MurphyA/hacker-news huggingface dataset:
by twalk4821 | 2025-11-15 04:37:29+00:00
Well said! To add on: if meaning is largely not "in" the words themselves, but embedded in a shared cognitive space, then in order to have a truly singular (ie "untranslatable") basis point would require positing unique cognitive mechanisms or some experiential quality that is unknown to members of the target language. But as you pointed out, most concepts do have an analogous representation in most languages, even if the tokens in use appear superficially different. And this is merely because the context in this case is a shared cognitive substrate (the low-level operating system, if you will) consisting of sense data, emotions, and so on, which in its fundamental operations does not substantially differ between members of the human race - or so I would argue. In either case, what matters seems to me to be not so much the actual tokens but the experiences or cognitive context in which they are embedded.
by ModernMech | 2025-11-15 04:39:42+00:00
That's not the point, no one uses 99% of languages, so if that's the standard then it's a free-for-all. The PL community is small, so norms are important.

PL naming code is:

1. Whoever uses the name first, has claim to the name. Using the name first is measured by: when was the spec published, or when is the first repo commit.

2. A name can be reused IFF the author has abandoned the original project. Usually there's a grace period depending on how long the project was under development. But if a project is abandoned then there's nothing to stop someone from picking up the name.

3. Under no circumstances should a PL dev step on the name of a currently active PL project. If that happens, it's up to the most recently named project to change their name, not the older project even if the newer project has money behind it.

4. Language names with historical notoriety are essentially "retired" despite not being actively developed anymore.

All of this is reasonable, because the PL namespace is still largely unsaturated*. There are plenty of one syllable English words that are out there for grabs. All sorts of animals, verbs, nouns, and human names that are common for PLs are there for the taking. There's no reason to step on someone else's work just because there's some tie in with your company's branding.

So it's pretty bottom basement behavior for luminaries like Ken Thompson and Rob Pike to cosign Google throwing around their weight to step on another dev's work, and then say essentially "make me" when asked to stop.

* This of course does not apply to the single-letter langs, but even still, that namespace doesn't really have 25 langs under active development.
by CamperBob2 | 2025-11-15 04:39:58+00:00
Hopefully you're right. Assuming that the rift that just opened up between Trump and MTG isn't just a bunch of kayfabe, it may actually hurt Trump more than Greene. It'll make it easy for others to break with him.

I also wouldn't be surprised if Trump's order to open an investigation into Democrats named in the documents, in a blatantly-transparent attempt to get them back under seal, turns out to be a bridge too far. At some point, maybe even the most diehard MAGAs will realize that he's insulting their intelligence.

Meanwhile, reports say that he has been cowering in the White House all day, blasting show tunes at high volume, as he is apparently wont to do when stressed.
by jacquesm | 2025-11-15 04:40:42+00:00
> Now LLMs use that pretty well (even though stuffing everything into an LLM is getting old, and as this article points out, in any specific application they tend to get bested by something like XGBoost with very simple models)

You can't blame the users for that though, for instance, OpenAI's ChatGPT uses 'Ask Anything' as their home page prompt. Zero specialization, expert at anything. And people totally believe it.
by LexiMax | 2025-11-15 04:41:53+00:00
16 years is a bit of an under-estimate. I think the first popular language with this form of declaration was Pascal.

var foo: char;

Go was developed by many of the minds behind C, and inertia would have led them to C-style declaration. I don't know if they've ever told anybody why they went with the Pascal style, but I would bet money on the fact that Pascal-style declarations are simply easier and faster for computers to parse. And it doesn't just help with compile speed, it also makes syntax highlighting far more reliable and speeds up tooling.

Sure, it's initially kind of annoying if you're used to the C style of type before identifier, but it's something you can quickly get to grips with. And as time has gone on, it seems like a style that a lot of modern languages have adopted. Off the top of my head, I think this style is in TypeScript, Python type hints, Go, Rust, Nim, Zig, and Odin. I asked Claude for a few more examples and apparently it's also used by Kotlin, Swift, and various flavors of ML and Haskell.

