MurphyA/hacker-news huggingface dataset:
by Animats | 2025-07-18 04:46:47+00:00
That's what I was thinking, too. All but one of those parts can be easily milled from flat plate. The yoke end is a bit harder, but yoke ends are cheap standard parts and there's probably an off the shelf solution. The ball joints they use are standard R/C car parts. Those are available in in a stronger form, nylon with a brass ball, for EUR 0.53.[1] It won't be hard to strengthen this design so it can do useful work.

[1] https://toni-clark-shop.com/Ball-Joint-for-M2-and-M3
by LambdaComplex | 2025-07-18 04:47:07+00:00
I just gave it a shot; I would definitely need more than 25 minutes.

> I am not sure I'd get the adjacent mines part correct on the first attempt

Yeah, getting to that point was easy. Solving that problem is where I got stuck. I'm sure I'd get it eventually, but getting to that point and figuring that out in 25 minutes is asking a bit too much.
by Dilettante_ | 2025-07-18 04:47:14+00:00
I do not (confidently) know how to make fire from "scratch". I do not know how to butcher or skin an animal. I do not know how to spin cloth, nor how to stitch it into clothing. My "finding the perfect kind of stone for knapping into a handaxe" muscles have fully atrophied.

We live in a society. That means giving up self-sufficiency in exchange for bigger leverage in our chosen specialisation. I am 110% confident that when electric power became widespread, people were making the exact same argument against using it as you are making now.
by joegibbs | 2025-07-18 04:47:34+00:00
That's not that much better - 12.5% stopped working and didn't do anything at all.

I think that would also massively increase if the money was guaranteed to keep coming in for the rest of their lives. And even if the percentage stayed flat it would be an economic disaster - an increase of 12.5% of the population unemployed would be worse, in the US, than peak COVID. Another 12.5% going off to school still gets them out of the workforce, and would worsen elite overproduction.
by noduerme | 2025-07-18 04:48:05+00:00
"being curious" carries a lot of weight here.

I mean, I was so curious, I started coding as a kid and got a tech job right out of high school. But I quit it at 19 because it didn't answer any of my questions about life. I moved to another city, waited tables, bartended, joined a band, drove a taxi, wrote a few novels, and started making indie games on the side. Eventually, the thing I found that I was most curious about was actually the intersection of code and art, and the way those things could be made to play off each other. That was the language in which I could best express myself and do truly original things.

To be intellectually curious is a rare thing these days. It's the main deciding factor if I'm hiring someone. Or going on a date.
by forgotoldacc | 2025-07-18 04:48:14+00:00
> We were ignorant of many things in the 90s.

Will people 30 years from now say we were enlightened in the 2020s? Or will we look back at 1/6 being on psychiatric medication as being a bit strange?

Doctors also used to give out antibiotics for any illness, now we realize a more targeted approach is much, much better since most illnesses not only don't need antibiotics, but they can make problems worse when improperly prescribed. And I only saw talk of this go mainstream within the past 15 years.
by fc417fc802 | 2025-07-18 04:49:22+00:00
Yes, I'm well aware that it isn't magnetic. I'm not sure what your point is? The typical user doesn't care about the technology behind a given storage medium, only the performance characteristics such as cost, density, latency, cycle durability, power draw, environmental hardiness, and retention time.

> spinning disks are magnetic storage and even today are cheaper than flash memory on a unit cost basis

Presumably not for much longer though. Unless there has been a major upset recently?

> the market for it never materialized and the cost of continued investment wasn't worth it

An entirely empty statement. I was suggesting that unpowered retention time is almost certainly not what led to the failure. The point I'm making is that consumers are impossibly cost conscious in this area.

We already tried the pitch of "clearly technically superior in every metric that matters, but noticeably more expensive" and the market soundly rejected it (much to my eternal dismay). So again I'll ask, is there any reason to expect this new type of magnet to be able to compete with flash memory on a unit cost basis? Because if not I assume it's doomed.
by rendaw | 2025-07-18 04:49:31+00:00
> What would it even mean for lifestyle choices to directly cause some condition?

