MurphyA/hacker-news huggingface dataset:
by samwillis | 2025-10-28 08:02:59+00:00
This is a great comparison, but it depends so much on what sort of website or web app you are building. If you are building a content site, with the majority of visitors arriving without a hot cache bundle size is obviously massively important. But for a web app, with users regularly visiting, it's somewhat less important.

As ever on mobile it's latency, not bandwidth, that's the issue. You can very happily transfer a lot of data, but if that network is in your interactive hot path then you will always have a significant delay.

You should optimise to use the available bandwidth to solve the latency issues, after FCP. Preload as much data as possible such that navigations are instant.
by globalnode | 2025-10-28 08:03:12+00:00
All good points, and I was sort of coming at it from the point of view of catching cheaters. ofc cheaters skew the data but theyre ultimately hurting themselves. They wont pass a companies' entrance tests or will soon find themselves unemployed if they cant do the work. Yes its a problem but I see a lot of effort being spent on trying to detect them. Is that effort proportional to the problem?
by globular-toast | 2025-10-28 08:03:31+00:00
A business will always tend towards taking the maximum and giving the minimum. Believing anything else is wishful thinking at best and naive at worst.

So you have to increase the minimum. This could be achieved by contract, ie. not allowing free pulls like Docker have done, or by convincing companies that support PyPI and the like is the minimum. Unfortunately the latter would involve companies thinking and planning for the future, which is massively out of fashion.
by rolisz | 2025-10-28 08:04:05+00:00
There's some research that shows that LLMs finetuned to write malicious code (with security vulnerabilities) also becomes more malicious (including claiming that Hitler is a role model).

So it's entirely possible that training in one area (eg: Reddit discourse) might influence other areas (such as PRs)

https://arxiv.org/html/2502.17424v1
by jjav | 2025-10-28 08:04:46+00:00
> If you give AI a set of tests to pass and turn it loose with no oversight, it will happily spit out 500k LOC when 500 would do. And then it will have a very hard time when you ask it to add some functionality.

I've been playing around with getting the AI to write a program, where I pretend I don't know anything about coding, only giving it scenarios that need to work in a specific way. The program is about financial planning and tax computations.

I recently discovered AI had implemented four different tax predictions to meet different scenarios. All of them incompatible and all incorrect but able to pass the specific test scenarios because it hardcoded which one to use for which test.

This is the kind of mess I'm seeing in the code when AI is left alone to just meet requirements without any oversight on the code itself.
by Al-Khwarizmi | 2025-10-28 08:04:49+00:00
It's fun for many of us due to the combination of music, dancing, alcohol and socialization (in varying proportions: depending on tastes, interests and circumstances, one or two of those aspects can be set to zero and it's still enjoyable).

Of course, it's also perfectly fine not to like it, and then the most reasonable course of action is not to go. Or to go a couple of times until you're sure you don't like it, and not go anymore. I know cases of people who go partying just because they want to find a partner, but don't enjoy it at all (it's relatively common in my country because partying is quite a religion and there's often a lot of social pressure at certain ages), and that's rather sad. There are other ways to socialize, it's not necessary at all to torture oneself.

That said, I have to lecture you on the questioning of "talking for the sake of talking". In the context of finding a partner, talking to other people is exactly what people need... it's not "for the sake of talking", it's for the sake of socializing, meeting new people, building connections, which is the whole point when we're talking about flirting or lack thereof.
by lmm | 2025-10-28 08:06:35+00:00
> Having a language where "func" defines a pure function and "proc" defines a procedure that can performed arbitrary side effects (as in any imperative language really) would still be really useful, I think

Rust tried that in the early days, the problem is no-one can agree on exactly what side effects make a function non-pure. You pay almost all the costs of a full effect system (and even have to add an extra language keyword) but get only some of the benefits.
by Beretta_Vexee | 2025-10-28 08:06:40+00:00
I worked on port facilities. Everything corrodes quite quickly, and locks and keys need to be replaced fairly regularly. Once, there was a problem with key management following the replacement of locks on a building containing emergency diesel generators.

The doors were heavy, 45-minute fire-rated security doors, aka "Fucking heavy doors that can cut your fingers just from inertia or wind.".