But hey, if you're still a fan of type before variable, PHP has your back.

class User { public int $id; public ?string $name; public function __construct(int $id, ?string $name) { $this->id = $id; $this->name = $name; } }
by martinvonz | 2025-11-15 04:43:07+00:00
> but splitting is harder than selectively adding after blindly merging all changes.

Is the scenario that you make many changes in the working copy and then run `git add -p` a few times until you're happy with what's staged and then you `git commit`? With jj, you would run `jj split` instead of the first `git add -p` and then `jj squash -i` instead of the subsequent ones. There's no need to do anything instead of `git commit`, assuming you gave the first commit a good description when you ran `jj split`. This scenario seems similarly complex with Git and jj. Did you have a different scenario in mind or do you disagree that the complexity is similar between the tools in this scenario? Maybe I'm missing some part of it, like unstaging some of the changes?
by jacquesm | 2025-11-15 04:43:25+00:00
I think the biggest problem with such classifiers is to actually know what is good data and what is bad data. To take a sample of the data and to recognize whether or not this dataset is a general enough representation of both true and false examples (for a binary classifier) to be able to use it to train a model. Because it isn't rare at all to have data sets that are biased 100 to 1 or more for one of the classes, which contain hints about what class the object is in that isn't in the object itself and so on. You can train until the cows come home on such data but it will never lead to satisfactory results.
by synthetic-echo | 2025-11-15 04:44:01+00:00
Of course, but the dataset was mostly strings that needed to be cross-referenced with GIS data. Tried every library under the sun. The greatest speed up I got was using polars to process the mostly-string CSVs, but didn't help much. With that said, I think polars was also just released when we were working with that dataset and I'm sure there's been a lot of performance improvements since then.
by didibus | 2025-11-15 04:45:32+00:00
I'm not fully able to follow what the article is trying to say.

I got especially confused at the actor part, aren't actors share nothing by design?

It does to say there's only 1 actor, so I guess it has nothing to do with actors? They're talking about GenServer-like behavior within a single actor.

As I write this, I'm figuring out maybe they mean it's like a single actor GenServer sending messages to itself, where each message will update some global state. Even that though, actors don't yield inside callbacks, if you send a message it gets queued to run but won't suspend the currently running callback, so the current method will run to completion and then the next will run.

Erlang actors do single-threaded actors with serialized message processing. If I understand the article, that avoids the issue it brings up completely as you cannot have captured old state that is stale when resuming.
by DarmokJalad1701 | 2025-11-15 04:46:44+00:00
> Reaction wheels can "saturate" if they compensate for rotation more in one direction than the other on net, so propellant is needed to get them back down.

Torque Rods can be used to desaturate wheels without needing any propellant

https://en.wikipedia.org/wiki/Magnetorquer

This is widely used in smaller satellites operating in Earth orbit.

However, this doesn't mean that TFA isn't BS.
by ajlaston | 2025-11-15 04:47:35+00:00
I’ve been experimenting with WebGPU and built a benchmark that simulates and renders up to *15,000,000 moving nodes(rectangles)* in real time in the browser.

Each node has its own position, velocity, size, and color. All simulation and rendering happens entirely on the GPU:

• GPU compute shader updates positions • GPU performs visibility checks • GPU maintains a visibility counter via atomics • Indirect draw calls per chunk • CPU does minimal work (just submits commands)

The demo starts at 50,000 nodes, but you can type any number up to ~15M and reset.

Warning: This is a GPU stress test. Large node counts may cause slowdowns, thermal spikes, or browser crashes on some hardware.

Demo: https://ajlaston.github.io/Nova-Web/

Code: https://github.com/ajlaston/Nova-Web

I’d be interested in performance reports across different GPUs, browsers, and platforms. Feedback on the architecture is welcome.
by lone-cloud | 2025-11-15 04:47:44+00:00
That's how the pros do it. Yes, you can load both a text and image gen models at the same time. Needless to say you'll need a very beefy GPU(s) to do this so I wouldn't recommend it unless you know exactly what you're doing as generally you'll want to max out your VRAM for one model at a time for the highest quality results. Open webui and sillytavern allow both text and image gen from the same UI although I wouldn't recommend it for advanced users. Otherwise Gerbil will give you multiple pages to toggle through via the titlebar dropdown.
by HeyLaughingBoy | 2025-11-15 04:48:01+00:00
>Is it just that I'm not looking in the right places?