Eating a diet largely of white rice directly causes beriberi. At least 9/10 people will get beriberi if they eat a diet that's mostly white rice. The median human body needs a certain amount of thiamine to operate properly, and without that certain body functions will cease to occur properly.

Eating too much spinach will cause kidney stones, but by exacerbating a different underlying cause (not directly). 9/10 people will not get kidney stones by eating too much spinach. Making the lifestyle choice to eat smaller amounts of spinach than the general population will protect against kidney stones, but it doesn't mean that spinach is bad to eat.

Without knowing the difference in bodily makeup that allows spinach to influence the occurrence of kidney stones, doctors will vilify spinach. But once the bodily factor that causes this will known, they'll either be able to treat that or recommend lifestyle (diet) changes specifically to the people who have that mutation, rather than vilifying spinach in general.
by parineum | 2025-07-18 04:49:34+00:00
The more apt comparison seems to be somewhere closer to an athlete that played sports with his friends all day instead of weight training for that same sport and getting instruction.

Most people excell with guidance and instruction but there are plenty of people who excel on their own and occasionally, because they don't know any better, end up doing something nobody ever thought to do or were taught was impossible.
by honorable_coder | 2025-07-18 04:50:41+00:00
Hi HN — we're the team behind Arch (an open-source edge and service proxy for agents)[1], and today we're releasing Arch-Router (https://huggingface.co/katanemo/Arch-Router-1.5B), a 1.5B LLM router model designed to align to user-defined preferences, not public benchmarks and leader boards.

As teams integrate multiple LLMs - each with different strengths, styles, or cost/latency profiles — routing the right prompt to the right model becomes a critical part of the application design. But it's still an open problem. Most routing systems fall into two camps:

- Embedding-based routers use intent classifiers — label a prompt as “support,” “SQL,” or “math,” then route to a matching model. This works for simple tasks but breaks down in real conversations. Users shift topics mid-conversation, task boundaries blur, and product changes require retraining classifiers.

- Performance-based routers pick models based on benchmarks like MMLU or MT-Bench, or based on latency or cost curves. But benchmarks often can't capture what matters in production: domain-specific quality or subjective evaluation criteria. These routers are often opaque, difficult to debug, and their quality judgments can feel arbitrary, failing to capture the subjective nuance of what a “good” response actually means for a specific user’s intent.

Arch-Router takes a different approach: route to LLMs based on preferences written as policies in plain ol English.

You write policies like “contract clauses → GPT-4o” or “quick travel tips → Gemini Flash.” The router maps the prompt (and the full conversation context) to those policies using a lightweight 1.5B auto-regressive model. The model is capable to handle intent drift, supports multi-turn conversations, and lets you swap in or out models with a one-line change to the routing policy. To read more about the strength of our model, check out our research paper here: https://arxiv.org/abs/2506.16655

Essentially, Arch-Router splits the routing process into two distinct parts:

Route Selection: This is the what. The system defines a set of human-readable routing policies using a “Domain-Action Taxonomy.” Think of it as a clear API contract written in plain English. A policy isn’t just intent_123; it’s a descriptive label like Domain: ‘finance’, Action: ‘analyze earnings report’. The router’s only job is to match the user’s query to the best-fit policy description. Model Assignment: This is the how. A separate, simple mapping configuration connects each policy to a specific LLM. The finance/"analyze earnings report" policy might map to a powerful model like GPT-4o, while a simpler general/"greeting" policy maps to a faster, cheaper model.

Specs:

- 1.5B params — runs on a single GPU (or CPU for testing)

- No retraining needed — point it at any mix of LLMs

- Outperforms larger closed models on our conversational routing benchmarks (details in the paper)

Links:

[1] Arch Proxy: https://github.com/katanemo/archgw
by Cagrikartal | 2025-07-18 04:51:04+00:00
curious, maybe one could go and spin up a study for using claculators instead of calculating manually and how it can lead to less x type of thinking and affect our abiltiy but maybe even if that is true(i am not sure maybe it is just in the domains we dont feel like we need to care much or etc) would people quitting clacutors a good thing for getting things done in the world ?
by throw10920 | 2025-07-18 04:51:13+00:00
> expensive

Citation needed

> harmful

Citation needed

> little reason to think the bad experiments would adopt the winner

What does this mean? Not a coherent sentence.

