MurphyA/hacker-news huggingface dataset:
by littlestymaar | 2025-08-21 21:25:21+00:00
> So what exactly is the "much smaller and cleaner language struggling to get out" of Rust? If I'm understanding the post right, that language still has references, lifetimes, traits, enums, etc., because all of those features cohere; you can't remove just one and expect the rest of the language to still work. Once you grant all those features, your language isn't much smaller or cleaner than Rust; your language pretty much is Rust.

I think there's an argument to be made that you could in fact make a simpler language than Rust while keeping the core concept. This variant of the language would remove:

- the Copy trait

- reborrowing

- deref coercion

- automagic insertion of `into_iter` in loops

- automatic call to drop at the end of scope (instead you'd have to call it by yourself or get an compiler error)

- trait bounds having an automatic `:Sized` bound by default.

- lifetime elision

- no “match ergonomics”

- and likely a few other pieces of “magic” that can be hard for beginner to grasp, but that's what I had at the top of my head.

This language would be much simpler, by having fewer concepts and a lot less “magic”, but it would also be much more cumbersome to use in a day to day basis, as all of the above are clever workaround designed to make common tasks as straightforward as possible, and I don't think anyone would prefer to use it than using Rust itself. It may be useful as an instructional tool when introducing Rust to students though.
by TZubiri | 2025-08-21 21:26:07+00:00
#Takes around 1 second s="a"*3000000000

#instant, does not consume twice as much memory. s+="a"

I don't know the internals, but certainly there's not a new string being created. Maybe if it exceeds capacity? Who cares at that point, it's python strings, not Matmuls in C.
by CuriouslyC | 2025-08-21 21:26:58+00:00
If you set up your agents correctly, they can run for hours. My record is around 4 hours for a "prod/launch readiness" on a 90k LoC codebase, and that same codebase had a marathon lint and mypy plan that fixed ~700 issues over 6 hours (split around 3/3 due to API limits)
by whydoineedthis | 2025-08-21 21:27:02+00:00
Similar fear mongering when calculators came about. No one got dumber, we just got faster at doing simple math. WOrking out complex math will always be interesting to those who really want to do it, and the rest likely wont contribute mu ch anyway - thier just consumers. Let the kids have thier wordy calculators, it actually may unblock critical paths of success needed for someone to really go deep.
by simonw | 2025-08-21 21:27:03+00:00
I wonder if the author is using automated tests.

My hunch is that good automated testing is an enormous factor with respect to how productive you can get with coding agent tools.

Thorough tests? Just like working without LLMs you can confidently make changes without fear of breaking other parts of the application.

No tests at all? Any change you make is a roll of the dice with respect to how it affects the rest of your existing code.
by johnnyanmac | 2025-08-21 21:27:29+00:00
I agree on principle, and I'm sure many of us know how much of a pain it is to work on million or even billion dollar codebases, where even small changes can be weeks of beauracracy and hours of meetings.

But with the way the industry is, I'm also not remotely surprised. We have people come and go as they are poached, burned out, or simply life circumstances. The training for the new people isn't the best, and the documentation for any but the large companies are probably a mess. We also don't tend to encourage periods to focus on properly addressing tech debt, but focusing on delivering features. I don't know how such an environment over years, decades doesn't generate so much redundant, clashing, and quirky interactions. The culture doesn't allow much alternative.

And of course, I hope even the most devout AI evangelists realize that AI will only multiply this culture. Code that no one may even truly understand, but "it works". I don't know if even Silicon Valley (2014) could have made a parody more shocking than the reality this will yield.
by recallingmemory | 2025-08-21 21:27:43+00:00
Yep, 1.6 trillion gallons of water from the Colorado river goes into irrigation for alfalfa[1]. Google's total water consumption across all data centers in 2023 was 6.4 billion gallons[2].

People are sounding the alarm about water usage in AI data centers while ignoring the real unsustainable industries like animal agriculture.

1: https://coloradosun.com/2024/04/04/research-colorado-river-w...

