MurphyA/hacker-news huggingface dataset:
by colechristensen | 2025-12-11 19:14:24+00:00
>There’s an odd tendency in modern software development; we’ve collectively decided that naming things after random nouns, mythological creatures, or random favorite fictional characters is somehow acceptable professional practice. This would be career suicide in virtually any other technical field.

Odd? Modern? I started working professionally in 2005 and everything had silly names. The DNS server was named athena instead of c302r5s1 or whatever building/room/rack/position name. I once rebooted a server that had an uptime of 12 years, so it had been running since 1993... it indeed had a silly name. Everything had silly names, usually types of things had a theme.

>Same thing applies to other fields like chemical engineering, where people there maintain even stricter discipline. IUPAC nomenclature ensures that 2,2,4-trimethylpentane describes exactly one molecule. No chemist wakes up and decides to call it “Steve” because Steve is a funny name and they think it’ll make their paper more approachable.

How about piranha? aqua regia? Up/Down/Strange/Charm quarks? Gluons? Like a third of the elements named after people or places.

Curium, Einsteinium, Fermium, Mendelevium, Nobelium, Lawrencium, Rutherfordium, Seaborgium, Bohrium, Meitnerium, Roentgenium, Copernicium, Flerovium, Oganesson -- I guess none of these people were named Steve, but you get the point

These tendencies are OLD and EVERYWHERE. IUPAC names are just a convenient way to serialize data.
by no_wizard | 2025-12-11 19:14:25+00:00
What is it really about, in contrast to what I assert? I'm looking at how its being implemented, talked about, thought about, introduced.

I'm happy to re-evaluate my stance in the light of better evidence, but the AI adoption has corresponded to alot of CEOs announcing layoffs with a simultaneous doubling down on AI tools to replace those now displaced workers or those LinkedIn stories from people saying how they will never have to hire X or Y because AI will do it / does it.
by jorvi | 2025-12-11 19:14:25+00:00
There are two very simple causes to point to why touch keyboards turned to shit:

1. Crowdsourced word weighting: your keyboard's stochastic predictions are no longer mostly based on your typing, but rather on what 'everyone' is typing as their next word. This makes the word replacements it does often suboptimal to downright nonsensical.

2. Aggressive lookbehind correction: these days you have to be seriously on your guard for your keyboard to not sneak-edit something you typed 5 words back, because autocorrect suddenly decided that the probability is high you meant to say something else there (which it clearly isn't, as your eyes and brain exist)

The problem your encountering is downstream from point 1. Basically your keyboard thinks due to the way most people construct a particular sentence, you're gonna want to type "bold" next, despite "hold" clearly clearly making more sense. So it'll force "b" on you 4 times in a row until it realizes you really want to type "h".

Going back to the old style of doing keyboards (mostly user-learned dictionaries and probability weighting, and little lookbehind autocorrrect) could be done, but within Google and Apple there are probably people who got promoted by switching to the current shitty system. They'll block off any attempt at someone messing with their pride.

(There is a third 'problem' where your visual keys do not correspond to the touchmap at all. Swiftkey has a feature where it can show you what your touchmap and heatmap look like versus the actual layout and it its often staggeringly different, with many keys vastly tilted. When you try to desperately type "h" after 4 misses, you're doing that with your index finger in "hunt and peck" mode, which does correspond to the visual layout but not with your usual typing on the touchmap layout. There is no way for your keyboard to know you're in "hunt and peck" accuracy mode.)
by 0xbadcafebee | 2025-12-11 19:14:37+00:00
I am a heavy skeptic of this thing, but I can see a good use case for it: S3 I/O, ephemeral compute (1 instance), versioned blobs. The first two allow you to abstract the data away from the compute (flexibility), and the third lets you recover from mistakes or bugs quicker (or do immutable migrations easier).

I think the devil's in the details though. I expect a high number of unusual bugs due to the novel code, networking, and multiple abstractions. I'd need to trial it for a year before I called it reliable.
by prennert | 2025-12-11 19:14:43+00:00
Same for me. My Pixel magically fixed scrambled words (and was very fast doing it). iOS is terrible, even without described bug.

