MurphyA/hacker-news huggingface dataset:
by owenversteeg | 2025-05-04 21:38:48+00:00
You're very welcome!

Heat is a fascinating thing. I can really recommend trying to visualize it and "playing around" with it in your daily life to get a stronger intuition for things. Pay attention to the thermal conductivity of the things around you and how that "feels": aluminum or copper extremely high, other metals high, plastics and woods low, fabrics and foams very low. Notice how evaporating water is very powerful at cooling things down, and how condensing water can warm things up. Notice how a small hot object cools slowly but a larger one can reject the same amount of heat very fast. Inspect the back of your fridge, or the inside of an A/C, and understand what's going on and where the energy is.
by palata | 2025-05-04 21:38:50+00:00
> the exact inverse of how I most often use AI, which is to throw a ton of information at it in a large prompt

It sounds to me that you don't make the effort to absorb the information. You cherry-pick stuff that pops in your head or that you find online, throw that into an LLM and let it convince you that it created something sound.

To me it confirms what the article says: it's not worth reading what you produce this way. I am not interested in that eloquent text that your LLM produced (and that you modify just enough to feel good saying it's your work); it won't bring me anything I couldn't get by quickly thinking about it or quickly making a web search. I don't need to talk to you, you are not interesting.

But if you spend the time to actually absorb that information, realise that you need to read even more, actually make your own opinion and get to a point where we could have an actual discussion about that topic, then I'm interested. An LLM will not get you there, and getting there is not done in 2 minutes. That's precisely why it is interesting.
by jez | 2025-05-04 21:39:00+00:00
Where I especially hold this viewpoint is for end-of-year peer performance reviews.

People say “I saved so much time on perf this year with the aid of ChatGPT,” but ChatGPT doesn’t know anything about your working relationship with your coworker… everything interesting is contained in the prompt. If you’re brain dumping bullet points into an LLM prompt, just make those bullets your feedback and be done with it? Then it’ll be clear what the kernel of feedback is and what’s useless fluff.
by HdS84 | 2025-05-04 21:39:07+00:00
Exactly. In theory, the original windows 10 model is the one most users want: a perpetually up to date os which runs also up to date software. Yes, of there might be reasons the pin something to an older version, but it this pc is on a network, security alone tells you to update ASAP. Don't get me wrong, a working package manager is a very good addition to this model. But currently, most of the time setting up a ltm Linux system I spent on updating ancient git/docker whatever versions.
by sph | 2025-05-04 21:39:41+00:00
Nonsense. I have lived in UK (London) for 13 years, and I'd say I saw on average one thunderstorm a year, and they last just a few minutes [1]. Now back in Italy, it's like every other week during the warmer months.

Anyway, the post provides more information than N=1 anecdotes. UK is just too far north for them.

1: I quite like thunderstorms, and I remember the last time there was one where I lived in N. London. It was a single instance of thunder last autumn, lasted all of 2 minutes. Quite underwhelming to say the least.
by giardini | 2025-05-04 21:39:48+00:00
>Outside a bar in southern Arizona in 1890, a stagecoach driver stumbled into the night and fell asleep in the open air, unknowingly becoming host to hundreds of screwworms while passed out drunk. The parasitic insects made their way through his nose, into his throat, and eventually killed him — a grim but once relatively common occurrence.<

From

"Screwworm eradication lessons from a longtime veterinarian"

https://www.agdaily.com/livestock/screwworm-eradication-less...

An excellent article on the realities of screwworm in USA. It also speaks of topical treatments! Unfortunately though and to our great loss no doubt, it does not go into detail about "the scrotal area post castration" of unsnap_biceps fascination on these posts nor "lambs ...licking the topically applied ivermectin" so titillating to 8note. (FWIW ivermectin pour-ons contain ethanol.)
by johnny22 | 2025-05-04 21:39:53+00:00
> Clearly I'm wrong, but how is it that windows can have portable apps of a similar size to their installable versions and Linux cann

They can't depend on many apis existing or at the right version. Linux distros are made from a collection of various third party projects and distros just integrate those. Each of these third party projects has it's own development speed and ABI and API stability policies.

