MurphyA/hacker-news huggingface dataset:
by teekert | 2025-08-24 07:16:26+00:00
I have this too, I have never been able to "do exercises" or "study a codebase". I need to be making something that I am excited about, then I'll learn, from examples, from wanting to be thorough and correct.

But sometimes I think I'm just not their yet, if I become able to read code like a book and really understand what happens, which often I don't, then perhaps I'll enjoy the process more.
by gf000 | 2025-08-24 07:19:17+00:00
There is not much point talking about throughput and latency in the abstract - they are very often opposing goals, you can make one better at the expense of the other.

Go's GC is tuned more for latency at the expense of throughput (not sure if it still applies, but Go was quite literally stopping the "business" mutator threads when utilisation got higher to be able to keep up with the load - Java's default GC is tuned for a more balanced approach, but it can deliver it at very high congestion rates as well. Plus it has a low-latency focused GC which has much better latency guarantees, and it trades off some throughput in a consistent manner, so you can choose what fits best). The reason it might sometimes be more efficient than Java is simply value types - it doesn't create as much garbage, so doesn't need as good a GC in certain settings.

Rust code can indeed be better at both metrics for a particular application, but it is not automatically true, e.g. if the requirements have funny lifetimes and you put a bunch of ARC's, then you might actually end up worse than a modern tracing GC could do. Also, future changes to the lifetimes may be more expensive (even though the compiler will guide you, you still have to make a lot of recursive changes all across the codebase, even if it might be a local change only in, say, Java), so for often changing requirements like most business software, it may not be the best choice (even though I absolutely love Rust).
by weinzierl | 2025-08-24 07:19:27+00:00
I had many devices and gadgets over the decades, certainly a three digit figure.

There are only a few I really loved and consider well-rounded and beautiful while useful.

My Commodore 64 comes to mind, my 2010 aluminum unibody Mac Book Pro has a place in this list and certainly my Palm III.

The first time I saw one was with one of my superiors at a Siemens R&D facility where I interned at the time. I knew I had to have one. A little later I bought mine from a dude who brought it from a work trip to the US. I still have it, I keep it together with my copy of the O'Reilly Palm Programming book.

I used the Palm a lot in everyday life and had it always with me, so for a brief period of my life it was an invaluable tool. Its real value for me however was how it foreshadowed what was about to come. I think the looming smartphone revolution was really obvious for us Palm users. We might not have foreseen every detail (Steve Jobs ditching the stylus) but the broad strokes of what was about to happen were crystal clear.
by pydry | 2025-08-24 07:19:48+00:00
I dont think this is a good idea, actually. Good design is about making good trade offs at the right point in time.

A code base with excellent design will show you the end state but not how it got there but probably not the trade offs and decisions involved.

Practicing refactoring on subpar code bases and dealing with the consequences of your decisions is a better way to improve.
by Jensson | 2025-08-24 07:20:24+00:00
> You don’t test each new human to see if they have it

We do, its called school and we label some humans with different learning disabilities. Some of those learning disabilities are grave enough that they can't learn to do tasks we expect humans to be able to learn, such humans can be argued to not posses the general intelligence we expect from humans.

Interacting with an LLM today is like interacting with an Alzheimer patient, they can do things they already learned well but poke at it and it all falls apart and they start repeating themselves, they can't learn.
by astrobe_ | 2025-08-24 07:20:42+00:00
> These days, computers can easily recognize photos of cats, but that’s not because a clever programmer discovered a way to isolate the essence of “catness.”

It could have been. It did happen in some cases as computer vision didn't wait for neural networks (e.g. OCR). But to hijack a famous quote, "Neural networks are like violence - if it doesn't solve your problems, you are not using enough of it."

> A neuron with two inputs has three parameters. Two of them, called weights, determine how much each input affects the output. The third parameter, called the bias, determines the neuron’s overall preference for putting out 0 or 1.

