MurphyA/hacker-news huggingface dataset:
by Mountain_Skies | 2025-08-12 17:19:10+00:00
Religions have multitudes of problems but suicide rates amongst atheists is higher than you'd think it would be. It seems like for many, rejection of organized religion leads to adoption of ad hoc quasi-religions with no mooring to them, leaving the person who is seeking a solid belief system drifting until they find a cult, give in to madness that causes self-harm, or adopt their own system of belief that they then need to vigorously protect from other beliefs.

Some percentage of the population has a lesser need for a belief system (supernatural, ad hoc, or anything else) but in general, most humans appear to be hardcoded for this need and the overlap doesn't align strictly with atheism. For the atheist with a deep need for something to believe in, the results can be ugly. Though far from perfect, organized religions tend to weed out their most destructive beliefs or end up getting squashed by adherents of other belief systems that are less internally destructive.
by Johnny603 | 2025-08-12 17:19:25+00:00
I recently dug into a tricky bug in Keyshade’s CLI where WebSocket errors weren’t showing meaningful messages — just [object Object]. I ended up reworking the error-handling flow so developers get clear, actionable feedback. The post walks through the debugging process, design trade-offs, and final fix.

If you’ve tackled similar CLI or WebSocket reliability issues, I’d be interested in how you approached them and whether you see gaps in my solution.
by gwbas1c | 2025-08-12 17:19:29+00:00
(Joke)

I've noticed that warm people "showed substantially higher error rates (+10 to +30 percentage points) than their original counterparts, promoting conspiracy theories, providing incorrect factual information, and offering problematic medical advice. They were also significantly more likely to validate incorrect user beliefs, particularly when user messages expressed sadness."

(/Joke)

Jokes aside, sometimes I find it very hard to work with friendly people, or people who are eager to please me, because they won't tell me the truth. It ends up being much more frustrating.

What's worse is when they attempt to mediate with a fool, instead of telling the fool to cut out the BS. It wastes everyones' time.

Turns out the same is true for AI.
by pessimizer | 2025-08-12 17:19:50+00:00
It's not a friend, it's an appliance. You can still love it, I love a lot of objects, will never part with them willingly, will mourn them, and am grateful for the day that they came into my life. It just won't love you back, and getting it to mime love feels perverted.

It's not being mean, it's a toaster. Emotional boundaries are valuable and necessary.
by fuzzfactor | 2025-08-12 17:20:05+00:00
I like that.

I used to keep track of ways to dual-boot Linux and DOS/W9x and never could pull the trigger until NT6 and Grub1 reached enough maturity to make it actually seem like I could achieve it. I guess I waited about 10 years :\

One weekend long ago I designed, built, and deployed a high-precision electronic temperature controller to replace a mercury-containing unit which was originally included with laboratory reference instrumentation.

Before there was a commercial all-electronic alternative to the originals.

Using only parts that could be bought at Radio Shack at the time :)

There was no spite involved :) Nobody cares about this kind of days' work. Personal pride should be rewarding enough.

I had no idea if it was going to be possible until I was done anyway :\

Plus I had bigger fish to fry that had already been proven possible, even though the hard work needed was years, not a weekend, and odds of success were still much lower than an iffy new circuit.
by jerf | 2025-08-12 17:20:06+00:00
It might help a bit to expand this test to a short phrase. With such a small test the model can be right for the wrong reasons; opening up a bit of space to be wrong in might sharpen the differences.

(My one-off test of the default ChatGPT model, whatever that is, got 'How many b's are there in "Billy Bob beat the record for bounding?"' correct first try, with correct reasoning given.)
by jlokier | 2025-08-12 17:20:07+00:00
It's the Three network in the UK. I've been using it every day for work for at least 10 years, and it served me very well, including all my remote work through the pandemic, gaming and Netflix, sometimes downloading terabytes per month without issues.

But they've managed capacity disastrously in my area recently. For the last three months. Where I live, and other parts of the centre of town, every day for about 4 hours from 11am to 3pm, it goes offline most of the time, so the network is unusable. It's impossible to work - can't even do chat or an audio meeting.