2: https://www.datacenterdynamics.com/en/news/google-emissions-...
by HarHarVeryFunny | 2025-08-21 21:27:52+00:00
Actually that's not true. Our neocortex - the "crumpled up" outer layer of our brain, which is basically responsible for cognition/intelligence, has a highly regular architecture. If you uncrumpled it, it'd be a thin sheet of neurons about the size of a teatowel, consisting of 6 layers of different types of neurons with a specific inter-layer and intra-layer pattern of connections. It's not a general graph at all, but rather a specific processing architecture.
by Aurornis | 2025-08-21 21:28:35+00:00
I’ve driven through The Dalles. It’s a very small town. A search shows a population of 15,000 and declining annually.

It’s also right on a big river. The article you linked said that Google was spending nearly $30 million to improve the city’s water infrastructure so there are no problems.

Talking about this in terms of percentages of a small town’s water supply while ignoring the fact that the city is literally on a giant river and Google is paying for the water infrastructure is misleading.
by gonzalohm | 2025-08-21 21:29:41+00:00
One thing that shocks me as an immigrant from Europe to the US is toilets. I have not seen a single one that has the two buttons, one for pee and one for the other stuff.

Every time I use the toilet it uses 1.6 gallons. 6 liters...

I think in my home country more than 90% of home toilets are the "low water usage one" (with 3 and 6 liters buttons)

And that's only the start, I noticed that people just don't care about water usage over here. People take water from wells with little oversight. In my home country you need a vast amount of bureaucracy to be allowed to take water from aquifers
by potatolicious | 2025-08-21 21:29:54+00:00
> "When you consider that classical engineers are responsible for the correctness of their work"

Woah hang on, I think this betrays a severe misunderstanding of what engineers do.

FWIW I was trained as a classical engineer (mechanical), but pretty much just write code these days. But I did have a past life as a not-SWE.

Most classical engineering fields deal with probabilistic system components all of the time. In fact I'd go as far as to say that inability to deal with probabilistic components is disqualifying from many engineering endeavors.

Process engineers for example have to account for human error rates. On a given production line with humans in a loop, the operators will sometimes screw up. Designing systems to detect these errors (which are highly probabilistic!), mitigate them, and reduce the occurrence rates of such errors is a huge part of the job.

Likewise even for regular mechanical engineers, there are probabilistic variances in manufacturing tolerances. Your specs are always given with confidence intervals (this metal sheet is 1mm thick +- 0.05mm) because of this. All of the designs you work on specifically account for this (hence safety margins!). The ways in which these probabilities combine and interact is a serious field of study.

Software engineering is unlike traditional engineering disciplines in that for most of its lifetime it's had the luxury of purely deterministic expectations. This is not true in nearly every other type of engineering.

If anything the advent of ML has introduced this element to software, and the ability to actually work with probabilistic outcomes is what separates those who are serious about this stuff vs. demoware hot air blowers.
by bpt3 | 2025-08-21 21:31:22+00:00
> And you don't acknowledge the actual definition, or you would have been asking about price elasticity, not what is or is not essential for human life. Plenty of people will give up Chinese takeout before they give up GPUs.

You just listed two examples of discretionary items (prepared food is generally not considered a consumer staple).

> The luxury car, because it's grandma's old classic that Tom has kept in good enough shape to drive to his job, and he doesn't know how he'll get there when it finally breaks down, but he doesn't really have a penchant for fancy food and gets by with some cheap staples he prepares at home.

You're 0 for 2. That's not a luxury car, unless Grandma had a love of rare exotics that he should probably sell to buy food and a reliable car.

> The trip to the casino, because Judy is getting evicted, and doesn't have any friends or family she can stay with, and won't survive the winter on the street, and hitting it big at Blackjack is unlikely, but desperate times call for desperate measures. And although she does sometimes take Tylenol for headaches, she's otherwise in good health and doesn't have any ongoing medicinal needs.

And now you're 0 for 3. Your earlier comments are making more sense.

> What are we doing? You're deciding what other people need for their lives?

Most humans understand what is essential to sustain human life and what is not. In fact, every functioning adult I've ever met does.

The implications of the fact that you don't can be left for you or other readers to decuce.

> Of course they do, because however they behave, they have an army of op-ed writers, sycophants, and apologists who spew out post-hoc justification for their behavior, and viola, their behavior turns out to have been rational all along.