These doors had to be opened quickly in the middle of the night. There was no locksmith on call, but there were boilermakers. Supports and a chain were welded to the doors, and a T-Rex container mover was used to carefully pull the doors off the building.

The whole operation took less than an hour. Physical security is a matter of time and resources.
by 0xrelogic | 2025-10-28 08:06:59+00:00
I spent weeks tracking Meta's AI infrastructure deals from September-October 2025. The scale is unprecedented: $75.5 billion across 4 deals in just 3 months.

Key findings: • CoreWeave: $14.2B (6+ years, Nvidia GB300 GPUs) • Oracle: ~$20B (multi-year cloud deal) • Blue Owl/Hyperion: $27B (joint venture, private credit financing) • Scale AI: $14.3B (49% stake)

What's interesting isn't just the size—it's the structure. Meta is using private credit and joint ventures instead of traditional CapEx. The Hyperion deal: Meta owns 20%, Blue Owl owns 80%, but Meta is on the hook for 16 years.

The math is uncomfortable: $75B in infrastructure spending vs ~$7B in AI revenue. That's a 10:1 cost-to-revenue ratio.

Happy to discuss the economics, the private credit angle, or whether this is sustainable.
by ViscountPenguin | 2025-10-28 08:07:24+00:00
I love SAT solvers, but way more underappreciated by software engineers are MILP solvers.

MILPs (Mixed Integer Linear Programs) are basically sets of linear constraints, along with a linear optimization functions, where your variables can either be reals or ints.

Notably, you can easily encode any SAT problem as a MILP, but it's much easier to encode optimization problems, or problems with "county" constraints as MILPs.
by pjmlp | 2025-10-28 08:08:03+00:00
Try to do TDD with graphics programming.

I never bought into TDD because it is only usefull for business logic, plain algorithms and data structures, it is no accident that is what 99% of conference talks and books focus on.

There isn't a single TDD talk about shader programming for GPGPU, and validating that what the shader algorithms produce via automated tests, the reason being the amount of enginneering effort only to make it work, and still lacks human sensitivity for what gets rendered.
by elnerd | 2025-10-28 08:08:17+00:00
Just because you cannot see how a vulnerability can be exploited does not mean that others can. As you describe, people seem to assume that the only way the config file ends up on the server is «physically» editing it.

An anecdote: I have been struggling with exploiting a product that relies on MongoDb, I can replace the configuration file, but gaining RCE is not supported «functionality» in the embedded version as the __exec option came in a newer version.

A parser bug would be most welcome here.
by calgoo | 2025-10-28 08:08:42+00:00
Yesterday I had to pass a bunch of data to finance as the person that does so had left the company. But they wanted me to basically group by a few columns, so instead of spending an hour on this in excel, I created 3 rows of fake data, gave it to the llm, it created a Python script which I ran against the dataset. After manual verification of the results, it could be submitted to finance.
by heeton | 2025-10-28 08:09:09+00:00
Your comment wasn’t wrong. Neither is the reply wrong to be frustrated about how the world understands this complex topic.

You’re talking about autism. The reply is about autism spectrum DISORDER.

Different things, exacerbated by the imprecise and evolving language we use to describe current understanding.

An individual can absolutely exhibit autistic traits, whilst also not meeting the diagnostic criteria for the disorder.

And autistic traits are absolutely a variant of normalcy. When you combine many together, and it affects you in a strongly negative way, now you meet ASD criteria.

Here’s a good description: https://www.autism.org.uk/advice-and-guidance/what-is-autism...
by FarmerPotato | 2025-10-28 08:10:36+00:00
At VCFMW last month, my table was adjacent to Lorraine and her friends.

Ben Heck walked by during setup, and asked me what it was. I was clueless, so we started making educated guesses. The Amiga poster was a start.

I do wire-wrap. This thing is a marvel to behold. It is quite orderly, but could have used colors more effectively.

The three units implement the VLSI chips and the main board of the Amiga that was first shown at CES (I believe.)

Each VLSI is a stack of PCB such as you might get from Vector, with columns of pads for ICs in wire-wrap sockets, buss bars, and edge areas having mounting holes for connectors. The layers are connected by ribbon cables.