> that we can even measure the best outcome

So, exactly the same as when it's done at the federal level.

> for a lot of stuff - we don’t need experiments, we know what works

In terms of legislation? Factually incorrect. Legislation/regulation is extremely difficult to get right and it's incredibly rare that there's precedent that is universally-agreed-upon to be beneficial in general, let alone when the states don't try their hand first.

> As an example, is there any reason to think we need to do experiments on whether children are fed at school for free?

Again, what does this mean? This isn't a coherent sentence either.
by YZF | 2025-07-18 04:51:57+00:00
By the time I got to university I already knew C and the socket APIs and have been paid for delivering software that uses them. I had a friend who made a lot of money selling games he wrote in high school for the C64. Both of us were well ahead of new grads in terms of raw programming skills.

What I was missing were things like Calculus, Linear Algebra, Discrete Math (I knew parts having read TAOCP but had gaps). I knew data structures and algorithms but learnt some I didn't. I had some other random theoretical exposure but the CS program plugged some holes and I did learn random things I didn't know. I also learned more about how to learn.

I think the CS program made me more well rounded. I don't think it made me a better programmer. There was zero challenge for me in all the programming related courses. Where I had to work was on the math and theory side.
by ironmagma | 2025-07-18 04:52:04+00:00
To push back on this article's thrust, those are actual issues that can occur with dependencies. It's just that they usually don't, and most dependencies are harmless, small, and transparent, so articles like this and people complaining about dependencies are almost always overstating their case.

And therefore, adopting a "zero dependencies" policy is absolutely an overreaction.
by deadbabe | 2025-07-18 04:53:14+00:00
If you pair a self taught engineer with a classically trained engineer, the self taught will dramatically reap benefits from the collaboration but the reverse isn’t true.

A true 4 year CS curriculum is so theoretical you basically have to self teach to do anything practical once you leave the university. But due to the intuition you gain in university, your teaching process happens much faster and can hone in on specific correct paths, which contrasts with the pure self taught engineer who maybe stumble around longer or get trapped in local minimums.

Some self taught engineers may never truly grasp certain high theoretical concepts because they never occur often enough in the wild, but the CS degree holder will at least know these concepts exist and where they might apply. This is what can make the difference in a business’s competitive edge.

Nowadays though, I’m growing cynical of a lot of people trying to enter the industry as self taught, as many are simply chasing the high salary and easy lifestyle of the typical software engineer. You need to figure out quickly if you’re dealing with a true enthusiast or just someone chasing a good job. It’s safer to just go with the CS degree, but even there you have the same problem, the people entering the industry just aren’t built like they used to be.

Sorry if this is a little rambly, it’s late.
by ninetyninenine | 2025-07-18 04:53:31+00:00
The free world is under WW2 levels of threat? Listen to yourself. You’re brainwashed. Is China slaughtering Jews like the holocaust? Is China trying to wage war against the world and build an empire? Nobody actually wants war. In fact if war happens it will be the US getting into the whole Taiwan and China conflict that is none of its fucking business in the first place.

The world is building military defense against a threat that will never materialize. That’s one half the story. The other half of the story is a big economic dick measuring contest where the country with the most military might (that they will never use) is the better country.
by motorest | 2025-07-18 04:53:34+00:00
> Then it's a real bad case of using the LLM hammer thinking everything is a nail. If you're truly using transformer inference to auto fill variables when your LSP could do that with orders of magnitude less power usage, 100% success rate (given it's parsed the source tree and knows exactly what variables exist, etc), I'd argue that that tool is better.

I think you're clinging onto low-level thinking, whereas today you have tools at your disposal that allow you to easily focus on higher level details while eliminating the repetitive work required by, say, the shotgun surgery of adding individual log statements to a chain of function calls.

> Of course LLMs can do a lot more than variable autocomplete.

Yes, they can.