I am now much faster typing with the speech-to-text feature. Maybe that is what they are pushing. Maybe Apple wants to remove the keyboard and it is slowly increasing the friction so people use it less and less? Similarly how Chrome degrades browser performance until it gets restarted to force an update.
by blobbers | 2025-12-11 19:15:35+00:00
I'm curious if anyone has written a "Principal Engineer" agents.md or CLAUDE.md style file that yields better results than the 'junior dev' results people are seeing here.

I've worked on writing some as a data scientist, and I have gotten the basic claude output to be much better; it makes some saner decisions, it validates and circles back to fix fits, etc.
by lr0 | 2025-12-11 19:15:58+00:00
Sonic hedgehog is a terrible example this case. Researchers literally had to tell parents their children had mutations in the "sonic hedgehog gene." The scientific community recognized this was a problem and it's a widely-known controversy. It's cited as an example of bad naming in medical ethics discussions.

Boaty McBoatface? officials overrode the vote to name it after David Attenborough. The actual research submarine got the joke name. Again, this proves my point.

Fat Gary was an internal chip designation that never needed to be public-facing. Perfectly fine.

"Names are only for distinct identification" if efficiency was not at a question. Why use worse identifiers when better ones cost the same?
by hinkley | 2025-12-11 19:16:01+00:00
> In the end, good leadership is never proven by what you say about yourself. It’s proven by what people say when you’re not in the room.

> And trust me, they’re talking.

Some of the people I’ve had to railroad into things say stuff like, “well this is the first I’ve heard about it.” That’s a You Problem.

The fact that nobody is discussing this with you should tell you that you’ve been cut out of the loop for being impossible to negotiate with. It’s absence of evidence not evidence of absence.
Show HN: Νοῦς – A Customizable LLM Project
by albertlungu | 2025-12-11 19:16:07+00:00
I've been working on a personal project called νοῦς (Nous). It's a Python implementation of the transformer model described in Attention is All You Need (Vaswani et al., 2017), using only JAX for the backend. The goal started as a learning exercise, but the system turned into something that many others might also find useful.

As I previously mentioned, the backend is completely Python, but I have also built an electron-based frontend, releasing a fully built MacOS app. If you are on Windows, you can clone the repository and visit the README for further instructions. All model components are completely configurable: depth, width, number of heads, training parameters, and generation settings. You can both train locally using the Electron app or using the CLI with a remote GPU. Note that using the CLI, you will have to modify source code to edit the components.

Nous would be useful in experimenting with specific architectures, running controlled training setups, or even teaching/learning how modern LLMs work (the README also explains how every single part of my backend works, so it could be quite helpful to use while reading the codebase).

I originally wanted to make it a NumPy-only version but switched fully to JAX after running into performance problems.

Currently, the app comes with a pre-trained model that has 76.9M parameters, trained to a final loss value of ~0.6. It also comes with a Byte-Pair Encoding tokenizer implementation, so that you can build the tokenizer on a dataset of your choice.

Everything is open-source. Repo link is above.
by Lerc | 2025-12-11 19:16:18+00:00
Past projects of mine.

'pedes Glook Fitznik Plops Gyralight I wanted a new tower defence game: So I made one

Oh and https://lerc.itch.io/namesarehardpart5

The examples given for real world things The Golden Gate Bridge and The Hoover Dam, are instances of things. Things that the class of which they belong is old enough that Dam and Bridge are not new words.

If you are making new things you need a new name. Software is inherently new because computers have been in wide use for only a few decades. Instances of software rarely even get names, just numbers, with project names or nicknames attached. I'd be willing to bet both The Golden Gate Bridge and the Hoover dam had project names or nicknames.
by kergonath | 2025-12-11 19:16:22+00:00
From my experience it is much worse than it used to be 5 years ago. I have been writing English, French, and to a lesser extent German on an iPhone since ~2008. Initially, the dumb autocorrect would just correct to the closer word in the dictionary corresponding to the current keyboard, but over time it would pick up more and more words I used regularly. At some point around 2018 or so, it was nearly flawless. I think it changed the dictionary depending on the language or the sentence, because I had different suggestions for the same mistyped word in the same document. Also, I assume that by then my personal dictionary was quite extensive.