So a neuron does very basic polynomial interpolation and by hooking them together you get polynomial regression. I don't know if it amusing or amazing that people use polynomial regression to write programs now.
by pss314 | 2025-08-24 07:22:27+00:00
LinkedIn recently announced that it transitioned from Kafka to Northguard. Introducing Northguard and Xinfra: scalable log storage at LinkedIn [1] & LinkedIn: Stream Processing 4.16.25 [2]

[1]: https://www.linkedin.com/blog/engineering/infrastructure/int...

[2]: https://www.youtube.com/watch?v=RDV6-MUVEbQ
by rich_sasha | 2025-08-24 07:23:09+00:00
I have always found it a bizarre idea that we allegedly judge a country's importance by it's size on a Mercator projection map. Does anyone really think Greenland is the most important place in the world? Europe is tiny, yet the kind of people to complain about it will also complain about the outsized importance of it. Africa, which is apparently a victim of such projectionism, is also placed in the middle because of where the arbitrary Greenwich meridian goes.
by cornholio | 2025-08-24 07:23:42+00:00
Both can be true at the same time, the American market can subsidize research for the rest of the world, and one source of this subsidy could be US public programs leaving substantial cash on the table for big pharma.

Another perspective is that this extra spending is more closely correlated with global pharmaceutical profits and the spending by these companies for their US sales and lobby apparatus (which influences Medicare prescribing physicians just as well), and much less with actual fundamental research and clinical study spending required to bring these drugs to market. So it's relatively speaking "wastage" compared to direct medical research spending - perhaps through a global research institution funded by major economies. Hey, we can dream.

As to why would Medicare leave these untold billions on the table, I don't know the details of how they decide what to treat, but it's a very tricky political problem. Once you start to deal with things like DALYs, QALYs and micromorts, you are plowing straight into the "death panels" controversy. So all pharma has to do is refuse to play ball, continue to sell most of their products into the open market, and watch their Madicare centralized buyers quickly fold. You can only force Pharma to play if you institute a national monopsony; a single program, even a big one, can't possibly work since by acquiescing they would threaten profits in the rest of the market. For the same reason, a single US state could not go at it alone, pharma would just refuse to sell to that state at the imposed ceilings; it needs to be a nation wide program.
by aurareturn | 2025-08-24 07:24:08+00:00
Uber lost $31b. They make about $4b/year in profit now. It'll take them 7 years to make it all back assuming they don't grow anymore.

$31b put into Nasdaq would have netted investors $300b before dividends. So honestly it was a bad deal.

And let's not forget that Uber can be killed by self driving cars.
by aurareturn | 2025-08-24 07:24:30+00:00
Uber lost $31b. They make about $4b/year in profit now. It'll take them 7 years to make it all back assuming they don't grow anymore.

$31b put into S&P 500 would have netted investors are more in return over the last 15 years. So honestly it was a bad deal.

And let's not forget that Uber can be killed by self driving cars.
by gf000 | 2025-08-24 07:24:36+00:00
> The problem is that writing genuinely performant Java code requires that you drop most if not all of the niceties of writing Java

Such as? The only area where you have to "drop" features is high-frequency trading, where they often want to reach a steady-state for the trading interval with absolutely no allocations. But for HFT you would have to do serious tradeoffs for every language.

In my experience, vanilla java is more than fine for almost every application - you might just benchmark your code and maybe add some int arrays over an Integer list, but Java's GC is an absolute beast, you don't have to baby it at all.
by hnlmorg | 2025-08-24 07:25:36+00:00
You’re talking about software piracy, which the UK and US, and most of the developed world too, also has strict laws for.

However new games are constantly released for old consoles and often sold as ROMs. Which is completely legal because they own the copyright and distribution rights to those games.

Also modern variants of old consoles will typically use emulation with ROMs approved for distribution, such as:

- The SNES Classic Mini

- The Wii Virtual Console

- The Switch Online, SNES

All of these are official Nintendo products. All of them available in Japan. And all of them use emulation under the hood with ROMs that Nintendo supply and have legal authority to distribute.