When I ran ping, I found it wasn't really offline sometimes. Sometimes it was just such high latency and/or packet loss that it may as well be. Signal strength was good, and voice calls worked fine.
by grishka | 2025-08-12 17:20:43+00:00
Doesn't Chinese input usually work by typing Latin codes for characters? Korean characters represent syllables made up of shapes representing individual sounds, those fit on a keyboard just fine. And I'm not sure about Japanese, there they may use something like spell checkers to map kana to kanji.

Another interesting challenge with CJK languages was just displaying them. You need higher-resolution graphics and a much bigger character ROM to even consider that.
by photon_lines | 2025-08-12 17:21:23+00:00
Sorry -- I keep seeing this being used but I'm not entirely sure how it differs from most of human thinking. Most human 'reasoning' is probabilistic as well and we rely on 'associative' networks to ingest information. In a similar manner - LLMs use association as well -- and not only that, but they are capable of figuring out patterns based on examples (just like humans are) -- read this paper for context: https://arxiv.org/pdf/2005.14165. In other words, they are capable of grokking patterns from simple data (just like humans are). I've given various LLMs my requirements and they produced working solutions for me by simply 1) including all of the requirements in my prompt and 2) asking them to think through and 'reason' through their suggestions and the products have always been superior to what most humans have produced. The 'LLMs are probabilistic predictors' comments though keep appearing on threads and I'm not quite sure I understand them -- yes, LLMs don't have 'human context' i.e. data needed to understand human beings since they have not directly been fed in human experiences, but for the most part -- LLMs are not simple 'statistical predictors' as everyone brands them to be. You can see a thorough write-up I did of what GPT is / was here if you're interested: https://photonlines.substack.com/p/intuitive-and-visual-guid...
by tracker1 | 2025-08-12 17:21:33+00:00
I was an insider user of Windows for close to a decade... the first time I saw an ad in the start menu search results, that's when I changed my default drive to Linux and have not looked back. I booted to windows on that system twice since (firmware updater). I don't have a Windows drive on my current desktop at all, and my personal laptop is a Macbook. My work laptop is Windows though, the down side is the environment is so locked down, I can't even run WSL or Docker.
by slg | 2025-08-12 17:21:42+00:00
>Pretty clear this was faked

Yet you were saying the opposite in that previous thread.

>I've implemented limp modes before and the easiest way is to prevent acceleration to over a certain speed without enabling regen. If you're already at highway speeds, you'll simply coast down to the limp speed and have plenty of time to pull over.

The video had the car stopped in the middle of traffic, so this wasn't the accusation being made. You are creating a hypothetical scenario in which the accusations are plausible rather than actually engaging with the accusations as they were made.
by zzzeek | 2025-08-12 17:22:08+00:00
yeah, people should understand, what is Scientology based on? The E-Meter which is some kind of cheap shit radio shack lie detector thing. I'm quite sure LLMs would do very well if given the task to spit out new cult doctrines and I would gather we are less than years away from cults based on LLM generated content (if not already).
by lotsofpulp | 2025-08-12 17:22:43+00:00
I notice you didn’t mention any of the health or physical risks women face in partnering up with a man, pregnancy, childbirth, breastfeeding, infant rearing (lack of sleep), loss of income and potential income due to career stagnation (meaning loss of financial security).

Given what we know of how pervasive harassment and violence against women was and is, could you envision a scenario where total fertility rate never reaches replacement rate?

What if it simply doesn’t make sense for women to partner up with the bottom 10% of men? Or even 20% of men? Then you have the women who end up only having 1 child, for whatever reason.

The higher the percentage of women that have 0 or 1 child, the higher the percentage of women that need to have 3 or more children to offset them. But the data shows, even amongst the richest women in the world with servants, that most prefer to experience 2 childbirths. A few will go for 3, in case they didn’t get a boy or girl, but the amount that want more than 3 is basically negligible.
by dvrj101 | 2025-08-12 17:22:59+00:00
i tried with three different models : - hf.co/lmstudio-community/DeepSeek-R1-Distill-Llama-8B-GGUF:Q8_0 - qwen3:4b-instruct-2507-fp16 - hf.co/ibm-granite/granite-3.3-2b-instruct-GGUF:F16

ollama run qwen3:4b-instruct-2507-fp16 >>> how many b’s are there in blueberry? Let's break down the word *"blueberry"* step by step to count how many *b's* are in it.