Each distro also has it's own development speed and release policy, which means they might have things that could either be too new or to old. Most distros try to avoid packaging multiple versions of the same project when they can avoid it to ease maintenance as well.

Heck, you can't even guarantee that you have the exact same libc. Most distros use glibc, but there are plenty of systems that use musl.
by sillywalk | 2025-05-04 21:40:18+00:00
Ars Technica has a couple of good articles about JTRS from 2012[0] and 2018[1].

EDIT: Link from the 1st article to a report by David Axe @ The Center for Public Integrity[2].

[0] https://arstechnica.com/information-technology/2012/06/how-t...

[1] https://arstechnica.com/information-technology/2018/03/the-a...

[2] https://publicintegrity.org/national-security/failure-to-com...
by spencerh21 | 2025-05-04 21:40:28+00:00
Lately, I've been thinking a lot about how much sensitive information we're all feeding into AI tools without really stopping to consider the consequences.

At first, it was harmless - asking ChatGPT to help draft emails, summarize articles, or brainstorm ideas. But over time, my prompts got more detailed. I started including real client names, project info, company data… even things like meeting notes or internal discussions. It felt natural, convenient, but I started thinking a lot more about my privacy

No one reads the terms of service, and even when companies say they don’t store your prompts, the truth is murky. And the more AI becomes integrated into daily workflows, the easier it becomes to overshare, especially when you're moving fast. So I built a tool to protect myself.

It’s called Redactifi. It's a browser extension that detects and redacts sensitive information from your AI prompts before they’re ever sent. It runs entirely on your device, no cloud processing, no logs, no storage. You just write your prompt, click a button, and it automatically scrubs out things like names, emails, phone numbers, company info, and more.

Curious if anyone else has been feeling the same tension - using AI more, but trusting it less?
by generativenoise | 2025-05-04 21:40:51+00:00
Would be nice to fix the performance reviews so we don't end up in a arms race of creating bloat until it becomes so unproductive it kills the host.

Over-fitting proxy measures is one of the scourges of modernity.

The only silver lining is if it becomes so wide spread and easy it loses the value of seeming sophisticated and thorough.
by staunton | 2025-05-04 21:40:57+00:00
I've never met someone like that and don't believe the claim.

Maybe you mean people who are bad at interviews? Or people whose job isn't actually programming? Or maybe "lots" means "at least one"? Or maybe they can strictly speaking do fizzbuzz, but are "in any case bad programmers"? If your claim is true, what do these people do all day (or, let's say, did before LLMs were a thing...)?
by necovek | 2025-05-04 21:41:10+00:00
Is "what has been my experience" not implied in what I am still waiting for — "someone using an LLM to produce high quality code in the field of their expertise in less time than without an LLM"?

So, observing a couple of my colleagues (I am an engineering manager, but have switched back and forth between management and IC roles for the last ~20 years), I've seen them either produce crap, or spend so much time tuning the prompts that it would have been faster to do it without an LLM. They mostly used Github Copilot or ChatGPT (most recent versions as of last few months ago).

I am also keeping out a keen eye for any examples of this (on HN in particular), but it usually turns out things like https://news.ycombinator.com/item?id=43573755

Again, I am not saying it's not being done, but I have struggled to find someone who would demonstrate it happen in a convincing enough fashion — I am really trying to imagine how I would best incorporate this into my daily non-work programming activities, so I'd love to see a few examples of someone using it effectively.
by krisoft | 2025-05-04 21:41:34+00:00
> while you read, do the math in your head and think about what OP was trying to say.

I did the math in my head. Before i read their comment in fact. Did calculations both on paper and spreadsheets too. Run simulations, and field tests too. Based on what i know i do not believe that the latency imposed by the frame rate of the cameras is a limiting factor on self-driving car performance or safety. I was asking to see if they have some particular scenairo in their mind to check if maybe i’m missing something. If anything I’m much more concerned about the latency of brake actuators.