You can also take this point further and talk about uses of emulation outside of gaming too. Such as emulated hardware components in a virtual machine.
by Mikhail_Edoshin | 2025-08-24 07:26:01+00:00
When you try to solve a problem the goal or the reason to reject the current solution are often vague and hard to put in words. Irrational. For example, for many years the fifth postulate of Euclid was a source of mathematical discontent because of a vague feeling that it was way too complex compared to the other four. Such irrationality is a necessary step in human thought.
by simonw | 2025-08-24 07:27:22+00:00
I use a 64GB M2 MacBook Pro. I tend to find any model that's smaller than 32B works well (I can just about run a 70B but it's not worth it as I have to quit all other apps first).

My current favorite to run on my machine is OpenAI's gpt-oss-20b because it only uses 11GB of RAM and it's designed to run at that quantization size.

I also really like playing with the Qwen 3 family at various sizes and I'm fond of Mistral Small 3.2 as a vision LLM that works well.
by raffraffraff | 2025-08-24 07:27:32+00:00
I created a static site generator for my wife's business using go + js + git. She has no tech skills whatsoever, but had very specific ideas about how the website should work.

Once the basic functionality was worked out in js (with a simple JSON schema and Lourm Ipsum text), I created a Samba share on the network, mapped it to her computer.

Her first post was an edit of the Lorum Ipsum markdown and some new images, and from then on she had a pattern to follow: add a directory with a markdown file and assets.

The NAS runs a Go program that generates a JSON file for the static site js, starts a http server for testing. She can access the http server over the network to preview the static site. If it's ok, she can trigger a git commit and push (with a click). She didn't have to learn anything (like Hugo or jinja), because markdown is kinda obvious. She has exactly the website she wants.

Of course, I had more work to do initially, coming up with the static site, the JSON schema and the go generator, but it was over a week of evenings. She's been happily adding to it regularly without my interaction.

And this, my friends, is why I (a mere DevOps / Cloud guy) "vibe code" with Claude.
by dns_snek | 2025-08-24 07:27:52+00:00
> The fact that at one point it gave you the correct answer is indicative that an aspect of it understands the concept.

Having a conceptual understanding means that you always provide the same answer to a conceptually equivalent question. Producing the wrong answer when a question is rephrased is indicative of rote memorization.

The fact that it provided the right answer at one point is only indicative of memorization, not understanding which is precisely the difference between sometimes getting it right and always getting it right.
by lukan | 2025-08-24 07:28:16+00:00
Then it still matters a lot what kind of codebase he is working on. A web project is differently structured and done than the codebase for a embedded operating system. There are differend standards and practices in the industry.

I learned a lot by just stepping through the code with the debugger of libaries I used. That brought more practical insight while learning about design patterns etc. In the end, it is all about patterns. Finding the right pattern for a given problem.
by soraminazuki | 2025-08-24 07:29:00+00:00
The trailing dot is part of the link, but HN doesn't recognize it as such. Here's the relevant quote:

> End users have reported that Brother has initiated various methods to limit or reduce functionality on many printers prior and during usage. This includes:

> - 3rd party consumable lockout on various printer models.

> - Reduction in print capacity via software, firmware and hardware.

> - Disabling of functionality via print counters, software and firmware.

> - Nagware screens or pop-ups indicating firmware or software should be updated.

> - Limited or obfuscated information regarding effects of software or firmware update implementation.
by mofeien | 2025-08-24 07:30:30+00:00
There is the concept of n-t-AGI, which is capable of performing tasks that would take n humans t time. So a single AI system that is capable of rediscovering much of science from basic principles could be classified as something like 10'000'000humans-2500years-AGI, which could already be reasonably considered artificial superintelligence.
by gf000 | 2025-08-24 07:30:42+00:00
Which is very important in... embedded settings.

While for typical backend situations, reference counting has a crazy high throughput overhead, doing atomic inc/decs left and right, that instantly trashes any kind of cache, and does it in the mutator thread that would do the actual work, for the negligible benefit of using less memory. Meanwhile a tracing GC can do (almost) all its work in another thread, not slowing down the actually important business task, and with generational GCs cleaning up is basically a no-op (of just saying that this region can now be reused).