(they are not called breadboard!)

Wire wrap is a superior technology. There are no cold solder joints. They are gas-tight.

It is not hard to debug. If you follow some rules, and don't make a spaghetti bird's nest.

Such workmanship can be seen on minicomputers of the early 1970s.

Whole computers were made by wire-wrap around MSI chips. My wire-wrapped PDP-11/10 functioned perfectly thru the 1990s.

Recently, I implemented a microcomputer design in wire-wrap. That was enjoyable!

My design was captured in KiCad, laid out as a PCB, which I translated to perf-board and wire-wrap sockets

This approach is perfect for prototyping, as you can simply add new blocks.
by sebastix | 2025-10-28 08:10:39+00:00
Thx for sharing, didn't know that one.

After reading https://radicle.xyz/guides/protocol my first impression it's the same as how it works with Nostr with one key difference in the conceptual model. Nostr uses relays to distribute the data and Radicle is using a gossip model to distribute the data peer-to-peer (the bittorrent model).

They do explain the difference with a federated model. I miss the explainer compared to a relay model.

So regarding the peer-to-peer modal, here are some thoughts: How IPFS is broken: https://fiatjaf.com/d5031e5b.html Why IPFS cannot work, again: https://fiatjaf.com/b8e2f959.html
by atoav | 2025-10-28 08:11:19+00:00
As a former VFX freelancer I think many people underestimate how effective cheap tricks like using image textures like that can be.

You don't need real noise, it is enough to have a single texture that is a bit bigger than the input image and then randomly offset and rotate it. If that random offset is random enough (so not pseudorandom with a low periodicity), nobody will ever notice.

Memory has gotten cheaper while latency deadlines are still deciding over how much you can do realtime. That means cheap tricks like this are not an embarrassing workaround, but sometimes the smart choice.
by wobfan | 2025-10-28 08:11:35+00:00
In my experience, >95% of the people you see online (comments, selfies, posts) seem way worse - more evil, arrogant, or enraging - than even the worst <1% of people I’ve met in real life. And that definitely doesn’t help those of us who are already socially anxious.

Obviously, “are way worse” means I interpret them that way. I regularly notice how I project the worst possible intentions onto random Reddit comments, even when they might be neutral or just uninformed. Sometimes it feels like my brain is wired to get angry at people. It’s a bit like how many people feel when driving: everyone else is evil, incompetent, or out to ruin your day. When in reality, they’re probably in the same situation as you - maybe they had a bad morning, overslept, or are rushing to work because their boss is upset (and maybe he had a bad morning too). They might even have a legitimate reason for driving recklessly, like dealing with an emergency. You never know.

For me, it all comes back to two things:

(1) Leave obnoxious, ad-driven platforms that ~need~ want (I mean, Mark Zuckerberg has to pay for cat food somehow) to make you mad, because that’s the easiest way to keep you engaged.

(2) Try to always see the human behind the usernames, photos, comments, and walking bodies on the street. They’re a person just like you, with their own problems, stresses, and unmet desires. They’re probably trying their best - just like you.
by Al-Khwarizmi | 2025-10-28 08:12:01+00:00
We would need the big picture, though... maybe it caused that death (which is awful) but it's also saving lives? If there are that many people confiding in it, I wouldn't be surprised if it actually prevents some suicides with encouraging comments, and that's not going to make the news.

Before declaring that it shouldn't be near anyone with psychological issues, someone in the relevant field should study whether the positive impact on suicides is greater than negative or vice versa (not a social scientist so I have no idea what the methodology would look like, but if should be doable... or if it currently isn't, we should find the way).
by freestingo | 2025-10-28 08:12:46+00:00
Keep in mind the purpose of all this “research” and “improvement” is just so OpenAI can have their cake (advertise their product as psychological supporter) and eat it too (avoid implementing any safeguards that would be required in any product for psychological support, but harmful for data collection). They just want to tell you that so many people write bad things it is inevitable :( what can we do :( proper handling would hurt our business model too much :(((
by koakuma-chan | 2025-10-28 08:13:11+00:00
I know right? And tech is such a male-dominated industry, so presence of a female in your proximity is a rare event by itself. But, even if such an event occurs, as you said, interacting with a female is one hell of a minefield. Honestly, at this point, I cannot blame people for choosing to be gay. It is just so much easier to just talk to men, because you don't have to worry about all those mind games.
by noone_youknow | 2025-10-28 08:13:13+00:00
It is hard, and things are messy in some areas. But in my experience it’s less hard than writing a lot of the existing documentation would’ve been (because good datasheets and documentation are more available now) and actually less messy (with some exceptions) than things were back in the days of the legacy hardware most existing wikis etc focus on.