And then they bragged about a new machine-learning improved keyboard and it went downhill. First, all keyboards became monolingual, which was a 10-years regression. And even in that language, it was very flakey. They added multi-language keyboards somewhat recently and it got slightly better, except that for some reason it changes the keyboard back to the English-only one regularly for no reason I can see.

It is maddening. For a couple of years it was fantastic.
by margalabargala | 2025-12-11 19:16:31+00:00
> the alternative would be a corporation constantly providing -- for free -- updates and even support if your car gets into an accident or stuck.

That's one alternative.

Another alternative would be that you get what you get at purchase time, and you have to buy a new car to get the newest update.

"Continuous development" isn't always a selling point when it's something with your life in its hands. A great example is Tesla. There are plenty of people who are thrilled with the continuous updates and changes to everything, and there are plenty of people that mock Tesla for it. Both groups are large markets that will have companies cater to them.
by Tade0 | 2025-12-11 19:16:42+00:00
I think the author is ignoring the difference between Branding and several other categories, like technical terms and their common names.

The adjustable wrench is named straightforwardly, but most English speakers know it as the monkey wrench. In some European languages its name translates to "French wrench" or "the French" (as in: French person), in others it's "English wrench" even though those two were originally just variants of the adjustable wrench.

Point is, all those goofy names are brands that may or may not stick around for longer and the terms for what they actually do are more descriptive.

My favourite example: BlueJeans. A videoconferencing platform. Why is it named like that? We might never know, but most likely partly to stand out, but there's a clear distinction between the brand name and the more descriptive terms used to tell what it does.
by lr0 | 2025-12-11 19:16:57+00:00
Nobody says "gh:someguy/openai/llm-streaming-client" in conversation. You say "the streaming client" or "llm-stream" the same way you'd say "Pegasus." But when someone new joins or you're reading code, "llm-stream" is self-documenting. "Pegasus" requires looking it up every single time until you memorize an arbitrary mapping.
by shadowgovt | 2025-12-11 19:17:04+00:00
Well written, but author is at the risk of tripping over Poe's Law, especially if readers don't read to the bottom.

Author's point is that their modest proposal (and its sibling, introducing intentional delays in resolving the deprecated API pieces) is a bad idea. Instead, author suggests that making the API change at all is begging the question "Who does this API serve?" It is, perhaps, okay actually if the old system never gets deprecated.
by wahnfrieden | 2025-12-11 19:17:26+00:00
Pro solves many problems for me on first try that the other 5.1 models are unable to after many iterations. I don't pay API pricing but if I could afford it I would in some cases for the much higher context window it affords when a problem calls for it. I'd rather spend some tens of dollars to solve a problem than grind at it for hours.
by 9rx | 2025-12-11 19:17:35+00:00
> The product name is not expected to describe what the product is.

There are some exceptions, but the agriculture machinery industry has actually gotten pretty good at making the names useful, with reasonable consistency across brands. S7 600: 600 tells that it is a class 6 combine, which is a value farmers understand as it pertains to the combine's capacity. For tractors, the John Deere 8R 230 sees 8 indicate a large row-crop frame, and 230 indicates a 230 HP engine. A New Holland T7.180 is, you guessed it, a medium row-crop frame with a 180 HP engine.

It may look like nothing to outsiders, but there is a lot of useful information encoded in there once you know what to look for.
by Yokohiii | 2025-12-11 19:17:45+00:00
I have mixed feelings about this.

I think Julian Assange once said he would refer to things in discussion just as "Tomato" (or similar), in discussion to have a shortcut for something unnamed with some meaning. We do this all day in programming, we give a complex component a name and it means a lot more then just the actual word. The problem is that this specific meaning is often not universal, it's contextual.

If you take a hammer, an integer and design patterns, the latter is the least universal thing. They depend on domain, context and conventions, and can change quite a lot depending on the language. Removing hammers and integers from the world would cause collapse, removing design patterns would do almost nothing.