> Meanwhile, if the poor (and we are always talking about the poor when we are talking about "essential") stubbornly show an unwillingness to stop purchasing some good that some economist has decided is "non-essential", they're villainized and called irrational. Many of them even have refrigerators!

Not remotely true.

> You choose now, in 2025, to deny that there's a class war? That's certainly a take.

Whether there is or isn't a class war is debatable, but the one you've concocted that is led by economists is certainly not happening.
by IshKebab | 2025-08-21 21:31:49+00:00
* Same names: fn, let, mut, pub, println, etc.

* Same everything-is-an-expression style. Blocks evaluate to the last expression in them.

* /// Doc comments

* ML style pattern matching

* Result type

* 'todo', 'panic'

"Whhaaa but you can find those features in other languages! You literally said ML-style you big idiot!!"

Indeed but Rust massively popularised a lot of those features (how many people actually use ML?) and the number of them makes it almost impossible that it isn't at least strongly inspired by Rust.

Interestingly they have fixed the tuple syntax issue - it's #(a, b, c) - but have copied the match pattern matching mistake where you can write what looks like a variable name and it becomes a pattern. That mistake has been known since the 70s.
by scythe | 2025-08-21 21:32:00+00:00
Potter's analysis of the various consumptive uses of water relies on the USGS survey data of the uses of water, generally a good source. However, there is a small flaw when we try to turn consumptive use into consumption, which is alluded to but not quantified in the USGS report: water losses to evaporation during storage (in reservoirs) and transportation. This is discussed in e.g.:

https://journals.ametsoc.org/view/journals/bams/99/1/bams-d-...

https://www.sciencedirect.com/science/article/abs/pii/S00344... (translation: 33.73e9 m^3/yr ≈ 24400 Mgal/day, roughly corn + alfalfa + steel)

Much of the literature is preliminary and recommends further study, but the initial estimates indicate that the amount of water that is simply lost from reservoirs is surprisingly large. So I like to yak about covering reservoirs (possibly with solar panels), which won't solve everything, but it has a far larger impact than data centers.

Aside: metric, please!
by tombert | 2025-08-21 21:32:37+00:00
Yeah, I remember the 5G one and it kind of upset me.

Obviously people can have opinions on anything, and of course you can't be an expert on everything, but I feel like what Sabine does goes beyond "having an opinion"; she seems to have pivoted into fear-mongering about academia. I don't love academia either, and I have my criticisms of how it is run in the US, but I think a lot of my complaints can largely be explained by incompetence at the administrative level, not a grand conspiracy to control narratives or suppress questions or anything like that.

Granted, the research I've worked on has been pretty apolitical [1], mostly mathy computer science stuff, so maybe I was never at a risk of my research being suppressed, but I certainly don't think that Eric Weinstein is being censored by no one taking his attempt at Unified Field Theory seriously.

[1] Yes I know everything can be political. You don't need to explain this to me.
by toss1 | 2025-08-21 21:33:30+00:00
>>What makes LLMs different?

Good question!

Writing or calculators likely do reduce our ability memorize vast amounts of text or do arithmetic in our heads; but to write or do math with writing and calculation, we still must fully load those intermediate facts into our brain and fully understand what was previously written down or calculated to wield and wrangle it into a new piece of work.

In contrast, LLMs (unless used with great care as only one research input) can produce a fully written answer without ever really requiring the 'author' to fully load the details of the work into their brain. LLMs basically reduc ethe task to editing not writing. As editing is not the same as writing, so it is no surprise this study shows an serious inability to remember quotes from the "written" piece.

Perhaps it is similar to learning a new language wherein we tend to be much sooner able to read the new language at a higher complexity than write or speak it?
by binwiederhier | 2025-08-21 21:34:05+00:00
Disclaimer: I am the ntfy maintainer. Pleasantly surprised to be mentioned, hehe.

Pushover is an amazing tool and works well. In my obviously biased opinion though, I think that ntfy has a ton more features than Pushover and is fully open source. You can self host all aspects of it or you can use the hosted version on ntfy.sh for free, without signups, or pay for higher limits.

