding LLM would require a similar approach to be effective.