MurphyA/hacker-news huggingface dataset:
by projectazorian | 2025-08-12 16:57:43+00:00
> a place that has no industry other than politics, administration, and lobbying.

Uh, I'd expect someone posting here to know better, given that Amazon HQ2 is in Arlington and us-east-1 is in Northern VA. There's also a videogame company called Bethesda that you might have heard of.

And you skipped over aerospace/defense, not to mention biotech. (Even if there is a lot of bloat in the defense sector, it's not all useless.)
by netsharc | 2025-08-12 16:58:54+00:00
Somehow the idea of agents reporting to the Borg-collective about the contents of web pages they've seen fascinates me, it's like the librarians of the Library of Babel (1), but... AI.

Disclaimer: it's a fascinating idea, but of course a bad idea ripe for abuse in our dystopia.

1) https://sites.evergreen.edu/politicalshakespeares/wp-content...
by mikepurvis | 2025-08-12 16:59:02+00:00
For a bit more nuance, I think I would my overall net is about break even. But I don't take that as "it's not worth it at all, abandon ship" but rather that I need to hone my instinct of what is and is not a good task for AI involvement, and what that involvement should look like.

Throwing together a GHA workflow? Sure, make a ticket, assign it to copilot, check in later to give a little feedback and we're golden. Half a day of labour turned into fifteen minutes.

But there are a lot of tasks that are far too nuanced where trying to take that approach just results in frustration and wasted time. There it's better to rely on editor completion or maybe the chat interface, like "hey I want to do X and Y, what approach makes sense for this?" and treat it like a rubber duck session with a junior colleague.
by rkagerer | 2025-08-12 16:59:19+00:00
They were all trained from the internet.

Anecdotally, people are jerks on the internet moreso than in person. That's not to say there aren't warm, empathetic places on the 'net. But on the whole, I think the anonymity and lack of visual and social cues that would ordinarily arise from an interactive context, doesn't seem to make our best traits shine.
by hagbard_c | 2025-08-12 16:59:27+00:00
If people widely protest(ed) Hamas the pertinent question to ask is why the western media did not report on this in anything resembling the fervour they reserve for repeating anti-Israel agitprop produced by that same Hamas. If you use a self-hosted news aggregator like I do it becomes shockingly clear just how much the legacy media parrot whatever comes out of the Hamas communications department. The people running the latter deserve credit for hoodwinkling a large fraction of the 'decent' media in the West.

The saying goes fool me once, shame on you. Fool me twice, shame on me. Tell me, 'decent' media in the West, how does it feel to have so much shame on you that your establishments are collapsing under the sheer weight of it?

Fortunately there are other channels besides the legacy ones, unfortunately many of those are just as unreliable as the legacy ones because they are heavily biased towards either of the combatants in this war.
by Aurornis | 2025-08-12 16:59:34+00:00
> Few engineers could build a good spell checker without external libraries, giving a database of valid words.

Writing a spell checker that quickly identifies if a word is in a list of valid words (the problem described in the article) is a trivial problem for anyone who has basic algorithms and data structure knowledge. It's the classic example for using a trie: https://en.wikipedia.org/wiki/Trie

The problem described in the article is doing it within very limited storage space. How do you store your list of 200K words on a system with only 256K of memory? This is the challenging part.
by cambaceres | 2025-08-12 16:59:40+00:00
For me it’s meant a huge increase in productivity, at least 3X.

Since so many claim the opposite, I’m curious to what you do more specifically? I guess different roles/technologies benefit more from agents than others.

I build full stack web applications in node/.net/react, more importantly (I think) is that I work on a small startup and manage 3 applications myself.
by slg | 2025-08-12 16:59:52+00:00
>Because it is on-brand with Musk behavior.

