MurphyA/hacker-news huggingface dataset:
by edg5000 | 2025-08-13 07:00:20+00:00
I encourage you to try and really lean on LLMs (Claude Code in particular), it's hard to argue that there is no productivity boost. Athropy in "low level" skills is certainly real though. But our ancestors knew how to repair a pair of socks. Due to industrialisation, we just buy new ones and have lost the skills to repair them. Most people may forget how to do many things in programming, but may still intimately understand, at a high level, what each line is doing.
by chrisco255 | 2025-08-13 07:00:32+00:00
I literally said "one of the highest" not the absolute highest. Being in a top 10 or 20 list on murder rates is not an achievement to strive for, but it absolutely places you in upper echelon of murder. DC has had 100 murders so far in 2025, just 12 shy of 2024 with 3.5 months to go: https://mpdc.dc.gov/dailycrime

St. Louis situation is absolutely abysmal. 20 is way too high, 69 is way too high. These are 3rd world numbers that are absolutely inexcusable. And we're only talking about murders here, if you look into other violent crime data, it's also substantial for D.C.

The FBI frequently gets involved in murder cases all over the country, there are field offices everywhere. States are significantly different things than the special federal District of Columbia. There, it is generally up to the Governor to deploy the national guard, although plenty of exceptions and precedents exist for the President to do so.
by energy123 | 2025-08-13 07:00:41+00:00
You could probably build a decent agentic harness that achieves something similar.

Show the LLM a tree and/or call-graph representation of your codebase (e.g. `cargo diagram` and `cargo-depgraph`), which is token efficient.

And give the LLM a tool call to see the contents of the desired subtree. More precise than querying a RAG chunk or a whole file.

You could also have another optional tool call which routes the text content of the subtree through a smaller LLM that summarizes it into a maximum density snippet, which the LLM can use for a token efficient understanding of that subtree during early the planning phase.

But I'd agree that an LLM built natively around AST is a pretty cool idea.
by Telaneo | 2025-08-13 07:00:49+00:00
The list's probably going to get a lot longer. I wonder how it's going to compare to the list of sites who block Europeans due to GDPR concerns. I've only ever noticed two sites that did that, even though the amount of noise from Americans was not insubstantial. The OSA is a lot more invasive than the GDPR though.
by crystal_revenge | 2025-08-13 07:01:44+00:00
AI feels different because quietly we are all aware, to differing degrees of comfort, that the world around us is collapsing. We see the escalating effects of climate change impacting day-to-day life in ways we were told would only happen in the far future, witnessing genocide become a normal part of the news critique of which can mean serious personal consequences, we're watching the United States transform into State Capitalism [0] making our country far more like modern day China than many of us would have ever imagined possible.

And we deeply need to believe something wonderous, whether delightful or terrifying, is also happening. I honestly think AI is largely mass hallucination which is supported by a system that is able to extract tremendous wealth from this hallucination continuing.

We can no longer believe that everything happening is normal, so we need to inject some, slightly less horrific, explanation for what we're experiencing.

0. https://www.wsj.com/economy/the-u-s-marches-toward-state-cap...
by scrapeops | 2025-08-13 07:02:54+00:00
Web scraping has evolved from a niche hobby into a foundational technique used across industries from market research and competitive intelligence to SEO, finance, and AI training data pipelines. But as scraping grows in scale and complexity, developers often find themselves drowning in operational overhead: failed requests, proxy bans, missed jobs, scheduling chaos, and zero visibility into what went wrong.

Enter ScrapeOps a purpose-built DevOps platform that transforms how developers manage scraping infrastructure, debug scrapers, and scale reliable data pipelines without burning cycles on boilerplate.

The Modern Web Scraping Problem While libraries like Scrapy, Playwright, and Selenium offer flexible tools for data extraction, they leave massive operational gaps once you're scraping at scale:

Scrapers fail silently or get blocked without alerts.

Requests are black-boxed—if it fails, you don’t know why.

Proxy juggling becomes an engineering headache.