It's a tradeoff as everything in IT.

Also, iPhone CPUs are always a generation ahead, than any android CPU, if not more. So it's not really Apples to oranges.
by johannesboyne | 2025-08-24 07:30:54+00:00
A very similar "how to guide" can be found here https://ampcode.com/how-to-build-an-agent written by Thorsten Ball. In general Amp is quite interesting - obviously no hidden gem anymore ;-) but great to see more tooling around agentic coding being published. Also, because similar agentic-approaches will be part of (certain/many?) software suits in the future.
by gavmor | 2025-08-24 07:31:12+00:00
A lot of the jokes about JavaScript being messy come from historical quirks—like loose equality, type coercion oddities, or the way `this` behaves—but the ECMAScript specification has been steadily improved over the years by ECMA TC39 (the committee responsible for developing the standard).

Likewise PHP has been somewhat inconsistent historically and carries its own legacy quirks—but it's JS that gets mocked, because why?

Meanwhile Java—although designed with a cohesive strict, statically typed, object-oriented sensibility—has seen fit to add lambda expressions, stream APIs, record types, and pattern matching, following some of the same trends as ECMA TC39.

So, when it comes to developer ergonomics—which, I daresay, is the subject of this satire and the preeminent aspect of a language most hotly debated—does JS really deserve the hate? There must be some other current of thought—some dark matter—warping the discourse.
by esperent | 2025-08-24 07:31:42+00:00
I didn't ignore it, I actually spent some time researching to find out what Google means by "Gemini Apps" (plural) and whether it includes search AI overview, and I can't get a clear answer anywhere.

Of course, Gemini App (singular) means the mobile app. But it seems that the term Gemini Apps (plural) is being used by Google to refer to any way in which users can access the Gemini models, and also they do clearly state that a version of Gemini isused to generate the search overviews.

So it still seems reasonably likely, until they confirm otherwise, that this median includes search overview.
by NobodyNada | 2025-08-24 07:32:49+00:00
There have definitely been some applications of this sort of thing to speedrunning -- though far less sophisticated than the approach here, and usually only testing against a very small subset of the game. I've heard of some of this kind of work being done before on e.g. SM64.

I've also done something along these lines myself in Super Metroid. Mother Brain's neck moves in a conceptually simple but very chaotic pattern influenced by Samus's vertical movement, and there's a cutscene during the fight where the positioning of her neck can make a difference of about 7 seconds. The TAS fight used complicated movement to manipulate her neck position developed through much trial-and-error, while the best known human-viable manips were several seconds slower.

I wrote a program to search the state space for optimal movement patterns, and working with some speedrunners we were able to come up with a new human-viable manipulation that matched the previous TAS fight, as well as a new TAS manipulation that saved an additional 41 frames.

https://youtu.be/7SHD9L_Jx5Q

https://github.com/NobodyNada/mbsim
by perihelions | 2025-08-24 07:33:10+00:00
Bluesky has never opposed or criticized OSA. Am I over-indexing on that?

Their July 10 blogpost even frames OSA as a collaboration—it's written plain in the title, "Working with [sic] the UK Government to Protect Children Online",

https://bsky.social/about/blog/07-10-2025-age-assurance
by hdgvhicv | 2025-08-24 07:33:24+00:00
You thought wrong, the names are just a branding thing.

The overground came under TfL management in 2007, before then it was silverlink. The routes had unofficial names (north London line, Watford dc, goblin etc), they’ve had swanky new names now and the old names weren’t used officially very much, but were on the most part obvious (goblin being the Gospel Oak to Barking LINe, the rest being more obvious)
by globular-toast | 2025-08-24 07:33:33+00:00
That's kinda like saying you can learn to drive by just getting into a car, crashing then thinking about how not to crash it next time.

In reality both things are necessary. The car analogy doesn't hold for road driving because we drive well within the limits, but for racing it really is necessary to know exactly where the limits are. I don't think we should really be treating our profession like a race, though.