Pretty much. That and there's a lot more talk about software because there seems to be this "conventional wisdom" that software people need to blog.

Anyway...

https://www.plctalk.net/forums/forums/plc-questions-and-answ...

https://www.practicalmachinist.com/

https://www.thefdalawblog.com/category/medical-devices/

https://www.eevblog.com/

https://talk.newagtalk.com/forums/forum-view.asp?fid=6

A few off the top of my head. The other thing to think about is that while there are tons of software blogs, sites and forums, 99% of it is just regurgitating the same crap.
by jandrewrogers | 2025-11-15 04:50:15+00:00
The quantity of ticks in the eastern US is insane. I would be in favor of a serious look at eradicating them.

It isn’t too bad in the Mountain West comparatively in my experience, though you have some bad areas in California. I am an outdoorsy person. While I live in the western US my experiences in the woods of the eastern US still stick in my mind. In some areas it was literally crawling with ticks.

I currently live in Seattle. The western side of the Cascade Mountains are essentially devoid of ticks and no one knows why, it is a bit of a scientific mystery. Years of tromping through the bush and I’ve never seen one here, which is great. It does make me wonder if there is something in the ecosystem here that could be adapted to mitigate tick populations elsewhere.
by frmersdog | 2025-11-15 04:50:37+00:00
>gifting sums of money to someone to solve their problems can significantly complicate relationships

Maybe. If you have a relationship. I was thinking more along the lines of listening to someone's story and them finding a check from a mysterious benefactor in the mail sometime later.

>And people hate it when somebody buys a run down building in a poor neighborhood and "invests" in it because now you're making it unaffordable

So don't do that. There are other ways to invest in communities. "Upgrading" housing is couched as the primary way to do so really only because it's a good way to make money (and influence what some people would view as desirable demographic changes).

Better things are possible.
by lmorchard | 2025-11-15 04:51:16+00:00
> Firefox OS: 2013

Apple wouldn't let Firefox onto the iPhone. Pretty big writing on the wall, there. Turns out it's really hard for a sub-billion-dollar company to succeed with a mobile OS, though, which is why we only really have two left. (Even Microsoft couldn't swing it)

> Mozilla caves to Widevine DRM: 2014

Shipping the only major browser that can't play movies, cool cool cool.

> Directory Tiles: 2014

Nearly everything on the web visited with Firefox is funded by advertising. The new tab page is one of the least obtrusive surfaces in the browser that still gets seen. Seemed worth a shot to try building an ad stack in that space which tried not to surveil.

> Pocket acquisition: 2015

Discovery on the web is hard. Maybe that's a job for a browser? Maybe folks will pay for it? Maybe it can pay folks on the web?

> Firefox Focus: 2015

Privacy seems like a good idea. Maybe folks would like a browser that focuses on that?

> Cliqz experiment: 2017

That's Brave Search, these days. Lots of folks seem to like it?

> "Looking Glass" Mr. Robot sponsorship: 2017

I don't know the whole story there. IMO, looked to me like some earnest folks tried to do something fun but rolled a 1 on the d20 for a critical fail. Footguns abound.

Not saying all the above were handled with perfection, but I was there for all of them and there were good folks doing things that made sense at the time. Hindsight is 20/20, I guess?
by snickerbockers | 2025-11-15 04:51:21+00:00
I agree and that's the case I'm trying to make. The machine-learning community expects us to believe that it is somehow comparable to human cognition, yet the way it learns is inherently inhuman. If an LLM was in any way similar to a human I would expect that, like a human, it might require a little bit of guidance as it learns but ultimately it would be capable of understanding concepts well enough that it doesn't need to have memorized every book in the library just to perform simple tasks.