CI/CD pipelines lack scraper-specific tooling.

Monitoring, retry logic, and scheduling are cobbled together manually.

These problems aren't just annoying, they're costly. Failed scrapes can derail data-dependent products, delay deliveries, and cause silent business blindspots.
by ehnto | 2025-08-13 07:03:02+00:00
Of course, but even those blackoxes are not empty, they've got a vague picture inside them based on prior experience. I have been doing this for a while so most things are just various flavours of the same stuff, especially in enterprise software.

The important thing in this context is that I know it's all there, I don't have to grep the codebase to fill up my context, and my understanding of the holistic project does not change each time I am booted up.
by qcnguy | 2025-08-13 07:03:07+00:00
LLMs are good at copy editing. They recognize when words are misspelled or grammar is poor very easily, despite not being able to see individual letters.

For understanding the guy's point it helps if you know anything about Heather Cox Richardson. Merely saying her copyeditors could be replaced by AI is a gross minimization, probably most of her own work could be too.

HCRs newsletter is popular because she delivers much purer, harder Trump Derangement Syndrome than anyone else on the market. That's it, that's the entire secret to her success. She delivers an ordinary and easily LLMable service (summarizing news), but ramps the Trump hate up orders of magnitude. Her competitive edge is she delivers to a market of liberals who find themselves disgusted with the mainstream journalism because, as they see it, it tries much too hard to be neutral and unbiased. It's sort of like how the Guardian makes millions off of donations by being a very openly left wing paper, except 1000x more extreme.

One might think US journalism is not particularly neutral, but they claim they are, so if you reject the whole notion that journalism should be unbiased as idiotic appeasement the market doesn't have much for you. Into this gap steps Heather Cox Richardson, a humanities academic who for a low low price will send you a daily news report that, every day, tells you how evil and bad Trump is and how good a person you are for realizing that.

Go read some of her reports and then tell us an LLM couldn't write them cold, I dare you. It probably wouldn't even need to be a big LLM. Summarization and rewrites are things they're really good at. She never even cites sources and hallucinations aren't the sort of thing her customer base are going to notice.
by hulitu | 2025-08-13 07:04:21+00:00
> The root cause: Google’s new aapt2 binary in AGP 8.12.0 started requiring CPU instructions (SSE4.1, SSSE3) that F-Droid’s build farm hardware doesn’t support.

Very intelligent move from Google. Now you can't compile "Hello World" without SSE4.1, SSSE3. /s

Are there any X86 tablets with Android ?
by vintermann | 2025-08-13 07:04:38+00:00
I'm not a car person, but I can sort of relate. I have a vintage computer, a Commodore 64. I am absolutely tempted to buy other vintage computers - For instance I see old Norwegian Tiki-100 machines for sale on occasion.

But I know these machines require a bit more electronics work to not become self-destructive due to various aging components (one memorably caught fire during a demo event a few years ago). Work I'm honestly not very good at. So it's better to leave it to those who can do it. The C64 requires little or no work, and they're also not remotely as rare as the Tikis, so even if something should break I wouldn't feel too bad about it.
by mixedCase | 2025-08-13 07:05:31+00:00
This is a thing and doesn't require a separate model. You can set up custom prompts that will, based on another prompt describing the task to achieve, generate information about the codebase and a set of TODOs to accomplish the task, generating markdown files with a summarized version of the relevant knowledge and prompting you again to refine that summary if needed. You can then use these files to let the agent take over without going on a wild goose chase.
by dragonwriter | 2025-08-13 07:07:15+00:00
> For congressional seat/term limits on parties.

Limits on parties like you discuss are a dumb idea, because they are trivially evaded by factional alliances that aren't formally parties.

OTOH, you wouldn't even need to have a reason to consider them if you simply had an electoral system that didn't lead to national duopoly frequently consisting of regional monopolies, e.g., if the legislative branch was elected in multiseat districts with a system structurally providing roughly proportional results, like Single Transferrable Vote.