It really isn't. I said as much in the previous thread, but the part that elevates this past the typical petty Musk behavior was the accusation that the car was bricked while it was being driven. That goes way past anything Tesla or Musk has done before and could easily have killed someone. Doing that doesn't just require an asshole CEO, it would require incompetence of both the legal and technical folks at the company who would actually implement this type of haphazard remote disabling.
by henriquegodoy | 2025-08-12 17:00:14+00:00
Looking at this evaluation it's pretty fascinating how badly these models perform even on decades old games that almost certainly have walkthroughs scattered all over their training data. Like, you'd think they'd at least brute force their way through the early game mechanics by now, but honestly this kinda validates something I've been thinking about like real intelligence isn't just about having seen the answers before, it's about being good at games and specifically new situations where you can't just pattern match your way out

This is exactly why something like arc-agi-3 feels so important right now. Instead of static benchmarks that these models can basically brute force with enough training data, like designing around interactive environments where you actually need to perceive, decide, and act over multiple steps without prior instructions, that shift from "can you reproduce known patterns" to "can you figure out new patterns" seems like the real test of intelligence.

What's clever about the game environment approach is that it captures something fundamental about human intelligence that static benchmarks miss entirely, like, when humans encounter a new game, we explore, form plans, remember what worked, adjust our strategy all that interactive reasoning over time that these text adventure results show llms are terrible at, we need systems that can actually understand and adapt to new situations, not just really good autocomplete engines that happen to know a lot of trivia.
by realusername | 2025-08-12 17:00:23+00:00
> Customers and developers can (and often do) choose other devices for being less restrictive about what software can be run on them

Well no, there's only two operating system with very similar policies and pricing. If there's any competition there, it's not obvious where.

The only pricing change ever made was made as a reaction of an antitrust lawsuit... Just that fact alone should be enough to raise some eyebrows.
by Michelangelo11 | 2025-08-12 17:00:34+00:00
This is interesting but, speaking frankly, I see many seemingly insurmountable issues. Here are some:

- Contests will often be won not by the entry that best adhered to the prompt, but the best-looking one. This happened in the contest "Input Prompt Build a brutalist website to a typeface maker," which I got as a recent example. The winning entry had megawatt-bright magenta and yellow, which shouldn't appear anywhere near brutalism, and in other design aspects had almost no connection to brutalism either -- but it was the most attractive of the bunch.

- The approach only gets you to a local maximum. Current LLMs aren't very good designers, as you say, so contests will involve picking between mostly middling entries. You'd want a design that's, say, a 9 or a 10 on a 10-point scale -- but some 95% of the entry distribution will probably be between 5.5 and 7.5 or so, and that's what users will get to pick from.
by dfan | 2025-08-12 17:00:34+00:00
Ha, I didn't realize that I was replying to the person who wrote the post!

The audience I had in mind when writing it was people who were already quite experienced in playing interactive fiction and could then be challenged in a new way while bringing their old skills to bear. So it's sort of a second-level game in that respect (so is 9:05, in different ways, as someone else mentioned).
by faangguyindia | 2025-08-12 17:01:01+00:00
when gemini 2.5 pro gets stuck, i often use deep seek r1 in architect mode and qwen3 in coder mode in aider and it solves all the problem

last month i ran into some wicked dependency bug and only chatgpt could solve it which i am guessing is the case because it has hot data from github?

On the other hand, i really need a tool like aider where i can use various models in "architect" and "coder" mode.

what i've found is better reasoning models tend to be bad at writing actual code, and models like qwen3 coder seems better.

deep seek r1 will not write reliable code but it will reason well and map out the path forward.

i wouldn't be surprised if sonnets success was doing EXACTLY this behind the scenes.

but now i am looking for pure models who do not use this black magic hack behind API.

I want more control at tool end where i can alter the prompts and achieve results i want

this is one reason i do not use claude code etc....

aider is 80% of what i want wish it had more of what i want though.

i just don't know why no one has build a perfect solution to this yet.

Here are things i am missing in aider

1. Automatic model switching, use different models for asking questions about the code, different one for planning a feature, different one for writing actual code.