In fact, I would expect it to be able to reproduce past human discoveries it hasn't even been exposed to, and if the AI is actually capable of this then it should be possible for them to set up a controlled experiment wherein it is given a limited "education" and must discover something already known to the researchers but not the machine. That nobody has done this tells me that either they have low confidence in the AI despite their bravado, or that they already have tried it and the machine failed.
by ctxc | 2025-11-15 04:51:37+00:00
How isn't this just fraud?

Expectation is that sensitive meetings run through a pipeline without being exposed to actual people (and if it is for very specific reasons, there are audit trails).

Here, they literally listen to sensitive information and can act on it.

How do you trust they won't do it again to "enhance summaries" or something in the future?
by kayodelycaon | 2025-11-15 04:51:50+00:00
Sofa and couch are only interchangeable in some contexts. They are different “flavors” of similar ideas.

This becomes immediately apparent (and relevant) when writing fiction or poetry. At least it does to me.

Non-fiction and spoken English do not highlight the subtleties between these words because using them interchangeably in the same work is considered bad form.
by pksebben | 2025-11-15 04:52:09+00:00
Yeah, I see both those points and really I agree with both. Actually, I think problem 1 is exacerbating problem 2 by a lot - I get just as mad at the postmillenial dudebro with the get-rich-quick-on-AI scam video as I do with the AI-MBAs of the world.

Actually, that's a lie. The MBAs are still worse. They ought to know better at least.

All I'm getting at is that while we put totally legitimate backpressure on the hype cycle, we should at the same time be able to talk about and develop those elements of this new tech that will benefit us. Not "us the tech vcs" (I am not one of them) but "us the engineers and creatives".

Yes it's disruptive. Yes it's already caused significant damage to our world, and in a lot of ways. I'm not at all trying to downplay that. But we have two ways this goes:

- people (individuals) manage to adopt and leverage this tech to their own benefit and the benefit of the commons. Large AI companies develop their models and capture large sectors of industry, but the diffusion of the disruption means that individuals also have been empowered, in many ways that we can't even predict yet.

- people (individuals) fight tooth and nail against this tech, and lose the battle to create laws that will contain it (because let's be honest, our leadership was captured by private interests long ago and OpenAI / MSFT / Google / Meta have deep enough pockets to afford to buy the legislature). Large AI companies still develop their models and capture whole sectors of industry, but this time they go unchecked due to a fragile and damaged AI industry in the commons. We learn too late that the window to make use of this stuff has closed because all the powerful stuff is gated behind corporate doors and there ARE laws about AI now but basically those laws make it impossible to challenge the entrenched powers (kinda like they do now with pre-AI tech - patent laws and legal challenges to threats to power - like what the EFF is constantly battling).

If we do not begin to steer towards a robust open conversation about creating and using these models, it's only going to empower the people that we are worried about empowering already. Yes, we need to check the spread of "AI in fucking everything". Yes we need to do something about scraping all data everywhere all the time for free. But if we don't adopt the new weapon in the information space, we'll just be left with digital muskets versus armies of indefatigable robots with heat-seeking satellite munitions. Metaphorically(?) speaking.
by burnt-resistor | 2025-11-15 04:52:45+00:00
For context, state-administered food programs paid for by SNAP already treat recipients like criminals with extensive salary, income, assets, and life situation reporting and verification every 6 months to 12 months max. It comes across as just yet another way look down on poor people, waste their time, and spend more money on duplicated means testing already costing significantly more than whatever hunting down every marginal unqualified case hoped to save like "finding" the "welfare queen" or "voting fraud" bogeyman that doesn't exist to demonize one group or another.

UBI would probably be a whole lot cheaper than micromanaging what people can and can't buy while not treating the most desperate people with unkind, perpetual suspicion.