> The point - latency is a cold and often uncalculated bitch that will screw with reliability and integrity of the system - got across to me quite easily.

Ah, ok. If we are just catching the vibes, then sure. The vibes are great.
by bsdetector | 2025-05-04 21:42:04+00:00
Would this be far enough out to use the sun's gravitational lensing to image distant planets?

It seems like the idea was to send a bunch of instruments way out and then take pictures in the brief time they were at a useful distance, but if there's a planet out there we can orbit and so stop the instruments at that distance it seems like we could make a permanent super telescope.
by crush_robo_1536 | 2025-05-04 21:42:41+00:00
I think they'll still continue to matter. Ofc if you're just trying to write some simple code you don't really need a degree, but I'd trust someone who understands the fundamentals of computing way more than someone who doesn't when it comes to working on complex optimization problems (like squeezing the last bit of efficiency from your CPUs). I know AI is getting really good at all this stuff, but I still think that there have to be people that understand this stuff deeply (even if they use AI to develop this deep understanding). It also shouldn't take 4 years for a CS degree now imo given that it is so much easier to grasp concepts with LLM assisted learning.
by smallstepforman | 2025-05-04 21:42:56+00:00
Secure boot is a problem for users with secondary alternative OS’s (eg Haiku). I even have a DOS tool which needs high precision timing which no general purpose multitasking OS can provide. These alternative systems are hampered by secure boot.

And speaking of up to date video drivers, these checks are a plague of usability. If I have stable driver rev 235, why would I install latest buggy version 246? Eg. AMD has 2 flavours of drivers, Adrenalin which has “optimisations”, but crashes, and the Pro drivers which are older but more stable, and have 10 bit support, more colour spaces etc. I’m done dealing with experimental drivers, give me stability 100% time. Games which insist that I run experimental drivers and secure boot can get stuffed.
by p_l | 2025-05-04 21:43:02+00:00
Non trivial amounts of industrial and civil infrastructure, sometimes the air gapping is also because there's no viable connectivity more so than security reasons (or you have to assume flaky network so the system is designed to operate as separated island 99% of time - for unlikely example Chick-Fil-A has such requirements for their k8s clusters running individual restaurants.

Sometimes it's also simpler to physically air gap a system than to deal with more complex security.
by NewJazz | 2025-05-04 21:43:17+00:00
I'm sitting staring at an 8W filament led Edison bulb, 800 lumens. For a zigbee bulb I found, 11W, 1100 lumens. And I think they include ZigBee overhead in their 11W? Don't even need PoE+ for that.

It would just come down to chip and maybe power cost difference between Ethernet with PoE vs wireless with traditional 120V electrical wiring. Pretty pointless to retrofit I'd think, but for new construction it could be viable.
by vidarh | 2025-05-04 21:43:38+00:00
Not liking Oberon is fine, but calling it a "generic half-assed language" is at best grossly ignorant of the effort that went into the design. Wirth had a very clear philosophy for his language, that he followed relentlessly. If you don't like that philosophy, you won't like Oberon, but there's nothing half-assed about it.

With respect some of your points, the lack of support for early returns is one of those philosophical decisions, as is many of the other "missing" features.

Many of them were implemented in various versions by students of Wirth. Polymorphism for Oberon was the subject of at two projects at EHTZ in the 90's, including an at the time fairly novel approaches for a runtime extensible vtable approach to polymorphism.

As for your #5, to me that's one of the most horific warts I can think of in the languages that use it, but again a question of philosophy, and certainly one aspect of Go I detest.

But to go back to Oberon, as a language user, I find Oberon too austere, but as an implementer, the design is beautiful in its simplicitly and how clean it is, and I wish more language implementers paid attention to Wirths work as a starting point, and paid attention to his systematic approach to language design - even if I'd prefer a result that isn't as minimalist.
by pyrale | 2025-05-04 21:44:07+00:00
Here are a few other genocides of the 20th century: the Armenian genocide [1], Porajmos [2], the Rwandan genocide [3].

