MurphyA/hacker-news huggingface dataset:
by achierius | 2026-01-12 06:43:21+00:00
You really underestimate how much work goes into everything around you. You don't care because it just works: the stuff you use is by and large not crap, which makes the crappy stuff all the more noticable. Check out the housing code for your area: everything from the size of steps to the materials used for siding are in there. Or look at the FCC specifications for electrical devices that make sure you don't inadvertently jam radio frequencies in your local area, or the various codes which try very hard to stop you from burning your house down.

You're right that "there are parts of our society where junk isn't well tolerated", but the scope of those areas is far greater than you give credit for.
by tzahifadida | 2026-01-12 06:43:45+00:00
An agent can make summaries via Markdown files while processing. Then use that to break the problem to several issues and then tackle them one by one, even automatically, but more usually interactively. The problem is the technique now, not the llm. Yes, it costs a lot (lot) more. But, it can do it, and people work cost way more than tokens.
by jaggederest | 2026-01-12 06:44:58+00:00
Exactly my opinion - I think the more you lock down the "search space" by providing strong and opinionated tooling, the more LLMs perform well. I think of it as starting something like a simulated annealing trying to get a correct solution, versus the same simulated annealing run while using heuristics and bounds to narrow the solution space
by solid_fuel | 2026-01-12 06:45:25+00:00
Cool. That sure sounds nice and simple. What do you do when the multiple LLMs disagree on what the correct tests are? Do you sit down and compare 5 different diffs to see which have the tests you actually want? That sure sounds like a task you would need an actual programmer for.

At some point a human has to actually use their brain to decide what the actual goals of a given task are. That person needs to be a domain expert to draw the lines correctly. There's no shortcut around that, and throwing more stochastic parrots at it doesn't help.
by quinnjh | 2026-01-12 06:45:46+00:00
do you expect the model to train on synthetic data or do you expect to grow a userbase that will generate organic training data?

> One of the biggest issues with symbols is that, to a human, matching parentheses is relatively easy, but the models struggle with it.

Great point. I find it near trivial to close parens but llms seem to struggle with the lisps ive played with because of this counting issue. To the point where ive not been working with them as much. typescript and functional js as other commentors note is usually smooth sailing.
by habinero | 2026-01-12 06:46:23+00:00
Documentation isn't there to have and admire, you write it for a purpose.

There are like eight bajillion systems out there that can generate low-level javadoc-ish docs. Those are trivial.

The other types of internal developer documentation are "how do I set this up", "why was this code written" and "why is this code the way it is" and usually those are much more efficiently conveyed person to person. At least until you get to be a big company.

For a small team, I would 100% agree those kinds of documentation are usually a liability. The problem is "I can't trust that the documentation is accurate or complete" and with AI, I still can't trust that it wrote accurate or complete documentation, or that anyone checked what it generated. So it's kind of worse than useless?
by amenod | 2026-01-12 06:47:21+00:00
> Just in case you want an even more vintage experience.

Just to clarify, it's not about "vintage experience". Xfce is deceptively simple - it gets out of your way and let you do whatever you wish. The original settings are sensible as they are, but you also can customize it as you wish. It is pretty un-opinionated.
by littlestymaar | 2026-01-12 06:47:37+00:00
> 2) Other people are just less picky than I am, or they have a less thorough review culture that lets subpar code slide more often.

Given how consistently terrible the code of Claude Code-d projects posted here have been, I think this is it.