Step 1: Write out the word clearly: *b l u e b e r r y*

Step 2: Go through each letter one by one:

- b → yes, a *b* - l → no - u → no - e → no - b → yes, another *b* - e → no - r → no - r → no - y → no

Step 3: Count the *b's*:

- First *b* at the beginning - Second *b* after "blue"

So, there are *two b's*.

Final answer: *2* b's in "blueberry".

>>> ollama run hf.co/ibm-granite/granite-3.3-2b-instruct-GGUF:F16 >>> how many b’s are there in blueberry? The word "blueberry" contains two 'b's. (fastest lol, granite models are pretty underated)

r1-distill output was similar to qwen instruct one but it double checked it's thinking part
by jl6 | 2025-08-12 17:23:01+00:00
I don’t think it’s just (or even particularly) bad axioms, I think it’s that people tend to build up “logical” conclusions where they think each step is a watertight necessity that follows inevitably from its antecedents, but actually each step is a little bit leaky, leading to runaway growth in false confidence.

Not that non-rationalists are any better at reasoning, but non-rationalists do at least benefit from some intellectual humility.
by scrumper | 2025-08-12 17:23:03+00:00
I second this. Perplexity is the only AI I actually pay for. It absolutely excels at the kind of deep search into narrow domains where expertise is concentrated in forums and specialist sites. Things like mechanical work on obscure classic vehicles, vacuum tube electronics, company tax arcana. It's also very very good at those questions you sometimes wake up with, where something happened in the news six months ago and you think, "Whatever came of that?"

Its deep research and Pro modes are great at synthesizing thorough briefings on complex topics too, to get up to speed on a new client or job responsibility for example.

It's not a chatbot for me, it's a brilliant, tireless little research minion.

As always with any LLM you should double-check its final, specific answers. It does occasionally hallucinate when information simply isn't available. Your research minion is just that - a minion, you have to have the context. It's not a teacher or guru.

EDIT: the bottom line is, it came along at exactly the right time for me. Google's search results are pages of ads, and DuckDuckGo insists on showing page after page of content-farm blogspam for the types of topics I search for. It cuts right through all that crap for me.
by Herring | 2025-08-12 17:23:07+00:00
I don't like evaluating an entire supreme court based on 1 case. I'm not a 1 issue voter. Often you find people banging on 1 issue actually care about other things the court ruled on, like covid lockdowns, or they really want to discriminate against women and gays, or they're Bolsonaro supporters, etc but they won't say that directly.

Overall I think the court is running a high-risk high-reward strategy. They're trying to act as the ultimate guardian of democracy, by adopting methods that strain democratic principles. Is it smart? Hard to say, depends how it goes 10-50 years from now. Again, I'd prefer if all this was correctly formalized and institutionalized. Get your legislature on board.
by uecker | 2025-08-12 17:23:21+00:00
BTW: I think what me annoys me about this comment is the claim that this would be "insane amounts of hidden complexity" . If you you look at the article, it four simple one-line macros:

#define maybe(T) struct maybe_##T { bool ok; T value; }

#define maybe_just(T, x) (maybe(T)){ .value = (x), .ok = true }

#define maybe_nothing(T) (maybe(T)){ .value = (T){ }, .ok = false }

#define maybe_value(T, x) (({ maybe(T) _p = &(x); _p->ok ? &_p->value : (void*)0; }))

Please compare this to your other languages.
by pupppet | 2025-08-12 17:23:31+00:00
The problem I often have is I may have instruction like-

General instruction: - Do "ABC"

If condition == whatever: - Do "XYZ" instead

I have a hard time making the AI obey the instances I wish to override my own instruction and without having full control of the input context, I can't just modify my 'General Instruction' on a case by case basis to simply avoid having to contradict myself.
by rpcope1 | 2025-08-12 17:23:40+00:00
Even the real progenitors of a lot of this sort of thought, like E.T. Jaynes, expoused significantly more skepticism than I've ever seen a "rationalist" use. I would even imagine if you asked almost all rationalists who E.T. Jaynes was (if they weren't well versed in statistical mechanics) they'd have no idea who he was or why his work was important to applying "Bayesianism".
Show HN: Nocturne – Your Car Thing's Second Chapter
by itsnebulalol | 2025-08-12 17:23:45+00:00
Hello HN! Recently, we have released Nocturne 3.0.0, which is a complete replacement for the (now unusable) Spotify Car Thing stock firmware. We're proud to eliminate more e-waste in the world.