I suggest you try out ntfy;-)
by readthenotes1 | 2025-08-21 21:34:11+00:00
55M visa holders ???

I had no idea it was that many.

I thought 18M undocumented was a high %age!

342M people in the US. 16% visa holders

I wonder how that compares to other countries?

https://www.census.gov/popclock/

https://www.census.gov/topics/population/foreign-born/about....
by Aachen | 2025-08-21 21:34:53+00:00
Moving bytes around doesn't take RAM but CPU. Notice how switches don't advertise how many gigabytes of RAM they have, but can push a few gigabits of content around between all 24 ports at once without even going expensive

Also, the HN homepage is pretty tame so long as you don't run WordPress. You don't get more than a few requests per second, so multiply that with the page size (images etc.) and you probably get a few megabits as bandwidth, no problem even for a Raspberry Pi 1 if the sdcard can read fast enough or the files are mapped to RAM by the kernel
by 1vuio0pswjnm7 | 2025-08-21 21:34:58+00:00
"I regularly see millions of unique ips doing strange requests, each just one or at most a few per day."

How would UA string help

For example, a crawler making "strange" requests can send _any_ UA string, and a crawler doing "normal" requests can also send _any_ UA string.

The "doing requests" is what I refer to as "behaviour"

A website operator might think "Crawlers making strange requests send UA string X but not Y"

Let's assume the "strange" requests cause a "website load" problem^1

Then a crawler, or any www user, makes a "normal" request and sends UA string X; the operator blocks or redirects the request, unnecessarily

Then a crawler makes "strange" request and sends UA string Y; the operator allows the request and the website "blows up"

What matters for the "blowing up websites" problem^1 is behaviour, not UA string

1. The article's title calls it the "blowing up websites" problem, but the article text calls it a problem with "website load". As always the details are missing. For example, what is the "load" at issue. Is it TCP connections or HTTP requests. What number of simultaneous connections and/or requests per second is acceptable, what number is not unacceptable. Again, behaviour is the issue, not UA string

The acceptable numbers need to be published; for example, see documentation for "web APIs"
by cabacon | 2025-08-21 21:35:28+00:00
I guess my point is that the argument being made is "if you lift dumbbells with a forklift, you aren't getting strong by exercising". And that's correct. But that doesn't mean that the existence of forklifts makes us weaker.

So, I guess I'm just saying that LLMs are a tool like any other. Their existence doesn't make you worse at what they do unless you forgo thinking when you use them. You can use a calculator to efficiently solve a wrong equation - you have to think about what it is going to solve for you. You can use an LLM to make a bad argument for you - you have to think about the inputs you're going to have it output for you.

I was just feeling anti-alarmist-headline - there's no intrinsic reason we'd get dumber because LLMs exist. We could, but I think history has shown that this kind of alarmism doesn't come to fruition.
by anigbrowl | 2025-08-21 21:36:03+00:00
The 'arbitrary and capricious' part (a legal term of art) is in saying things like attending a protest constitute grounds for deportation absent any published rules or guidance to this effect. While statute law gives wide discretion to the Secretary of State and Attorney-General in immigration matters, there's still an obligation for transparency and process, which is why there's a whole infrastructure set up for contestation, appeals and so on. You cannot just start issuing orders of removal based on, say, whether people like waffles.

As a side note, Israel isn't a US state the last time I looked. I doubt that a blanket ban on political expression could survive a first amendment challenge.
by tsongas4 | 2025-08-21 21:36:30+00:00
Mathematicians went nuts trying to invalidate Gödel. Imo similar phenomena to our senses; chasing an endlessly big numbers with no real outcome but growing some number that ostensibly represents an audience but who knows if its real or just numbers on a screen.

Religious belief is same biological phenom, chasing endless propagation of the religion.

Minds go fractal. It's like Snowcrash but they’re not blank, they speak in tongues, circumlocuting gibberish.
by ender341341 | 2025-08-21 21:36:41+00:00
> I wish they had "I'm only interested in file sync" mode so that the whole mess of other features is hidden from me.