I find LLMs pretty useful for coding, for multiple things(to write boilerplate, as an idiomatic design pattern search engine, as a rubber duck, helping me name things, explaining unclear error messages, etc.), but I find the grandiose claims a bit ridiculous.
by shevy-java | 2026-01-12 06:47:43+00:00
Reads like AI slop. This is also quite annoying: quality appears to go downwards constantly. I am not saying that the oldschool blogs were all great in quality, but now I look at an article to see signs of AI generated text and if I see it - or think I see it - I become more critical automatically. Even without that, it seems the quality of writing has gotten worse. I remember that people years ago complained that handwriting got worse (I always got awful handwriting though, way before using computers already); but now it seems that it also affected the brain. The seem to be some disconnect on what is thought, and what is written down.
by fuzzythinker | 2026-01-12 06:47:43+00:00
It wasn't ill timed. Any sane leader would understand both size and cost of tech always comes down rather quickly over time. He's just refused to accept having lidar uglify his cars or wait for it to get smaller. He instead fabricates about humans don't have lidars so cars shouldn't have them and sold "no lidars on Teslas" as an advantage instead of the opposite and refuses to accept the truth due to needing to feed his ego. Firing all non-yesmen didn't help either.
by csomar | 2026-01-12 06:48:18+00:00
Vibe-setting up a home network server with VaultWarden is beyond reckless. LLMs have tendency to overlook security in order to get things working. You are, thereby, exposing your passwords (and potentially your 2FA as bitwarden supports that) to the whole world. This is beyond stupid. Even before LLMs my main concern with setting up BitWarden on my own server was two folds: security and availability. LLMs doesn't fix the second point but they make the first point much worse.
by roomey | 2026-01-12 06:48:19+00:00
I have to agree. In fairness I am biased in that I have used xubuntu (xfce Ubuntu distro) for many years, but the one "feature" is that now I find it hard to use any other OS because of "perceived latency".

I see a top comment here speaking about an inefficient architecture.. that may be the case under the hood, but if you use it for a while, the "click lag" is very noticeable when you move off it.

Maybe it's not a good thing! /s. When I started a new role, I had to use a mac for a week until IT did a Linux swap out, and I found it so frustrating. Mostly the inability to set shortcuts that were muscle memory, but also the lag.

I have noticed lag more on a brand new iPhone (the pro one) then on my face... Which is something
by eru | 2026-01-12 06:48:32+00:00
Just because you can't (yet) remove the human entirely from the loop, doesn't mean that economising on the use of the humans time is impossible.

For comparison have a look at compilers: nowadays approximately no one writes their software by hand, we write a 'prompt' in something like Rust or C, and ask another computer program to create the actual software.

We still need the human in the loop here, but it takes much less human time than creating the ELF directly.
by nullocator | 2026-01-12 06:49:06+00:00
I would be heavily predisposed to vote for any candidate who had a public goal of breaking up the big tech companies and taxing their CEOs into oblivion. I want this primarily because of the immediate about-face they all had when Trump 2.0 was elected and them all contributing to and standing behind him during his inauguration. Had they not, mercifully, all shown themselves as the snakes that they are I probably would have mostly continued to considere them a-political-ish and not been strongly opinionated.
by daxfohl | 2026-01-12 06:49:32+00:00
Could be. Most projects I've worked on tend to span multiple services though, so I think AI would struggle more trying to understand and coordinate across all those services versus having all the logic in a single deployable instance.

The way I see feature development in the future is, PM creates a dev cluster (also much easier with a monolith), has AI implement a bunch of features to spec, AI provides some feedback and gets input on anywhere it might conflict with existing functionality, whether eventual consistency is okay, which pieces are performance criticial, etc., and provides the implementation, a bunch of tests for review, and errata about where to find observability data, design decisions considered and chosen, etc. PM does some manual testing across various personas and products (along with PMs from those teams), has AI add feature flags, launches. The feature flag rollout ends up being the long-pole, since generally the product team needs to monitor usage data for some time before increasing the rollout percentage.

So I see that kind of workflow as being a lot easier in a monolithic service. Granted, that's a few years down the road though, before we have AI reliable enough to do that kind of work.
by ateya | 2026-01-12 06:50:17+00:00
Hi everyone! I reverse engineered Ann Arbor’s parking ticket system to track parking tickets in real time.

I ended up building a “Google Maps for parking tickets” in Ann Arbor. You can:

- See tickets being issued live

- View which officers issue the most tickets

- Identify the most ticketed streets and parking spots

- Explore other interesting stats/patterns

It started as a curiosity project (inspired by Riley Walz) and turned into something pretty fun (and slightly painful if you park downtown a lot).