I guess the active celebration of design patterns as a catalogue of general wisdom is my primary issue here. I'd welcome any project/team/company that maintains a catalogue of their individual "patterns". But a universal source of truth has too much bible flavor to me. (Oh it also dictates OOP by default which renders it's inherent "wisdom" completely useless in many languages)
by pdimitar | 2025-12-11 19:17:53+00:00
That's exactly what happened. I tried improving processes and worked so hard that I neglected my wife.

I was removed because the team lead thought I'm going over his head... while I coordinated every move with him. But the moment I disagreed with him -- once, and for the first time -- I was removed. Zero discussion.

I'm quite empathetic. My original message above comes from bitterness because neither extreme is good. I was in the positive extreme for a while. Too sympathetic, always finding excuses for people who only saw me as a tool to advance their own careers and removed me the minute they thought that was no longer true.
by scoopdewoop | 2025-12-11 19:17:53+00:00
> programming shifted from corporate mainframe work to the community builders > which is good

but then:

> Our field deserves better than a zoo of random nouns masquerading as professional nomenclature

Okay? So is this professional nomenclature or the work of community builders?

I think: everyone should code, it should not be an elitist profession, we don't need to all accommodate busy professionals, i'm fine with corporate users having to say my stupid package name at work.

> Your fun has externalities. Every person who encounters your “fun” name pays a small tax. Across the industry, these taxes compound into significant waste

Someone please get this guy a bong rip.
by Spivak | 2025-12-11 19:18:11+00:00
HN literally has an algorithmic feed and the karma system is the most addictive system used on forums. It's why Reddit is so addictive.

Either HN is part of the evil social media club or the rule for what separates the good ones from the bad ones needs updated. HN and TikTok are different and I think being able to articulate what actually makes them meaningfully different is the first step toward useful legislation.
by joecool1029 | 2025-12-11 19:18:14+00:00
I guess I'm in an extreme minority here but... it's not broken if autocorrect is off.

I raw dog my typing everywhere. Zero autocorrect. The last time I did use typing assistance was on BB10 with the 'flick to complete' because it was out of my way enough that I could ignore it was there or use it to save a small amount of time. Otherwise I too have the fond memory of Windows Phone's keyboard (I ran it on the HTC HD2), I couldn't tell you why it was good other than it felt good to use, again without autocorrect.

However, I'm CERTAIN there's an ergonomics thing at play, the 'brain calibration' time for me to type accurately on a big screen takes longer. I ran the original iPhone SE's as long as I could and always carried a second android device that was huge by comparison. Today I have the 15 Pro and a OnePlus 11. If I spend a lot of time using the iPhone it takes a little time maybe 20 minutes or so to stop making easy errors on the OnePlus 11. However, going back to the smaller iPhone after being on the OnePlus for awhile, there's not really an adjustment, I can hit all the letters accurately.

I have large hands, I still want the smaller device. There is extra work to need to move your hand and eyes across a larger device. More space to misclick on.

Swipe to type is enabled on android/ios for me. I use it sometimes, if you are hesitant at all on iOS or have a tendency to drag fingers at all don't enable it or it will mess up your typing. It's of course enabled by default like autocorrect. Some people have issues with it.

Dictation is underrated on iOS at least. It just works better and faster than the shitty autocorrect for typing. Obviously not applicable to a lot of situations but when I don't feel like typing it works really well.

EDIT: And I really have to have it off, I switch between devices too much and even with them learning my style of writing, I write differently for different contexts and each OS does its own thing differently. I don't want to spend the extra mental bandwidth correcting the autocorrect or having to think of how that specific autocorrect will behave.
by CenekAlbl | 2025-12-11 19:18:25+00:00
In agriculture the main ones are collision avoidance, human-machine safety - detecting and computing distance to an object nearby, then crop analysis - counting, measuring the dimensions and estimating ripeness. Warehouse adds use-cases such as inventory tracking, through volume estimation and barcode reading. Navigation (stereo VSLAM is more robust than mono), bin-picking, palletization, free-space estimation for cargo load. Those and many more require accurate depth estimation and strereo vision is the most universally applicable way of doing it, while being accurate and fast enough!
by shadowgovt | 2025-12-11 19:18:32+00:00
As with all things, this can be pushed too far. Microsoft was suffering a maintainability crisis before the transition to Windows XP; their years of bending the API to support customers (which, in the short run, did keep customers to their benefit) was making for a fairly unmaintainable mess of an API surface that then screamed under the strain when the Internet era hit and all those open, under-observed APIs became potential worm attack vectors.
by dinobones | 2025-12-11 19:19:01+00:00
It's becoming challenging to really evaluate models.