Finding people with the knowledge, time and willingness to proof-read is also hard - but surely not insurmountable if we collectively decide it’s an endeavour we want to pursue.
by mnahkies | 2025-10-28 08:13:35+00:00
Tbf the new trusted publishers goes a long way to improving this (not used by this package by the look of it). I migrated a few of my packages to it, and now:

- publishing with an API token is forbidden, must use the specified workflow w/ OIDC auth

- an explicit approval step in GitHub is required to run the publish workflow (you can also set a time delay, similar to time release safes)

- provenance is generated and published

Ref: https://docs.npmjs.com/trusted-publishers/
by slinkydeveloper | 2025-10-28 08:13:47+00:00
Not sure why these not issues with state machines...

With RSM you often need to keep the history as well, just in a different form, that is the message/event log that your state machine processed.

With RSM you need your code to be deterministic to rebuild the materialized state during failover, unless you snapshot and replicate the state on each processed event/message.
by simoncion | 2025-10-28 08:13:58+00:00
> Are you saying I am being unnecessarily cautious?

Yeah, definitely. Given enough time, you absolutely will find games that don't work under Linux, but I expect that such games will be few and far between. Though, games with extremely invasive anticheat (such as Valorant) will almost certainly never, ever work on Linux. Games that use less-invasive anticheat like Easy Anti-Cheat (EAC) (such as Elden Ring or Hunt: Showdown) work. [0]

I have just shy of 500 games in my Steam library. Maybe three or five of them have Linux builds. I've run into only a handful of games that don't work correctly on Linux. [1]

As others have said, you can check ProtonDB to get an idea of whether a game will work for you. But:

1) ProtonDB is not always accurate. For instance, sometimes it says that a bunch of workarounds are needed, but everything works just fine with Proton in Steam. Other times, it says a game works, but it doesn't. On my computer, HighFleet is an example of a game that's said to work, but doesn't.

2) In my experience, games just work. For the very rare ones that don't, I go look around to see if there are easy workarounds, and -so far- there always have been.

[0] Though, specifically for EAC, if you have more than something like 28 CPUs, you need to limit the number of CPUs that Proton will tell EAC about, or it will fail with an unhelpful error. You'd do that by setting WINE_CPU_TOPOLOGY like this: <https://www.protondb.com/app/1245620#4SzWJRl8sv>, altering the string in the obvious way if claiming you only have 28 CPUs doesn't work and you need to claim you have fewer.

[1] I've also run into one (Ruiner) that has a Linux build that's far, far worse than the Windows build. It turns out that you can force a game that has both Windows and Linux builds to run the Windows version by going to the Compatibility tab in the game's properties and force the use of one of the Proton versions. My go-to is 'Proton Experimental', as that seems to be the Steam default.
by FloorEgg | 2025-10-28 08:14:07+00:00
I agree completely, though I continually wonder why. Is it by specific design? By economic incentive? Is it because novel threats attract attention, and having a need to be validated continually satisfied maintains attention?

I can't help but wonder if the polarization in the media is deliberate (e.g. foreign state sewing division) or accidental (second order consequence of attention economy) or organic (the claims of the paper, and/or other psychological effects of anonymity, etc.) or maybe all of the above?
by kuboble | 2025-10-28 08:14:22+00:00
As a person who grew up in Poland.

In the 80s and 90s USA was idolized and admired. Yes, even in the 80s when officially Poland was still in a soviet influence sphere with soviet and communist propaganda being everywhere.

The word "Ameryka" was a colloquial used to describe something amazing, rich, high tech. The myth of American freedom, that in America hard work can lead to personal eneichment were told like fairy tales.