But if you don't read it's going to be an incredibly long slow process and a lot of car crashes and mangled gearboxes etc. So I say read, read, and read some more. Even if you don't see the point of it right now your experience will later find a place for it and you won't end up descending a hill for the first time not knowing to shift to a lower gear.
by edgineer | 2025-08-24 07:34:01+00:00
I noticed today that a 9175F was in the $2000s down from a $4000s MSRP. I still can't justify buying one when a 9950x3d is more performant and <1/3rd price, even though the epyc has more PCIe lanes.

It's my first time contemplating getting a server CPU, so I assumed the insane markups were the same story as with Lenovo laptops, or Advance Auto parts or McDonald's meals--that nobody pays those prices, unless you're a sucker.
by abstractspoon | 2025-08-24 07:34:02+00:00
Originally from the UK I've lived in Australia for the last thirty years in a fibro cottage without A/C where the summer temperature reaches 35C/95F inside the house and to manage I just strip down and handle it.

I do have one mechanical fan for my yoga practice.

Oh, and the winter temp reaches 7C/45F and I don't use heating either.
by hliyan | 2025-08-24 07:34:12+00:00
This doesn't seem like the giant step I thought it was:

> Unlike the costly bleeding edge 2 and 3 nanometer chips made by giants like TSMC, TI’s chips are made on cheaper, legacy nodes: 45 to 130 nanometers.

What's worse:

> Making chips takes an immense amount of water, and about a quarter of Texas is in drought. Luckily, Sherman has water rights to nearby Lake Texoma.

Indeed lucky for TI, but probably not so for area residents.
by throwaway290 | 2025-08-24 07:34:22+00:00
If you think I am legitimizing flat earthers you really don't get the point. I am just saying that for 90% of people belief in this or that mostly dictated by people around them.

> unknowable metaphysical topics

religious people often conveniently shift goalposts to make sure what they say is always beyond knowable. We launched satellites and found no heaven above? fine, it exists in some other way. No soul detected? our technology is not good enough. Flat earthers do almost the same thing just they use conspiracy theories instead.

If you want to find a difference between religion and flat earther theory, Christianity for example (not sure this applies to all religions) is supposedly helping humans live together better, like: be kind, do to others what you want be done to you, don't steal/kill/rape etc. But that's not really related to how it's proven or factual.
by maxglute | 2025-08-24 07:36:21+00:00
I think it means Xi's advisors don't believe in AGI, and Xi's advisors are drawn from the largest pool of AI talent in the world. And given the incentive, i.e if they're wrong and PRC lightcone collapse because US built AGI, they would if anything advise AGI is more imminent to hedge. But they're not. The general discourse around PRC AI doesn't focus on AGI. IMO simply one one thinks AGI is around corner, not enough to drive short term strategic planning.
by RossBencina | 2025-08-24 07:36:25+00:00
I think there is value in groking entire code bases. It's not just about whether or not they are well designed though. It is an important skill to be able to analyze and see the big picture of how things work together in large systems. For me it often involves drawing diagrams (sometimes UML) to map things out. Being able to view systems in this way is a pre-requisite to intentionally designing your own systems at this level. And yes, once you can work at this level you can learn from good designs, but also see problems with bad ones.

EDIT: and to answer your question, if you're working on something that is "like X but different" then read the source code for X. You could also look at source code for software that you use from day to day: software where you already know what it does. For example, if you're in web, maybe the web framework, or web server, if you write python, maybe a core library that you use, or maybe the python interpreter, or if you use vscode ..., if you use android ..., you get the idea. At the start I would suggest smaller programs, and programs where you already know the domain (e.g. cpython might not be the best place to start if you never implemented an interpreter before, you may spend more time learning about interpreters than the design of this one, still a good thing to learn of course.)
by thenoblesunfish | 2025-08-24 07:37:30+00:00
Agreed - territorial area is only one measure of importance, and probably not a great one. What would be more useful on a wall, if we are interested in such things, are bubbles with size showing population, GDP, life expectancy, etc. (a la https://www.gapminder.org/tools/#$chart-type=bubbles&url=v2 ), arranged to preserve, as much as possible, country positions on the projection of your choosing.