The amount of intelligence that you can display within a single prompt, the riddles, the puzzles, they've all been solved or are mostly trivial to reasoners.

Now you have to drive a model for a few days to really get a decent understanding of how good it really is. In my experience, while Sonnet/Opus may not have always been leading on benchmarks, they have always *felt* the best to me, but it's hard to put into words why exactly I feel that way, but I can just feel it.

The way you can just feel when someone you're having a conversation with is deeply understanding you, somewhat understanding you, or maybe not understanding at all. But you don't have a quantifiable metric for this.

This is a strange, weird territory, and I don't know the path forward. We know we're definitely not at AGI.

And we know if you use these models for long-horizon tasks they fail at some point and just go off the rails.

I've tried using Codex with max reasoning for doing PRs and gotten laughable results too many times, but Codex with Max reasoning is apparently near-SOTA on code. And to be fair, Claude Code/Opus is also sometimes equally as bad at doing these types of "implement idea in big codebase, make changes too many files, still pass tests" type of tasks.

Is the solution that we start to evaluate LLMs on more long-horizon tasks? I think to some degree this was the spirit of SWE Verified right? But even that is being saturated now.
by dragonwriter | 2025-12-11 19:19:06+00:00
No, the defining feature of capitalism-as-a-system (as opposed to capitalism-as-a-feature of systems including those which predate capitalism-as-system) is the set and preeminence of property rights, which are very different under fascism, because fascist corporatism subordinates all interests (not least of all property interest) to central authority.

Fascist corporatism is as radically opposed to capitalism as Leninist “democratic centralism” is (and, arguably, despite the opposing rhetorical stance, in very much the same substantive direction in practice.)
by xpe | 2025-12-11 19:19:18+00:00
> I know that "X is destroying democracy, vote for Y" has been a prevalent narrative lately, but is there any evidence that it's true? I get that it's death by a thousand cuts, or "one step at a time" as they say.

I suggest reading [1], [2], and [3]. From there, you'll probably have lots of background to pose your own research questions. According to [4], until you write about something, your thinking will be incomplete, and I tend to agree nearly all of the time.

[1]: https://en.wikipedia.org/wiki/Democratic_backsliding

[2]: https://hub.jhu.edu/2024/08/12/anne-applebaum-autocracy-inc/

[3]: https://carnegieendowment.org/research/2025/08/us-democratic...

[4]: "Neuroscientists, psychologists and other experts on thinking have very different ideas about how our brains work, but, as Levy writes: “no matter how internal processes are implemented, (you) need to understand the extent to which the mind is reliant upon external scaffolding.” (2011, 270) If there is one thing the experts agree on, then it is this: You have to externalise your ideas, you have to write. Richard Feynman stresses it as much as Benjamin Franklin. If we write, it is more likely that we understand what we read, remember what we learn and that our thoughts make sense." - Sönke Ahrens. How to Take Smart Notes_ - Sonke Ahrens (p. 30)
by asdefghyk | 2025-12-11 19:19:22+00:00
Some what (vaguely) related to this topic About surveillance.

I recall a local political and business figure making statements you and/or I are being surveilled by the government. Everyone thought that's not likely , its not possible, he is a bit imbalanced..

After the dumping of documents' from Snowden and Assange it was shown to be possible Things like, if its even possible , it could plausibly be happening. The government has somewhat infinite resources.

The altered software for hard drive hacking for example. Wow. Intercepting packages in mail and altering the software ...