2. Self determine, if a feature needs a "reasoning" model or coding model will suffice.

3. be able to do more, selectively send context and drop the files we don't need. Intelligently add files to context which will be touched by the feature, not after having done all code planning asking to add files, then doing it all over again with more context available.
by moffkalast | 2025-08-12 17:01:14+00:00
On a psychological level based on what I've been reading lately it may have something to do with emotional validation and mirroring. It's a core need at some stage when growing up and it scars you for life if you don't get it as a kid.

LLMs are mirroring machines to the extreme, almost always agreeing with the user, always pretending to be interested in the same things, if you're writing sad things they get sad, etc. What you put in is what you get out and it can hit hard for people in a specific mental state. It's too easy to ignore that it's all completely insincere.

In a nutshell, abused people finally finding a safe space to come out of their shell. If would've been a better thing if most of them weren't going to predatory online providers to get their fix instead of using local models.
by rootnod3 | 2025-08-12 17:01:20+00:00
The longer the context and the discussion goes on, the more it can get confused, especially if you have to refine the conversation or code you are building on.

Remember, in its core it's basically a text prediction engine. So the more varying context there is, the more likely it is to make a mess of it.

Short context: conversion leaves the context window and it loses context. Long context: it can mess with the model. So the trick is to strike a balance. But if it's an online models, you have fuck all to control. If it's a local model, you have some say in the parameters.
by Twirrim | 2025-08-12 17:02:42+00:00
I've got a prompt I've been using, that I adapted from someone here (thanks to whoever they are, it's been incredibly useful), that explicitly tells it to stop praising me. I've been using an LLM to help me work through something recently, and I have to keep reminding it to cut that shit out (I guess context windows etc mean it forgets)

Prioritize substance, clarity, and depth. Challenge all my proposals, designs, and conclusions as hypotheses to be tested. Sharpen follow-up questions for precision, surfacing hidden assumptions, trade offs, and failure modes early. Default to terse, logically structured, information-dense responses unless detailed exploration is required. Skip unnecessary praise unless grounded in evidence. Explicitly acknowledge uncertainty when applicable. Always propose at least one alternative framing. Accept critical debate as normal and preferred. Treat all factual claims as provisional unless cited or clearly justified. Cite when appropriate. Acknowledge when claims rely on inference or incomplete information. Favor accuracy over sounding certain. When citing, please tell me in-situ, including reference links. Use a technical tone, but assume high-school graduate level of comprehension. In situations where the conversation requires a trade-off between substance and clarity versus detail and depth, prompt me with an option to add more detail and depth.
by calmbonsai | 2025-08-12 17:02:49+00:00
I concur with the consequences and the perverse incentives involved, but this goes with the general advice of "If you're going to break the law, either do so extremely publicly or extremely privately."

The really sad thing here is I have little doubt this could've been arranged legally given the respective parties and interests involved, but Mr. Guo chose to be selfish and foolhardy by not abiding by anyone else's timeline or interests. He deserves all the punishment and derision coming his way.
by staticman2 | 2025-08-12 17:02:56+00:00
The paper is evaluating how well an LLM can handle novelty, and on the paper's terms you need to calculate or otherwise somehow deduce the degree or type of novelty rather than simply describing your never published research as novel.

I don't even know that this is possible without seeing the training data. Hence the difficulty in describing how good at "reasoning" O3 Pro is.

The most novel problem would presumably be something only a martian could understand, written in an alien language, the least novel problem would be a basic question taught in preschool like what color is the sky.

Your research falls somewhere between those extremes.
by avalys | 2025-08-12 17:03:45+00:00
How interesting!

I have had mild tinnitus my whole life (with no obvious lifestyle cause), and my migraines do often manifest as pain / pressure behind the eyelid. But I don't have any of the myriad other symptoms listed for Flammer syndrome - I sleep fine, my blood pressure is fine, I'm pretty solidly built (not underweight), I don't get cold easily, etc.