The truth is this is yet another rug pull surprise to screw over poor people. Not just health insurance subsidy revocations or Medicaid cuts, because some people just aren't satisfied with trillions or all the power.
by canjobear | 2025-11-15 04:53:09+00:00
They gave the example of the verb yiwei in Mandarin. If you say “ta yiwei X” it means “s/he thinks X” with a strong connotation that X is in fact false. The Spanish equivalent is supposed to be the verb creerse [1], like if you say “Juan se cree que lo van a ascender” it means “Juan thinks that they are going to promote him” but with a strong connotation that he won’t in fact be promoted. English doesn’t really have a verb for “think” with the connotation that the belief is false. The claim (for what it’s worth, I am skeptical) is that English speakers are slower to learn the concept that someone can have a false belief, because English lacks such a verb.

[1] according to https://ojs.ub.uni-konstanz.de/sub/index.php/sub/article/vie... for example. I don’t know enough Spanish to say if the verb really works this way. Verbs like this are called “contrafactive”
by anon291 | 2025-11-15 04:54:00+00:00
I mean perhaps fair enough. Mumbai is looking really nice these days. Legitimately to the point where i think it would be fun to visit (as opposed to our visits growing up which I dreaded).

> What makes you think they don't exist in Mumbai?

Attempting to walk in Mumbai lol.

> The problem is that the Bay Area is not the heaven, perceived or real, it used to be any more.

Fair enough. It has a lot of problems but the class of problems is different. You are probably correct that those working in tech probably live better in Mumbai than the bay area. I mean having any money at all means having domestic staff and such.
by sho | 2025-11-15 04:54:29+00:00
Of course I can't "prove" it, just like you can't "prove" yours, but I am involved in the field and no-one I know thinks we're even close to a "dead end". On the contrary, people are more bullish than ever.

I don't have any inside knowledge of OpenAI's product release priorities, but your narrative about dead ends and desperate scrambles to push something out the door, tricking investors to keep the party going - this has nothing to do with reality as far as I can tell.
by notepad0x90 | 2025-11-15 04:54:42+00:00
Thanks for the reply, but you are exactly the audience my post is for. Because you say that, we will lose what little figments of privacy and freedoms we have left.

Apple tried and made good progress. They had bugs which could be resolved but your insistence that it couldn't be done caused too much of an uproar.

You can have a system that flags illicit content with some confidence level and have a human review that content. You can make any model or heuristic used is publicly logged and audited. You can anonymously flag that content to reviewers, and when deemed as actually illicit by a human, the hash or some other signature of the content can be published globally to reveal the devices and owners of those devices. You can presume innocence (such as a parent taking a pic of their kids bathing) and question suspects discretely without an arrest. You can require cops to build multiple sufficient points of independently corroborated evidence before arresting people.

These are just some of the things that are possible that I came up with in the last minute of typing this post. Better and more well thought out solutions can be developed if taken seriously and funded well.

However, your response of "Yes." is materially false, law makers will catch on to that and discredit anything the privacy community has been advocating. Even simple heuristics that isn't using ML models can have a higher "true positive" rate of identifying criminal activity than eye witness testimony, which is used to convict people of serious crimes. And I suspect, you meant security, not privacy. Because as I mentioned, for privacy, humans can review before a decision is made to search for the confirmed content across devices.
by card_zero | 2025-11-15 04:54:48+00:00
Which UBI trials do you know about? There's a list here: https://en.wikipedia.org/wiki/Universal_basic_income_pilots

But only six of the listed pilots mention the results.

1970s NIT pilots: no noticeable improvements.

Mincome: significant reduction in hospitalization. Slight decrease in work?

Tribal profit sharing: better homelife for children, parents on the booze less.

Madhya Pradesh: great success.

Netherlands: increased employment slightly, not health.

Finland: improved health slightly, not employment (employment was the goal).

So, I don't know. I suppose it helps, but mostly in Madhya Pradesh.
by Pbhaskal | 2025-11-15 04:56:09+00:00
It has been my go to language since 2020. I was given a task to complete in a week and my lead told just go through Go playground and write the code (it was some snmp receiver/transmit stuff). To my surprise it was so easy to learn, write and more importantly test. Only recent thing i have not learned is generics, hopefully will get their sooner. Coming from java background the things Go did felt so clever and just too good to believe