Please enlighten us on how pointing similarities in the administrative involvement, the systemic nature of the targetting, the harnessing of technology, or the way individuals perpetrating it are made to feel less accountable is, in your words, "highly inappropriate".

I honestly don't see how you could make such a claim for all these examples without negationism.

[1]: https://en.wikipedia.org/wiki/Armenian_genocide [2]: https://en.wikipedia.org/wiki/Romani_Holocaust [3]: https://en.wikipedia.org/wiki/Rwandan_genocide
by johnfn | 2025-05-04 21:44:26+00:00
> I guarantee 99% of the returns will return a very formulaic physics-based puzzle response like "The Resonant Hourglass"

Haha, I was suspicious, so I tried this, and I indeed got an hourglass themed puzzle! Though it wasn't physics-based - characters were supposed to share memories to evoke emotions, and different emotions would ring different bells, and then you were supposed to evoke a certain type of story. Honestly, I don't know what the hourglass had to do with it.
by necovek | 2025-05-04 21:44:27+00:00
Not really: I love reading fiction where I can imagine characters the way I want to based on their written depictions. When I see a book cover replaced with a recent movie adaptation actor, it usually reduces the creative space for the reader instead of enlarging it.

Video in itself is not more information by definition. Just look at those automatically generated videos when you try finding a review on an unusual product.
by stavros | 2025-05-04 21:45:38+00:00
Agreed, you need to know three things:

* Sketch a 2D design on a surface * Make the elements in that design depend on each other (this is parallel to that, this is equal to the other, X is at an angle to Y) as much as possible * Pull the 2D shape up into 3D space

Now you know how to design your own things! The rest is just learning the buttons, but there's usually one called "sketch", one called "constrain", and one called "extrude".
by buu700 | 2025-05-04 21:45:55+00:00
To be clear, I'm not a student, nor do I disagree with academic honor codes that forbid LLM assistance. For anything that I apply AI assistance to, the extent to which I could personally "claim credit" is essentially immaterial; my goal is to get a task done at the highest quality and lowest cost possible, not to cheat on my homework. AI performs busywork that would cost me time or cost money to delegate to another human, and that makes it valuable.

I'm expanding on the author's point that the hard part is the input, not the output. Sure someone else could produce the same output as an LLM given the same input and sufficient time, but they don't have the same input. The author is saying "well then just show me the input"; my counterpoint is that the input can often be vastly longer and less organized or cohesive than the output, and thus less useful to share.
by hoten | 2025-05-04 21:46:32+00:00
If you can't fully connect your results in the game to your skill (because you can't trust if the others cheated), then you can't trust you are improving (or how to adapt to maybe improve).

On an evolutionary level, the purpose of play is to improve your skill in something in a tight, enjoyable feedback loop. Cheating messes with that.

Though your approach is preferable, I do think cheating (or more broadly, not trusting that you can learn how to improve with further play) kneecaps the whole point of playing.

(I'm badly presenting an idea I learned from Jonathan Blow re: how some game design ideas, such as opaque adaptive difficulty like rubberbanding found in racing games, destroys the purpose of playing)
by dmillar | 2025-05-04 21:46:36+00:00
What the "right answer" is will vary widely on application and analyst. That's one reason there are so many coordinate ref systems. If you keep everything in 3857, you'll get answers in ~meters, but whether that's "right" depends on where and how large the distance or geom is and what your precision threshold is. So, really, everyone's needs are necessarily "specific."
by musicale | 2025-05-04 21:47:09+00:00
> LLMs are like anti-compression algorithms when used like that, a simple idea gets expanded into a bloated mess by an LLM,

I think that's the answer:

LLMs are primarily useful for data and text translation and reduction, not for expansion.

An exception is repetitive or boilerplate text or code where a verbose format is required to express a small amount of information.
by woodson | 2025-05-04 21:47:35+00:00
Oh, that’s pretty slow. Have you tried using quantization (int8 or int8_float32)? In my experience that can help speed up CT2 execution.