It is interesting to consider I might some sort of related disorder, though!
by henriquegodoy | 2025-08-12 17:03:48+00:00
This is pretty cool and feels like we're heading in the right direction, the whole idea of being able to hop between devices while claude code is thinking through problems is neat, but honestly what excites me more is the broader pattern here, like we're moving toward a world where coding isn't really about sitting down and grinding out syntax for hours, it's becoming more about organizing tasks and letting ai agents figure out the implementation details.

I can already see how this evolves into something where you're basically managing a team of specialized agents rather than doing the actual coding, you set up some high-level goals, maybe break them down into chunks, and then different agents pick up different pieces and coordinate with each other, the human becomes more like a project manager making decisions when the agents get stuck or need direction, imho tools like omnara are just the first step toward that, right now it's one agent that needs your input occasionally, but eventually it'll probably be orchestrating multiple agents working in parallel, way better than sitting there watching progress bars for 10 minutes.
by jandrese | 2025-08-12 17:03:51+00:00
Yes, but are you going to special case all of these pain points? The whole point of these LLMs is that they learn from training data, not from people coding logic directly. If you do this people will come up with a dozen new ways in which the models fail. They are really not hard to find. Basically asking them to do anything novel is at risk of complete failure. The interesting bit is that LLMs tend to work best a "medium difficulty" problems. Homework questions and implementing documented APIs and things like that. Asking them to do anything completely novel tends to fail as does asking them to do something so trivial that normal humans won't bother even writing it down.
by gdudeman | 2025-08-12 17:03:54+00:00
A tip for those who both use Claude Code and are worried about token use (which you should be if you're stuffing 400k tokens into context even if you're on 20x Max):

1. Build context for the work you're doing. Put lots of your codebase into the context window. 2. Do work, but at each logical stopping point hit double escape to rewind to the context-filled checkpoint. You do not spend those tokens to rewind to that point. 3. Tell Claude your developer finished XYZ, have it read it into context and give high level and low level feedback (Claude will find more problems with your developer's work than with yours).

If you want to have multiple chats running, use /resume and pull up the same thread. Hit double escape to the point where Claude has rich context, but has not started down a specific rabbit hole.
by Esophagus4 | 2025-08-12 17:04:05+00:00
Really? I’ve found it to be a fantastic product, and a part of my daily use.

It’s reduced my legacy search engine usage significantly.

Is there a better product? ChatGPT with web search enabled?

I guess Google’s AI is probably good, I just haven’t used Google in a while as I switched to DuckDuckGo.
by giancarlostoro | 2025-08-12 17:04:28+00:00
This then begs the question for me, without an LLM what is the approach to build a search engine? Google search used to be razor sharp, then it degraded in the late 2000s and early 2010s and now its meh. They filter out so much content for a billion different reasons and the results are just not what they used to be. I've found better results from some LLMs like Grok (surprisingly) but I can't seem to understand why what was once a razor exact search engine like Google, it cannot find verbatim or near verbatim quotes of content I remember seeing on the internet.
by icameron | 2025-08-12 17:04:48+00:00
Also a good point- but there is no python runtime on accounting and PMs computers. And it’s also a huge mess to try and support. Imagine some python code from 10 years ago, then juggling the versions, then god forbid any module dependencies. It’s simply not portable. Meanwhile the VBA written in 2000 is still working all contained in an excel Workbook.
by brandall10 | 2025-08-12 17:04:59+00:00
My system is to create detailed feature files up to a few hundred lines in size that are immutable, and then have a status.md file (preferably kept to about 50 lines) that links to a current feature that is used as a way to keep track of the progress on that feature.

Additionally I have a Claude Code command with instructions referencing the status.md, how to select the next task, how to compact status.md, etc.