Check it out here: ammarateya.com/a2-parking

Happy to answer questions about how it works or what I found: ammarateya.com/a2-parking/about
by magicalhippo | 2026-01-12 06:50:43+00:00
I recall reading about a paper in SciAm or American Scientist a couple of decades ago, where they had trained a ML model to predict regional conflicts or civil wars. The main input was scarcity of food, mainly through price IIRC.

They trained it on historical data up to the 90s or so, and had it predict the "future" up to the time of the article. And as I recall it did very well. They even included some actual near-future predictions as well which also turned out pretty accurately as I recall.

Which I suppose isn't a huge surprise after all. People don't like to starve.
by dennis16384 | 2026-01-12 06:50:51+00:00
I keep working on Routing24 https://routing24.com, a free route optimization tool for businesses.

It's been approx. an year since we are up and running, and we helped 100+ businesses in the US and world-wide to understand the value and savings of automated route planning, and prepared tens thousands of optimized routes for companies operating from 1 to 50 vehicles. All this keeping our operational expenses low and flat, thanks to our local-first route optimization engine working in the browser, and reliance on OpenStreetMap.
by johnisgood | 2026-01-12 06:50:54+00:00
Tailscale does not solve the "falling behind on updates" problem, it just moves the perimeter. Your services are still vulnerable if unpatched: the attacker now needs tailnet access first (compromised device, account, or Tailscale itself).

You have also added attack surface: Tailscale client, coordination plane, DERP relays. If your threat model includes "OpenSSH might have an RCE" then "Tailscale might have an RCE" belongs there too.

WireGuard gives you the same "no exposed ports except VPN" model without the third-party dependency.

The tradeoff is convenience, not security.

FWIW, why are people acting like accessing a server from a phone is a 2025 innovation?

SSH clients on Android/iOS have existed for 15 years. Termux, Prompt, Blink, JuiceSSH, pick one. Port N, key auth, done. You can run Mosh if you want session persistence across network changes. The "unlock" here is NAT traversal with a nice UI, not a new capability.
by bitwize | 2026-01-12 06:50:54+00:00
Fvwm ran exactly that way on my Pentium-60 and I do not recall ever experiencing performance or latency issues; matter of fact, my Linux desktop of the time was more efficient than Windows. The FvwmPager, FvwmButtons, and FvwmTaskBar modules are separate programs launched by fvwm and communicate with it via IPC. Sacrificing modularity to avoid performance issues that were hard to see even on machines from 30 years ago—let alone on today's hardware—is a bit penny-wise and pound-foolish.
by nl | 2026-01-12 06:51:03+00:00
This is wrong and I don't know why people think it is true.

LLMs understand language Grammar files really well. A new language is easy for them (you can tell this by giving them a JSON schema and seeing how well they do)

What they don't always have is good taste with what preexisting libraries work together well. But this isn't a problem for new languages.
by djtango | 2026-01-12 06:51:10+00:00
Yes - not about coke but my understanding is that Heinz invested a lot of money over the years to standardise the taste across factories, countries and tomatoes themselves.

Coke itself is not consumed in a containerless 0g environment so the container itself imparts taste - hence why aficionados will often prefer glass over pastic or can. The bottling processing factory will also impart a taste, as will the local humidity which is why I often think drinks taste odd in Singapore.

My fav thing I heard was back in a chemistry lab someone told me a rumour coke had invested serious R&D into a plastic/surface that tastes like lemon to accommodate for the regular plastic taste that leaches from their bottles.
by jaggederest | 2026-01-12 06:51:51+00:00
> do you expect the model to train on synthetic data or do you expect to grow a userbase that will generate organic training data?

Both, essentially, I expect the code examples to grow organically but I expect most of them to come from LLMs, after all, that's the point of the language. I basically expect there to be a step function in effectiveness when the language has been ingested by the models, but they're already plenty decent-ish right now at it.