# Changes from v2 - Bluetooth tethering for car use (no more Raspberry Pi in the car) - Full graphics acceleration - Native Spotify login (no more client ID/secret) - Start DJ from the Car Thing - Podcast support - Gesture control - New settings - Boot to Now Playing - Spotify Connect device switcher - Support for Japanese, Simplified Chinese, Traditional Chinese, Korean, Arabic, Devanagari, Hebrew, Bengali, Tamil, Thai, Cyrillic, Vietnamese, and Greek - Full knob control support - Local file support - Preset button support - Status bar on home (shows time & Bluetooth/Wi-Fi) - Auto brightness - Hold settings button for power menu - Lock screen showing time full screen (press settings button) - DJ preset binding (hold preset button while DJ is playing in Now Playing) - Spotify mixes in Radio tab (Discover Weekly, daily mixes, etc.) - OTA updates - + MUCH more (this is just the important stuff!)

# Flashing A guide to flashing Nocturne 3.0.0 is in the README. Bluetooth will work out of the box, or choose an alternative in the Setting up Network section. Hotspot capability from your phone and plan are required for Bluetooth.

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Consider buying the team a coffee if you can https://usenocturne.com/support

https://github.com/usenocturne/nocturne/releases/tag/v3.0.0
by andrewla | 2025-08-12 17:24:18+00:00
> OpenAI definitely tarnished the name of GPT-5 by allowing these issues to occur

For a certain class of customer maybe that is true.

But the reality is that the fact that this occurs is very encouraging -- they are not micro-optimizing to solve cosmetic problems that serve no functional purpose. They are instead letting these phenomena serve as external benchmarks of a sort to evaluate how well the LLM can work on tasks that are outside of its training data, and outside of what one would expect the capabilities to be.
by rayiner | 2025-08-12 17:24:23+00:00
> DC is safe. The 2023 spike was an anomaly and it has been falling sharply in 2024 and 2025, but even in that year it was highly focused on specific groups.

I feel like when you say “DC is safe” you mean “DC is safe for affluent white/asian people who stay in the designated safe zones.” Because it’s not safe for the majority of the people who don’t live in those areas.

Objectively speaking, DC’s 27 homicides per 100k people in 2024 is almost double what it was in 2012. If actually started going back up before the pandemic. And in absolute terms, DC has about 8 times the homicide rate of a relatively safe american city like new york or san diego.

> If you weren't part of a gang or making yourself an easy target for a mugging out drunk

It’s ultimately driven by gangs, but most people killed aren’t gang members per se. They’re gang adjacent, or siblings or friends who get caught up in the gang wars. Also, the gangs aggressively recruit young men in the neighborhoods where they operate. It’s very “you’re with us or against us.”

> go to any of these SUPER SCARY neighborhoods and it's like people waiting for the bus, moms jogging by with strollers, and old people hanging out on porches.

I’ve lived in downtown Baltimore, DC, and Wilmington Delaware. I know how cities work. But the violence is a constant for the people who live there. We got to know an Indian family who had a great Indian restaurant in the ghetto in Wilmington, which has a similar homicide rate to DC. Yeah, on any given day you won’t see someone get murdered. But they had someone get killed on the street outside their restaurant. And EMTs wouldn’t come for hours because they were worried about getting caught in a gang firefight. Then another person got shot in the street near my wife’s office at 5 am waiting for the Nike Store to open. That was just in one year. Imagine growing up there and not being rich each to isolate yourself from the violence.
by toast0 | 2025-08-12 17:25:19+00:00
Well, by broadly equivalent, I mean that it's generally easy to translate from one form to another; not that they exactly match. Iteration isn't really capable of expressing all the things you can express with mutual tail calls, but otherwise.

You can certainly argue about which of two forms is clearer, but I don't know that it's a decidable problem, so like ... do whatever you feel. I write in multiple programming languages and try to blend with the local idioms, so I write loops with foreach and with recursion, and they're both fine. If you have pattern matched function clauses, I don't find recursion to be lacking in indications of the broad control flow; if you're in a language that lacks that, then recursive loops look pretty ugly. But something like a loop to sum values would be (in Erlang)

sum(List) -> sum(List, 0). sum([], Acc) -> Acc; sum([H|T], Acc) -> sum(T, H + Acc).