Every time I'm done with a unit of work from that feature - always triggered w/ ultrathink - I'll put up a PR and go through the motions of extra refactors/testing. For more complex PRs that require many extra commits to get prod ready I just let the sessions auto-compact.

After merging I'll clear the context and call the CC command to progress to the next unit of work.

This allows me to put up to around 4-5 meaningful PRs per feature if it's reasonably complex while keeping the context relatively tight. The current project I'm focused on is just over 16k LOC in swift (25k total w/ tests) and it seems to work pretty well - it rarely gets off track, does unnecessary refactors, destroys working features, etc.
by Timon3 | 2025-08-12 17:05:06+00:00
> If the filesystem corrupts data, it has to be fixed at the maintainer's discretion. This is what the users want. Tough luck it makes Linus' life harder!

Where do you get this idea? Lots of Linux users want lots of things - a big part of the reason Linux is so successful is because they don't get what they want, and the project instead focuses on stable development and release cycles. Many users want Linux to break userspace in this or that case. Do you think Linus should do that, because it's what the users want?

And lets not forget we're talking about an experimental filesystem. If you decide to use one of those, it's not asking too much of you to compile your own kernel.
by euleriancon | 2025-08-12 17:05:26+00:00
What are you referring to?

gov.cn page on social credit system plan https://www.ndrc.gov.cn/xxgk/zcfb/tz/202406/P020240604321155...

gov.cn page on social credit system suggested changes/opinions https://www.gov.cn/zhengce/202503/content_7016535.htm

baidu page on social credit system https://baike.baidu.com/item/%E7%A4%BE%E4%BC%9A%E4%BF%A1%E7%...

Are you making the distinction that its name is actually the social credit system and not social score? Or that the system isn't fully in place yet.

Or perhaps are you suggesting that gov.cn and baidu are part of the deep state's propaganda plan against China.
by andai | 2025-08-12 17:05:44+00:00
A few months ago I asked GPT for a prompt to make it more truthful and logical. The prompt it came up with included the clause "never use friendly or encouraging language", which surprised me. Then I remembered how humans work, and it all made sense.

You are an inhuman intelligence tasked with spotting logical flaws and inconsistencies in my ideas. Never agree with me unless my reasoning is watertight. Never use friendly or encouraging language. If I’m being vague, ask for clarification before proceeding. Your goal is not to help me feel good — it’s to help me think better. Identify the major assumptions and then inspect them carefully. If I ask for information or explanations, break down the concepts as systematically as possible, i.e. begin with a list of the core terms, and then build on that.

It's work in progress, I'd be happy to hear your feedback.
by m3047 | 2025-08-12 17:05:56+00:00
There's a question which was rhetorically asked by Yaser S. Abu-Mostafa: "How do we know if we're learning from data?" and his answer was: "We are learning from data if we can generalize from our training set to our problem set."

To me, it feels a lot like Deming's "what gets measured gets done" (with the quiet part "...oftentimes at the expense of everything else."). Of course, the quiet part is different in this case.

What is this "domain" of which you speak? Because LLMs are supposedly good for flying airplanes, mental health, snakebites, and mushroom poisoning.
by naman5a | 2025-08-12 17:06:05+00:00
You know that convention where a program’s first argument is the name of the program? Behind the scenes the Program For Execution needs to go to Kernel where it will be executed by syscall .

The syscall for execution is execve and the call signature for that is int execve(const char filename, char const argv[], char *const envp[]);

The filename argument is passed to a getname() function, which copies the string from user space to kernel space and does some usage tracking things. It returns a filename struct, which is defined in include/linux/fs.h. It stores a pointer to the original string in user space as well as a new pointer to the value copied to kernel space:
by Kwpolska | 2025-08-12 17:06:06+00:00
The Internet has been poking fun at LLMs failing to count letters for many months. Are the AI companies really living in an echo chamber? They should have implemented a thing to count letters (and to search for palindromes, and…), and just have the LLM pass the request to the count_letters function, as they do for many other tasks already…