Unfortunately dropbox has been in the Enshittification phase for quite a while. They had a good while where they had extra features but no one used them cause no one wanted random feature 'x' from dropbox, they just wanted to sync files so dropbox began pushing them in your face and making you work to get what they had working perfectly 15 years ago.
by miohtama | 2025-08-21 21:37:06+00:00
Also:

"From 2001-2020, Intel blew $128 billion on buybacks (64% of net income) on top of paying out $68 billion as dividends (35% of net income),” notes Lazonick. That’s money that couldn’t go into innovation, retaining and training employees, R&D, and other critical areas.

https://www.ineteconomics.org/perspectives/blog/america-need...
by Aefiam | 2025-08-21 21:37:20+00:00
case .foo is explicitly mentioned in https://peps.python.org/pep-0622/ :

> While potentially useful, it introduces strange-looking new syntax without making the pattern syntax any more expressive. Indeed, named constants can be made to work with the existing rules by converting them to Enum types, or enclosing them in their own namespace (considered by the authors to be one honking great idea)[...] If needed, the leading-dot rule (or a similar variant) could be added back later with no backward-compatibility issues.

second: you can use case MyObject() as obj: print(obj)
by threecheese | 2025-08-21 21:37:23+00:00
I hate to admit it, but it is the prompt (call it context if ya like, includes tools). Model is important, window/tokensz are important, but direction wins. Also codebase is important, greenfield gets much better results, so much so that we may throw away 40 years of wisdom designed to help humans code amongst each other and use design patterns that will disgust us.
by eschaton | 2025-08-21 21:37:27+00:00
You should not just be open to being transparent, you need to understand that there will be times you will be required to be transparent about the tools you’ve used and the ultimate origin of your contributions, and that trying to evade or even push back against it is a huge red flag that you cannot be trusted to abide by your commitments.

If you’re unwilling to stop using slop tools, then you don’t get to contribute to some projects, and you need to be accept that.
by SquibblesRedux | 2025-08-21 21:37:33+00:00
At the risk of sounding dismissive -- this is all drama that amounts to nothing more than Internet entertainment. Legitimate claims of harm should be heard in court. Legitimate scientific debate should be hashed out at conferences or in peer-reviewed journals. Drama posted to an audience of 8 billion people, hosted in personal blogs and on YouTube videos, seems like soap opera entertainment at best and childish behavior at worst.

Just my humble opinion as a bystander looking in.
by uberduper | 2025-08-21 21:37:38+00:00
I worked at a place that made a robo-calling sales crm and they thought it would be great if during an offsite they had everyone use it to cold call places and run through some script they'd prepared. They didn't seem to understand nor care about what sort of anxiety that could cause not-sales-people. That's when I decided to start looking for another job.
by segmondy | 2025-08-21 21:37:42+00:00
garbage benchmark, inconsistent mix of "agent tools" and models. if you wanted to present a meaningful benchmark, the agent tools will stay the same and then we can really compare the models.

there are plenty of other benchmarks that disagree with these, with that said. from my experience most of these benchmarks are trash. use the model yourself, apply your own set of problems and see how well it fairs.
by djtango | 2025-08-21 21:38:11+00:00
This is a great example that I hadn't heard of and reminds me of when Nintendo tried to become an ISP when they built the Family Computer Network System in 1988

A16Z once talked about the scars of being too early causes investors/companies to get fixed that an idea will never work. Then some new younger people who never got burned will try the same idea and things will work.

Prodigy and the Faminet probably fall into that bucket along with a lot of early internet companies where they tried things early, got burned and then possibly were too late to capitalise when it was finally the right time for the idea to flourish
by bsder | 2025-08-21 21:39:29+00:00
> Courts (at least in the US) have already ruled that use of ingested data for training is transformative.

If you have code that happens to be identical to some else's code or implements someone's proprietary algorithm, you're going to lose in court even if you claim an "AI" gave it to you.

AI is training on private Github repos and coughing them up. I've had it regurgitate a very well written piece of code to do a particular computational geometry algorithm. It presented perfect, idiomatic Python with perfect tests that caught all the degenerate cases. That was obviously proprietary code--no amount of searching came up with anything even remotely close (it's why I asked the AI, after all).