When Poland joined NATO it was like dream come true. There was this huge enthusiasm of becoming officially friends and allies of USA.

We looked up so much to the USA.

It's really sad to see that completely disappear.
by inavida | 2025-10-28 08:15:00+00:00
Hi I'm nobody and the stories on here constantly remind me of this old parable. There once was a man who was afraid of his own shadow and who hated his own footprints. Somehow he got it into his head that if he could just run fast enough he could outrun them, so he ran and he ran, but no matter how fast he ran his shadow stayed by his side, and the faster he ran the more footprints he made. Somehow the man got it into his head that he just wasn't running fast enough, so he ran and he ran and he didn't stop or rest and he died. Not knowing that standing still is how to stop making footprints, and that resting under a tree is how to stop making shadows, is just so tragic.
by globular-toast | 2025-10-28 08:15:03+00:00
DEI is actually a bit of red herring here. It's worth reading again the commentary from simonw's blog:

> If we accepted and spent the money despite this term, there was a very real risk that the money could be clawed back later. That represents an existential risk for the foundation since we would have already spent the money!

This is the real problem. It's not about DEI really. It's the same problem as so much else this year: the US government is currently wildly unpredictable and doing business with such an entity is a liability.
by vanderZwan | 2025-10-28 08:15:20+00:00
That's one method they use, but "just cluster" is doing a lot of heavy lifting in that sentence. It's why Erik Bernhardsson came up with the Approximate Nearest Neighbors Oh Yeah algorithm (or ANNOY for short)

> We use it at Spotify for music recommendations. After running matrix factorization algorithms, every user/item can be represented as a vector in f-dimensional space. This library helps us search for similar users/items. We have many millions of tracks in a high-dimensional space, so memory usage is a prime concern.

[0] https://erikbern.com/2013/04/12/annoy.html

[1] https://github.com/spotify/annoy?tab=readme-ov-file
by rob_c | 2025-10-28 08:15:28+00:00
How tf else did you honestly expect black-boxes to get built, by self-mangling machine code spit out by a sentient AI god?

Karpathy is bullish on everything bleeding edge, and unfortunately it kinda shows when you know the material better than he does. (source, I've been lecturing on all of it for a few years now). I'm not saying this is bad. It's great to see people who are engaging and bullish, it's better than most futurists waving their hands and going "something, something warp drive".

But when you take a step back and really ask what is going on behind the scenes, all we have is massive statistical tools performing neato tricks at statistical probability to predict patterns. There's no greater understanding or ability to learn or mimic. YET. The transformer for-instance can't easily learn complex mathematical operations. There's a google paper on "learning" multiplication and I know people working on building networks to "learn" sin/cos from scratch. But given these basic limitations and pretty much, every, single, paper, out of Apple "intelligence" crapping on the buzz. We've pretty much hit a limit beyond being the first company to allow for multi-trillion token parsing (or basic, limited, token parsing memory) for companies to capture and retrieve information.
by rob_c | 2025-10-28 08:17:00+00:00
> The code itself no longer matters.

Good luck explaining that when you get hacked out of oblivion.

This is like saying the fine-print of contracts don't matter so I get "AI" to regurgitate them all for me as a lawyer. It's so wrong as to be beyond laughable.

Put the coffee down and go for a walk, preferably to a library, and LEARN SOMETHING.
by hansmayer | 2025-10-28 08:17:14+00:00
Yeah, it's like that commercial for OpenAI (or was it Gemini?) where the guy says it lets the tool work on it's complex financial spreadsheets, goes for a walk with a dog, gets back and it is done with "like 98% accuracy". I cannot imagine what the 2% margin of error looks like for a company that moves around hundreds of billions of dollars...
by bear141 | 2025-10-28 08:17:42+00:00
When I was in Amsterdam I was with a group of acquaintances of a friend who lived there. One of them offered me an extra piece of pizza they had when I showed up. When the bill came, they asked me for the exact percentage of the bill that that piece of pizza cost. First time experiencing something like that.

I also offered to buy several people a drink while I was there. This was received every time with suspicion and I was treated as if I was trying to gain something transactional besides a simple friendship in the moment. It was an interesting part of that society to experience.