Personally, I haven’t had much luck with small-ish decoder-only models (i.e., typical LLMs) for translation. Sure, GPT4 etc. work extremely well, but not so much local models capable of running on small form-factor devices. Perhaps I should revisit that.
by whatnow37373 | 2025-05-04 21:47:37+00:00
I can see how it is a possible source of confusion which is something we can ill afford in this already treacherous waters.

> But the biases of people are legitimate, while the biases of the elites are illegitimate. > [...] > while protecting legally recognized rights

Agreed, provided that by "elites" we mean the branches of government not just "successful people". I guess we're mostly in agreement. I'm just cranky about The People because in my country they are quite ... self-destructive, but that is a topic for another time.
by klabb3 | 2025-05-04 21:48:04+00:00
Disagree. There is almost no decision making in converting to use i18n APIs that already have example use cases elsewhere. Building a frontend involves many decisions, such as picking a language, build system, dependencies, etc. I’m sure the LLM would finish the task, but it could make many suboptimal decisions along the way. In my experience it also does make very different decisions from what I would have made.
by kayodelycaon | 2025-05-04 21:49:13+00:00
I think his argument about draw weight is compelling. In order to do a coordinated valley you would have to have everyone draw and hold.

Bows have highly variable “lock time”. There is no trigger and you can’t reasonably get an army to draw at the same rate.

Reload times are fast enough that the fastest archer may be able to be ready to fire again before the last archer has completed their first shot.

In those circumstances, you would simply get orders to start and stop firing.
by sieve | 2025-05-04 21:49:14+00:00
Depends on the situation.

I like reading and writing stories. Last month, I compared the ability of various LLMs to rewrite Saki's "The Open Window" from a given prompt.[1] The prompt follows the 13-odd attempts. I am pretty sure in this case that you'd rather read the story than the prompt.

I find the disdain that some people have for LLMs and diffusion models to be rather bizarre. They are tools that are democratizing some trades.

Very few people (basically, those who can afford it) write to "communicate original thoughts." They write because they want to get paid. People who can afford to concentrate on the "art" of writing/painting are pretty rare. Most people are doing these things as a profession with deadlines to meet. Unlike you are GRRM, you cannot spend decades on a single book waiting for inspiration to strike. You need to work on it. Also, authors writing crap/gold at a per-page rate is hardly something new.

LLMs are probably the most interesting thing I have encountered since I did the computer. These puritans should get off of their high horse (or down from their ivory tower) and join the plebes.

[1] Variations on a Theme of Saki (https://gist.github.com/s-i-e-v-e/b4d696bfb08488aeb893cce3a4...)
by margalabargala | 2025-05-04 21:49:34+00:00
I agree that the system can become unstable. Clearly; it's being made unstable currently.

I disagree that it must become unstable, especially on a time frame relevant to anyone currently alive. Perhaps certain resources could be sheparded more sustainably than they have been but I do not think we were previously heading towards a consequence worse than we are currently experiencing.

That argument applied to current administrative actions is like saying "we all die someday, therefore we should all commit suicide right now".
by NewJazz | 2025-05-04 21:49:41+00:00
Saw a 24 port Juniper PoE+ switch for around $450. EX3300-24P. And a 48 port variant. Only 400 and 700 Watt output respectively. But that is enough for ~15W per fixture, which should get well above 1000 lumens.

I'll admit that at a certain point it is a lot of switches to manage.
by prkl | 2025-05-04 21:50:00+00:00
This reads like privacy-invasion propaganda directly from the Chinese state. "Look how great we are at having full control over your PC. You know, to battle cheaters!".

Kernel-level anticheat is ridiculous. Especially when your data becomes a gaping would ready for the chinese state to stick their fingers into and twist around. It's like the police installing mandatory cameras in everyones house to catch thieves (if society here is games with kernel-level cheats).

I want to go back to the days of Windows 7. When there was minimal corporate bloat in the ecosystem, no ads in the startmenu, and when game studios actually knew what they were talking about and had some balls to stand up for their values.