The social technology of democracy has advanced since the 18th Century, but the most important parts of that advance, have been ignored in the US, at least at the federal level and statewide levels, though some local use is seen.
by OtherShrezzing | 2025-08-13 07:07:25+00:00
> There's zero evidence that LLMs have produced a measurable productivity boom

I’m not so sure on this one. AlphaFold2, while not quite an LLM, was based on Transformer architecture - and its implementation wasn’t a million miles away from a language model - and it massively improved the rate of protein structure prediction.

I think in general you’re correct, that we’re in a bubble, but I think it’s too extreme to say the technology is valueless.
by eptcyka | 2025-08-13 07:07:58+00:00
F-droid are thoroughly understaffed and yet incredibly ambitious and shrewd around their goals - they want to build all the apps in a reproducible manner. There’s lots of friction around deviating from builds that fit within their model. The system is also slow, takes a long while before a build shows up. I think f-droid could benefit immensely from more funding, saying that as someone who has never seen f-droid’s side, but have worked on an app that was published there.
by SilverElfin | 2025-08-13 07:09:47+00:00
In the UK the police seem to be very involved in arresting or intimidating people simply using their right to speech, which I think is the worst human right violation. There was a store that had a sign about “scumbag thieves” that was forced to take it down by the police. I guess this is what happens when you don’t have a fundamental (constitutional) right to free speech in your legal system.

https://metro.co.uk/2025/08/09/shopkeeper-told-police-take-s...
by mamonster | 2025-08-13 07:09:51+00:00
>And what about the soldiers who carry out deep strike operations, launching drones from 50 or 100 kilometers or more from the front, striking 500 kilometers or more deep against logistics and industry? Should they even bother wearing uniforms when they hop out of a van for a couple hours to launch their pre-programmed drones, just for a traitorous local to easily identify them and text their location to the enemy?

I mean, you get taught this early on in the army, no uniform when fighting a recognized nation is a war crime (unless youre a militia in which case you still need some "uniform").

>This whole drama unfolds both in front of officers in traditional Tactical Operations Centers, and increasingly, in front of splintered command teams and individuals watching from safehouses via livestream. At the end of the mission, the soldier will go home and pass on his kill footage to score “points” for his command to receive additional official funding.

Gameification is by far the worst innovation of the Ukrainian army so far. All it does is funnel even more funding/equipment into brigades that are already well equipped and typically stationed at easier parts of the front.
by arielcostas | 2025-08-13 07:10:12+00:00
Not just our thinking, but our search for truth. The biggest problem I see is that models can hallucinate or be biased (for example, Grok being told explicitly not to mention Trump and Musk when asked about misinformation) for the benefit of their owners or creators. This happens with Chinese models too, of course, because of their laws.

The problem is that people just trust what the LLM tells them, not realising they can be misled, or the model tells them "you're right" without any pushback or invitation to think further—just like an echo chamber, the consequences of which we've seen with social media in the last few years
by seszett | 2025-08-13 07:10:42+00:00
> I suspect though that it’s often a case of people noticing these type of design flaws but not having the authority to fix them while those with the authority don’t care.

Kinda related but also not really, my own pet peeve is the pouring spout in many products, coffee machine, water jugs, buckets... they might look effective but I find that more often than not, they are curved too much and drip all over when actually pouring.

And I always have to wonder, after serving coffee from one of those things, did the person who design it never even try it just once? Didn't they ever use such a thing, they never ever poured water from a pot?
by spiderfarmer | 2025-08-13 07:11:10+00:00
I recently saw a good example of how LLM's can be really useful.

A friend of mine, who always found learning difficult, now works as a plumber and installer with his own one-person company.

One of his clients is the local community pool. He took over the job from an older man who showed him how everything worked. My friend noticed a lot of inefficient (manual) use of energy and resources, but the previous installer told him it would cost too much to automate, so nothing was done.

The other day we talked about AI, and he said he had never tried it. I asked him to think of some questions from his daily work. He came up with questions about the pool system and how to automate it.