Assuming you know the syntax and the idioms, this is very clear. If you don't know the idioms, Acc means 'accumulator', H means 'head', T means 'tail', so if you call sum(List), it calls into the recursive sum with an initial accumulator of 0, then one element at a time is taken off the front of the list, and added to the accumulator, when the list is empty, the accumulator is returned.

the same thing in Rust would look like

fn sum (slice: &[i64]) -> i64 { let mut sum = 0; for i in slice { sum += i; } sum }

You could make it generic or whatever if you want. Is one form better at giving the reader immediate knowledge of the broad control flow than the other? I don't know. But the iterative version is 7 lines vs 4 lines in recursion. A list isn't really the same as an array slice of course, so that's a bit of a cheat. Using a tuple in Erlang is similar, but wordier:

sum(Tuple) -> sum(Tuple, 1, 0). sum(Tuple, N, Acc) when N > size(Tuple) -> Acc; sum(Tuple, N, Acc) -> sum(Tuple, N + 1, element(N, Tuple) + Acc).

And you have to know that Tuples are 1 indexed, and that N indicates the Nth element of a Tuple. You could make sum/1 take a list or a tuple, but you do have two write both versions... you could make the Rust take an IntoIterator and benefit from Traits to not have to write a different version for each kind of container. You could argue about what's a better choice, but I won't :) Maybe you like type annotations, you could add those to the Erlang, but I won't do that either :P

If your iteration has more exciting work than summation, the line count difference doesn't matter so much... maybe the work it shorter in one language than the other anyway. But I don't think either form is obviously and objectively superior. I'd wager iteration has more mind share, but that doesn't indicate that it's superior.
by andai | 2025-08-12 17:25:21+00:00
The GPT-5 used here is the Chat version, presumably gpt‑5‑chat‑latest, which from what I can tell is the same version used in ChatGPT, which is not actually a model but a "system" -- a router that semi-randomly forwards your request to various different models (in a way designed to massively reduce costs for OpenAI, based on people reporting inconsistent output and often worse results than 4o).

So from this it seems that not only would many of these requests not touch a reasoning model (or as it works now, have reasoning set to "minimal"?), but they're probably being routed to a mini or nano model?

It would make more sense, I think, to test on gpt-5 itself (and ideally the -mini and -nano as well), and perhaps with different reasoning effort, because that makes a big difference in many evals.

EDIT: Yeah the Chat router is busted big time. It fails to apply thinking even for problems that obviously call for it (analyzing financial reports). You have to add "Think hard." to the end of the prompt, or explicitly switch to the Thinking model in the UI.
by j45 | 2025-08-12 17:25:36+00:00
Yup, as you mentioned, there's other alternatives to Gitlab lcaolly that are decent.

I'm finding myself liking and using gitlab more and more when I come back to it every 6-8 months.

I don't know how I'd be able to trust only a cloud for my source code and devops/CI/CD. At least a mirrored setup in a private or hybrid cloud on another provider as a failover that isn't with the same cloud provider.
by saulpw | 2025-08-12 17:26:27+00:00
Not OP, but yes, "defund" meaning to reverse the excessive budgetary increases of the past 5-10 years, which increased militarization of police, alongside increasing qualified immunity precedent. Some people took "Defund The Police" to mean "No Police" (there will always be extremists, sincere or planted), and it turned out to be a terrible slogan for this reason. There's a healthy middle ground in which the police force is reduced to a reasonable level, and other services are funded, so the police with their guns and military training aren't the first responders when e.g. someone is suicidal or spraypainting graffiti.

And even if the suicidal person is holding a knife, or it's my house being spraypainted, I don't want the person shot!
by hnlmorg | 2025-08-12 17:27:10+00:00
OpenAI easily has worse naming.

Anthropic model names might not immediately conjure up their size and performance, but the name is at least internally consistent. Once you know what Anthropic call “medium”, you know what it is for all model releases.

Whereas OpenAIs naming convention, if you can even call it a “convention”, feels absolutely random to even those in the industry.

I do like your proposed naming convention though. It doesn’t sound “cool” so I can’t see any product managers approving it within the AI tech firms. But it’s definitely the best naming convention for models I’ve seen suggested for a while.