The most fascinating thing to me, generating the whole thing, has been that the LLMs are really, really good at iterating in a tight loop by updating the interpreter with new syntax, updating the stdlib with that new syntax, building some small extension to try using it, and then surfacing the need for a new builtin or primitive to start the cycle over.

I'm also leaning heavily on Chatgpt-5.2's insanely good math skills, and the language I'm building is very math heavy - it's essentially a distant cousin to Idris or any of the other dependently-typed theorem proving languages.
by jonas21 | 2026-01-12 06:51:56+00:00
Driving is certainly not deterministic. Even if you take the same route over and over, you never know exactly what the other drivers or pedestrians on the road are going to do, or whether there will be unexpected road conditions, construction, inclement weather, etc.
But through training and experience, you build up intuition and general rules of thumb that allow you to drive safely.

It's the same thing with LLMs. You build up the right procedures and intuitions to allow you to get good results, even if you don't get exactly the same result every time.
by refurb | 2026-01-12 06:52:03+00:00
> One only has to look at the buffoonish attempts to push through charges on Comey, James and other political opponents to see that.

How so? Charges were dismissed on a technicality of on the US prosecutor who brought them, not based on evidence presented.

Have you seen all the evidence? You seem very confident that no crime has been committed.

I mean we've seen the declassified Obama memo on sicking the CIA on Trump. Seems like some smoke there, why not find out if there is a fire?
by seanmcdirmid | 2026-01-12 06:52:15+00:00
Mostly the latter! You can ask it to look at things conditionally (like, if the test fails, look at this doc before deciding what to do next), but usually I just load it all up at the start before asking it to make change. The LLM is good enough about picking out what it needs. The one problem is that if you have a change you are propagating through the workflow, you need to highlight that change to the LLM or it might not notice it.

I'm working on workflow processing to make this easier ATM (because I can't help my coworkers do what I'm doing, and what I'm doing is so ad hoc), which is why I'm talking about it so much. So the idea is that you request a change at the top, and the LLM updates everything to accommodate the change, keeping track of what changed in each artifact. When it goes to generate code...it has a change for the artifacts that input into code (which are just read in along with a prompt saying "generate the code!"). You just don't ask the LLM to change the code directly (because if you do that, none of the docs get updated for the change, and things can go bad after that...).

When things go wrong, I add extra context if I can spot the problem ("focus on X, X looks wrong because...") and that just merges with the other docs as the context. Sometimes if I can't figure out why a test is failing, I ask it to create a simpler version of the test and see if that fails (if it does, it will be easier to eye the problem). Manual intervention is still necessary (and ugh, sometimes the LLM is just having a bad day and I need to /clear and try again).
by graovic | 2026-01-12 06:52:44+00:00
One thing related to programming jobs and AI: my opinion is that AI will create far more jobs than we’ve ever had.

Right now, there’s a limit to how widely software is adopted, largely based on software quality and cost. AI will improve software quality (for example, you can add a ton of automated tests even if you don’t use AI to develop features) and reduce the cost of building software.

That will lead to better software—and software we didn’t build in the past because it was too complex, or so niche that we weren’t sure we could make enough profit to justify the development costs. It will say also change many other industries, but I think generally for the better: more ways to create new things, more variations, and more customization for specific purposes.
by reconnecting | 2026-01-12 06:52:54+00:00
I confirm that you was absolutely right!

Photos on MacOS indeed synchronise photos with iCloud.

After our conversation I had tried to understand why I indeed don't see any status and I found out, that to get one in Monterey iOS I must need to scroll down of the collection and after, at the bottom pul whole page for the second time. Status message appears and it was saying that syncing was disabled due to Mac performance (I didn't asked for this).

Apologies, for misleading, code543 and thank you for consistence.