Managing log calls is just one of them. LLMs are a tool that you can use in many, many applications. And it's faster and more efficient than LSPs in accomplishing higher level tasks such as "add logs to this method/methods in this class/module". Why would anyone avoid using something that is just there?
by physicles | 2025-07-18 04:53:42+00:00
Tab autocomplete in Cursor is surprisingly good at guessing what I want to log when I type slog.Info. I’m enjoying that time save.

I agree with K&R about debuggers: when writing services that you need to debug in prod, you live and die by your logs. That said, sometimes an interactive debugger is faster than adding logs, like when you’re not sure about the precise call stack that leads to a given point, or there’s a bunch of stuff you need to keep track of and adding logs for all of it is tedious. But pretty quickly you can hit a point where you’re wasting more time in the debugger than it would’ve taken to add those logs…
by spauldo | 2025-07-18 04:54:49+00:00
I would say that it failed in its primary goal - to be a single language used for government software.

That doesn't say anything about the quality of the language, just that the goal for it was unrealistic. If the DoD had pressured Microsoft to support Ada in the same way they supported C++, Visual Basic, and vbscript, they might have been able to pull it off. But with the COTS directive and the utter lack of Ada support from commercial vendors, it was just never going to happen.
by moomoo11 | 2025-07-18 04:54:51+00:00
I'm cynical person, and IME the former are some of the most annoying and usually the worst engineers I've met.

Most people who "mentor" other people (like, make it a pride and distinction part of their identity) are usually the last people you want to take advice from.

Actual mentors are the latter group, who juniors seek out or look up to.

In other words, the former group is akin to those people on YouTube who try to sell shitty courses.
by ipnon | 2025-07-18 04:55:19+00:00
It's pretty clear to me that every member Big Token is converging on practically identical models and they're now just competing on compute efficiency based on their particular capital situation. So in the short-term products like Terragon might be nerfed. But in a year or two (2027!) it's hard to imagine OpenAI, Google, Anthropic, Mistral, and so on not all having terminal modes with automatic background agent creation and separate Git branching. At that point it's a race to the bottom for consumer prices.
by Scarblac | 2025-07-18 04:56:14+00:00
It's a classification proposed by a Brasilian researcher at the university of Sao Paolo, not European. [0]

He noticed a trend of obesity among the poor in the 90s and did statistical analyses to group ingredients into more traditional and more highly processed groups. An ingredient like cheese probably isn't the cause of the obesity epidemic among the poor as it already existed long before it.

I think the main advantage of using Nova is that so many other studies did, so results can be compared. That's an important advantage.

And it's good enough to show health differences between processed foods and traditional foods. There must be something to it, even if it's not perfect.

[0]: https://en.m.wikipedia.org/wiki/Nova_classification
by AdieuToLogic | 2025-07-18 04:56:32+00:00
> The scheduler that puts your program on a CPU works probabilistically. There are no rigid guarentees of workloads in Linux. Those only exist in real time operating systems.

Again, the post to which you originally replied was about code generation when authoring solution source code.

This has nothing to do with Linux, Linux process scheduling, RTOS[0], or any other runtime concern, be it operating system or otherwise.

0 - https://en.wikipedia.org/wiki/Real-time_operating_system
by noduerme | 2025-07-18 04:57:13+00:00
>> it is pretty obvious that self-taught people on average have nowhere near the hundreds of hours of experience solving theoretical problems

What makes you think that? Simple example: I'm self-taught. Failed pre-Calculus in high school, twice. Ten years in as a freelance programmer, I decided to build the first Bitcoin poker room, and therefore had to write my own poker hand evaluator. I had no example to work from. No logic flow-chart. I had to come up with the logic to parse, rank and show winning odds on anything from 5- to 7-card stud, hold'em and omaha hands. I had to dive deep into Monte Carlo methods, statistics, etc. Meanwhile, I'm writing a HUD for Star Citizen. I'm reading and learning about avionics, working out my own procedural generators in mixed 2D/3D. And this was just one year of my life as a developer. Working 16 hours a day, 7 days a week. Couch potato? Forget about the fact that I was getting paid, not paying tuition to sit in a classroom. These were problems I had to solve, and the work output was immediately in production, and the results were immediately visible.