ChatGPT answered his questions correctly, and after a few follow-ups, it even provided a list of the parts he would need and a plan to make it work. Last weekend he told me that, together with the previous installer, he made improvements that should save the pool thousands of euros over the next few years.

Of course, an experienced pool expert might have come up with the same solution, but it is often difficult to convince a committee to hire someone when nothing is broken, the budget is already set, and the inefficiencies are not obvious.

My friend now uses ChatGPT several times a day to solve practical problems. It helps him learn new things and explore possibilities he might not have considered otherwise.

I do not mind if ChatGPT makes the occasional mistake or gives an answer based on outdated information. As long as it is used as a tool to improve your own abilities, the subscription is worth the cost.

When I worked with colleagues, I sometimes relied on advice that turned out to be wrong. Everyone makes mistakes, even when working to the best of their abilities, and I find that my AI 'colleagues' make fewer of them.
by karteum | 2025-08-13 07:11:24+00:00
I don't fully understand: aren't gradle and aapt2 open-source ?

If you want to build buildroot or openwrt, the first thing it will do is compiling your own toolchain (rather than reusing the one from your distro) so that it can lead to predictable results. I would have the same rationale for f-droid : why not compile the whole toolchain from source rather than using a binary gradle/aapt2 that uses unsupported instructions?
by adrian_b | 2025-08-13 07:11:28+00:00
I believe that in such a case one can use both "has been abolished in 1966" and "was abolished in 1966", but they mean different things.

"Has been abolished in 1966" says that it was abolished in 1966 and it remains abolished today.

"Was abolished in 1966" says that it was abolished in 1966, but it provides no information about whether it might have been reinstated later and it might continue to be enforced today.

So in this case I believe that the other poster was correct in using "has been abolished in 1966".
Show HN: A Peek into My Accelerated Learning Stack and the Missing UI for AI
by IXCoach | 2025-08-13 07:12:04+00:00
Introducing Coherence OS / Coherence UI

This tool resolves in part several frustrations I have with attempting to accelerate actual production ready outputs from my collaborations with AI.

It solves the fact that the best AIs fail to allow infinite memory, in 2s, through copy and paste into the system.

It solves the issue of privacy with sensitive IP that I don't want leaked to big brother, while retaining AI accelerants.

It creates a personal knowledge base that you control on your computer locally, instantly searchable.

It exports sections of that to external AI instantly as you deem fit to create a 2nd brain for your collaborations with AI thats infinite in scope.

And its all built within a project management framework, GTD, one of the worlds most established. So it manages to do lists, habit lists and you don't have to write down what you got done to instantly see and celebrate it, its built for you.

Plus it provides a system for AI to do your work for you in a fashion much more efficient that chatGPT chat or claude chat Alone.

The Video attached shows a peek into my accelerated learning stack, AMA. Its one part of how I use Coherence and GPT and Text Expander to accelerate learning anything.

Right now Im building ( with no effort given the coherence tools solving of critical gaps ) a tool for mock interviews and interview prep for the high paying machine learning roles in silicon valley...

This is a peek into that.

Love your feedback.

Target is prepping for open source release, not public yet but your feedback or collaboration offers will accelerate that, and if you want early access we will shoot an invite to folks registered at ixcoach.com so grab a free account there to get on the mailing list if you want a heads up first.

Tell me what you think. Its far from perfect but Im addicted to it, it went down for a day and drove me nuts ( while I was upgrading and adding auth ), I was pulling my hair out, its been so essential to me.

Target impact

Subjective: Allow you to make sense of your world, drop all of the chaos you find riveting into one place, then act on it in an organized fashion.

Intersubjective: Break from the "we own your data" drama of the western world, empower those who value privacy on principle

Give private actors who want full capability full control and leverage with ai

Objective: Provide tangible tools that impact human flourishing

Systemic: Power open source past the boundaries of capitalism, optimize for impact at scale and prove this can self sustain: alignment + impact + scalability + healthy unit economics
by eru | 2025-08-13 07:13:06+00:00
The dot-com boom of the late 1990s also had plenty of VC money.