However, I must admit that I'm happy that found iCloud Photos Downloader as a result, also I liked that it's downloading all photos in date/folder structure.
by anonnon | 2026-01-12 06:53:38+00:00
If the term originated on 4chan, then there's little doubt it derived from "goyslop," given how common the usage of "goyslop" was and is there, and how similar are the connotations (overlords feeding their "cattle" an unhealthy facsimile of something, editable or digital, to physically or mentally sicken them and render them docile & subservient). The people here who don't see the connection fail to demonstrate any familiarity with imageboard culture, undermining their confidence. Even in this thread, at least one other person noted the link before me (and got flagged for it)[1], and the Wiktionary entry cites "goyslop" as a related term[2].

The only question remaining is whether it did, in fact, originate on 4chan. If it saw some usage outside of imageboards before November, 2022, then that undermines the argument. But if 4chan birthed it, then there's little doubt it's an offshoot of goyslop.

[1] https://news.ycombinator.com/item/id=46579707

[2] https://en.wiktionary.org/wiki/AI_slop
by jasonkester | 2026-01-12 06:54:11+00:00
I'm working on a oldskool video game:

https://valtima4.com/

It's the Survival Crafting RPG you would have played on your Apple II back in the 80's.

You can think of it as Valheim's gameplay crammed into the tile-based ui of the old Ultima games.

It has a procedurally-generated open world with towns and NPCs to talk to, all the resource gathering, mining, crafting stuff you'd expect in a modern survival game, and some good old fashioned dungeon crawling to boot.

I've been working on it off and on for the last several months. Let me know what you think!
by SilverElfin | 2026-01-12 06:54:19+00:00
What I have previously heard, is that the current generation of Chinese rockets cannot place these tiny satellites precisely into a lower orbit. And so they are choosing to go into some of these more traditional orbits, where not only is there more density of spacecraft, but also objects take a lot longer to naturally decay their orbit and fall back to earth.

The consequence here is that a space debris problem may last hundreds of years.
by mrtksn | 2026-01-12 06:55:09+00:00
> People are out there protesting right now even though ICE and the police have a history of shooting unarmed protestors

I never understand what's the point of those protests. They should be taking over power by force or GTFO. Notice that successful revolutions storm the HQ, destroy some building of iconic significance or kill/capture the leader, not just enduring the atrocities of the foot-soldiers of the people who they are against.

The peaceful protest thing works when the people in the HQ care about what you think about them, which means it only works if those protesting are their people and not the opposition.

The lefties should start taking notes on what works and what the far right did to gain so much power and start stealing their methods. Display of dissatisfaction isn't going to work, if anything that dissatisfaction is satisfaction to the right fingers. They feel giddy when see the people they hate protesting, their only complain can be that the protests are not big enough.
by Arun2009 | 2026-01-12 06:56:10+00:00
What we tend to forget is that even with the catastrophic effects of climate change, the Earth is still vastly more inhabitable than other planets in the solar system. More pertinently, today we also have the intellectual tools to come with the right solutions for a good part of this problem. Solutions most likely won't require dramatic breakthroughs in fundamental science; probably just more clever engineering and better social and political coordination.

The real problem is that this is happening in one of the most socio-economically underdeveloped regions of the world. Despite isolated centers of modest excellence, India still hasn't fully absorbed the implications of the scientific revolution at a popular, cultural level. A good part of the population are still caught up in pre-modern modes of thinking. Rather than addressing this gap, the political establishment is only deepening an irrational and romantic belief in the worth of India's classical worldviews to continue their hold on power.

More than climate change, I dread the self-inflicted servitude to infantile notions that is holding India hostage. It's not really difficult to emerge out of this - we just need to shed our intellectual timidity and face reality as it is.
by GRiMe2D | 2026-01-12 06:56:28+00:00
I think yes. Recently I was experimenting with NEAT and HyperNEAT solutions and found this site. At the bottom it explains how novelty yields far more optimal solutions. I would assume that reasonably high temperature may also result more interesting solutions from LLM

https://blog.lunatech.com/posts/2024-02-29-the-neat-algorith...