Talk about sweeping generalizations...
by motorest | 2025-07-18 04:57:28+00:00
> This. Set up your dev env and pay attention to details and get it right. Introducing function declarations before knowing what assembly instructions you need to generate is asking for trouble before you even really get started accruing tech debt.

Old heads cling to their tools and yell at kids walking on lawns, completely unaware that the world already changed right under their noses.
by opello | 2025-07-18 04:58:47+00:00
I was trying to recall just how early "Big N" was a nickname for Nintendo, thinking it must have predated the Nintendo 64, but it took a bit of digging to find anything concrete:

https://archive.org/details/run-magazine-87/page/n17/mode/1u...

My naive first thought was "Captain N: The Game Master" but that wasn't quite "Big N." But it was fun to visit a bunch of old Nintendo-related articles.
by adrian_b | 2025-07-18 04:59:05+00:00
There already are known many trans-neptunian bodies whose movements are synchronized with Neptune. Pluto is also among those.

However all the others are closer to Neptune, therefore the ratios between their revolution periods an that of Neptune are relatively small rational numbers, while for this new object the ratio is 10, which is much greater.

So for now, it is one such object among many, so it may be called "rare", at least until others are discovered. In any case it was unexpected that resonances still exist at such distances.
by rf15 | 2025-07-18 04:59:10+00:00
> while lactose and butter fat are at best useless for nutrition and at worst harmful.

They carry energy, and thus are useful. They would only become harmful if you would produce so much that our bodies, adopted for scarcity, were presented with an excess amount of it over longer periods. And you wouldn't build a society and industry around that kind of production, right? Right?
by opello | 2025-07-18 05:00:10+00:00
I replied in another thread [1] but this was the earliest thing I could find in online resources, but maybe your recollection would lead to something earlier:

https://archive.org/details/run-magazine-87/page/n17/mode/1u...

[1] https://news.ycombinator.com/item?id=44601355
by a_bonobo | 2025-07-18 05:01:10+00:00
There's a lot you can do in terms of efficient token usage in the context of Claude Code, I wouldn't be surprised if they soon launch a Claude Code-specific model.

In my experiments, it would be enormously wasteful in token usage, doing things like re-reading all Python scripts in the current folder just to make sure all comments were up-to-date, or it re-read an R script to make sure all brackets were closed correctly. Surely that's where a good chunk of the waste comes from?
by N1H1L | 2025-07-18 05:01:22+00:00
There are a lot of errors in that article. Like line 1, the idea that foreign students get jobs before Americans do. Quite the opposite in real life. Go to any school, and see the employment rates in that school for US vs foreign students.

Also H1B pays FICA taxes, that exemption is only for OPT. The OPT exemption can be easily removed.
by jbotz | 2025-07-18 05:03:30+00:00
While comparing things... a colony of leaf-cutter ants (which form some of the largest colonies with as many as 2 million individuals when the colony is mature) has roughly the same metabolic rate as cow (easily measured from the CO2 at the exits of their nest). So don't think of ants as tiny animals, think of ant colonies as fairly large animals.
by lmm | 2025-07-18 05:03:41+00:00
I've worked with many companies over the years. License management should be automatic or mostly-automatic if you're taking dependency management seriously (particularly these days where so many projects use well-known open-source licenses and everything is machine-readable metadata), and I've never seen a single in-house codebase (even at e.g. F500 financial institutions) that took security more seriously than your average open-source library.
by airocker | 2025-07-18 05:04:48+00:00
Conclusion The data points cited in the article are mostly accurate, based on available government reports (e.g., USCIS, ICE, NACE). However, the interpretations and causal claims are ideologically framed and often lack nuance:

Sound in identifying employment and wage challenges for new CS graduates.

Oversimplified in attributing these challenges mainly or solely to foreign workers.

Questionable in presenting policy recommendations as the only “truth-based” solution.

If you're looking for a deeper, balanced understanding, consider consulting:

National Science Board’s Science & Engineering Indicators

Brookings Institution or Cato Institute reports (for contrasting views)

NACE and NCES for graduate outcomes and education data