Back then and today, you find plenty of true believers, and plenty of people who are in it for the money.

Similar, when people financed eg canals and railways or factories in the past, many participants cared about the money.

(Or are you saying it's not about the money, but specifically VCs?)
by idorosen | 2025-08-13 07:13:59+00:00
The point was that Wikipedia blocking the UK today would not have the same effect as blocking it a decade ago during previous similar censorship attempts. It would likely be less effective.

However, those aren’t not the only two options. Wikipedia could block editing from the UK, or it could simply not comply and wait for an enforcement action.

What recourse would the UK have in any case of such an enforcement action if the law or regulation Wikipedia faces does not exist in the US, where Wikipedia is ostensibly based if it removed all financial or physical presence from the UK?
by mattlondon | 2025-08-13 07:15:24+00:00
FWIW I used similar IKEA units.

Cheap and flexible, although the way they work is different (uprights have holes drilled every 2cm or so for their entire length, and you insert metal dowels at the height you need and the shelves clip into that.

What sold it for me was that the IKEA ones are made of wood, so it makes it trivially easy to modify - cut a bit out here, screw something in there etc. This made it ideal for my shed workshop build where I needed some customisations for awkward tools and I could put a workbench exactly where I want it just by screwing it in. Finally just screw the uprights together and into the wooden walls of the shed and you have a rock-solid custom-built racking system that can be reconfigured and modified easily.
by helsinkiandrew | 2025-08-13 07:15:31+00:00
> It’s the first revolutionary technology that his first goal is to make money for VC investors instead of really change the world

Is that true?

Steam technology and factory machinery were created and used to make the pit, mill, and factory owners more money than with human workers. The railway mania in the 1840s was a period where vast sums of money were invested in railway lines and engine technology.

https://en.wikipedia.org/wiki/Railway_Mania
by croisillon | 2025-08-13 07:15:35+00:00
so in french there is an expression derived from this, condemning/forbidding can be called "putting things on the index" (https://en.wiktionary.org/wiki/mettre_%C3%A0_l%27index), and "index" is also the name of the pointer finger... so in 1990 a politician said (about a bishop, or was it about the pope himself?): "he doesn't understand how condom is to be used since he put it on the index"
by HL33tibCe7 | 2025-08-13 07:15:38+00:00
> What’s going to happen in the next 5 years? Will my skills be relevant? How do I truly add value with AI getting smarter in every way? How does it change life for me and my family?

Here is how I approach this - this might be a coping mechanism, but it’s certainly helped me personally.

LLMs are hugely impressive, no-one is denying that. But they have already been out for nearly 3 years at this point, and there are still massive gaps in their functionality that mean, in their current state, they are nowhere near being able to take over highly skilled work (e.g. software engineering at senior+ levels) from humans. They can handle grunt work well, but are unable to go beyond that: they operate at the level of a (poor) junior.

LLMs remind me to some extent of journalists and the Gell-Mann Amnesia effect. When I ask an LLM a question in an area I am not an expert in, I’m impressed. On the other hand, when I ask it something I am an expert in, I am almost always disappointed. I don’t bother using them for complex work any more, because they lie and hallucinate too much.

Furthermore, the rate of progress appears to be slowing.

All of this gives me some hope that my own life will not be completely ruined as a result of this technology.
by roenxi | 2025-08-13 07:16:41+00:00
The list of technological examples in the article are all notable for their economic effects and the first one was enabling factory jobs. The AI revolution is, so far, actually pretty economically mild, small and unprofitable for a tech revolution. Compare it to the industrial revolution was transformation on a scale that is outside the modern experience.

Of course, the assumption is it is going to be a lot bigger as the decades give it time to fully roll out. It is impossible to guess precisely but it'll probably be bigger than the industrial revolution by the time all the 2nd order effects start settling in. We just don't know what it looks like when the entire management and political decision making apparatuses are suddenly stuffed with counterintelligence. It'll be a shock to the system compared to the current leadership.