MurphyA/hacker-news huggingface dataset:
by lordnacho | 2025-09-08 08:23:11+00:00
But why is it that countries that are culturally close to Britain (eg colonies) have much higher fatality rates? You'd expect them to have implemented some of the same policies. Singapore and Malta have similar rates, but the others are much higher.

Regarding roundabouts, it makes sense when explained like in the article. But I've always felt like they were dangerous, especially the ones they have in Britain where you have multiple lanes with lights and connecting roundabouts. Perhaps that sense of fear is what actually makes them safe.
by rgblambda | 2025-09-08 08:23:31+00:00
>kinda like how we love to tell everyone how chuffed we are with how safe our AC plugs are.

I would actually love to see some data that compares total deaths and injuries per capita from electrocution from plugs across different countries. I have a feeling the total worldwide figures are tiny in comparison to injuries from stepping barefoot/putting your knee on UK plugs.

Also, UK plugs tend to have the wire coming out the bottom and then curving upwards as the electrical device is usually above the socket, over time resulting in an exposed wire, while most other plugs have the wire coming out the centre.
by imiric | 2025-09-08 08:24:21+00:00
I really think Intel is on the right track to dethrone both AMD and NVIDIA, while also competing with ARM SoCs. It's fascinating to watch.

Both their integrated and dedicated GPUs have been steadily improving each generation. The Arc line is both cheaper and comparable in performance to more premium NVIDIA cards. The 140T/140V iGPUs do the same to AMD APUs. Their upcoming Panther Lake and Nova Lake architectures seem promising, and will likely push this further. Meanwhile, they're also more power efficient and cooler, to the point where Apple's lead with their ARM SoCs is not far off. Sure, the software ecosystem is not up to par with the competition yet, but that's a much easier problem to solve, and they've been working on that front as well.

I'm holding off on buying a new laptop for a while just to see how this plays out. But I really like how Intel is shaking things up, and not allowing the established players to rest on their laurels.
by JetSetWilly | 2025-09-08 08:24:47+00:00
I think a national speed limit is a sensible system. In many countries, every random stretch of road has a different speed limit, as though driving speeds have been centrally planned - usually poorly.

Expecting the driver to be an educated and safe driver who is capable of judging the appropriate speed for the road is far superior. This also inculcates a better attitude in the driver - the speed limit is not a target.
by torginus | 2025-09-08 08:25:41+00:00
I think the conditions of the demoscene arising were a software interface that consisted of coding, and people's first experience with a computer was

10 PRINT "HELLO WORLD!"

20 GOTO 10

RUN

This piqued the interest of curious youth, who then were further enabled by a hardware interface where you could write a value into an area of memory, which would then appear as a pixel on screen.
by cherryteastain | 2025-09-08 08:26:05+00:00
> _impossible_ for your program to transition into an invalid state at runtime

Not the case for scientific computing/HPC. Often HPC codebases will use numerical schemes which are mathematically proven to 'blow up' (produce infs/nans) under certain conditions even with a perfect implementation - see for instance the CFL condition [1].

The solution to that is typically changing to a numerical scheme more suited for your problem or tweaking the current scheme's parameters (temporal step size, mesh, formula coefficients...). It is not trivial to find what the correct settings will be before starting. Encountering situations like a job which runs fine for 2 days and then suddenly blows up is not particularly rare.

[1] https://en.m.wikipedia.org/wiki/Courant%E2%80%93Friedrichs%E...
by iainmerrick | 2025-09-08 08:26:12+00:00
Yes, I really have a hard time understanding that trend.

More than just the overall sizes of the cars (and they are big) it's those very high, flat fronts. That surely must be bad for visibility and bad for fuel efficiency at speed. I can only imagine people like that style because it looks more like a car and less like a minivan, which is what those enormous SUVs really are.
by globular-toast | 2025-09-08 08:26:33+00:00
I don't think we really need an article a day fawning over LLMs. This is what they do. Yep.

Only thing I got from this is nostalgia from the old PC with its internals sprawled out everywhere. I still use desktop PCs as much as I can. My main rig is almost ten years old and it's been upgraded countless times although is now essentially "maxed out". Thank god for PC gamers, otherwise I'm not sure we'd still have PCs at all.
by hdgvhicv | 2025-09-08 08:26:42+00:00
If you are causing a delay you are responsible for pulling over.

Most slow vehicles do - bikes, horses, tractors. Just the idiot townies who filled their sat nav rather than the diversion signs.

You get people doing 15mph down a road like this

https://maps.app.goo.gl/76GxECaTe9ESePGY9?g_st=ic

They should be banned.
by piker | 2025-09-08 08:26:46+00:00
As an American who drove for 20 years before obtaining a license in the UK, I can offer some observations.

First, driving in the UK is much more a privilege than a right as in the US. You can live a complete life in the UK without a license because of the wide availability of public transit. In the US however, if you want to maintain a steady job outside of NYC, Chicago, DC, Boston or perhaps a few others, you'll have to drive. Revoking a driver's license in the US can be life-altering in a way that it just won't in the UK. Fewer people bother getting the license and fewer still drive.

Second, driving is much more physically and mentally demanding in the UK. Perhaps that serves to reduce traffic deaths by forcing focus, but it also imposes a limit on the types of people who can drive here. This selects against too young, too old, too small, disabled, etc. in a way that would not be tolerated in the US for the above reasons.

Third, annual vehicle inspections are much more stringent in the UK which takes a lot of older vehicles off the road and again selects against those of lower socio-economic status in a way that would be unconscionable in the US.
by graemep | 2025-09-08 08:26:48+00:00
> By the time I had left sixth form (18), two other people from my high school had died in RTAs and two others had life changing injuries.

I think your experience is extremely unlucky. I went to a school in London (in the 80s) with around a 1,000 kids from 8 to 18 and there was one road death, and two injuries, all in the same accident, in all the time i was there. I did not know the buy who died personally, although i knew one of the others who was in the car.

I agree with you about the improvements in general. I do think the 20mph limits where I now live (and in some other places) seem a bit random, and there are some difficult A road junctions that I think the really could do with lower limits or other improvements that do not have them.

Absolutely true that kids are objectively much safer, but people have grown fearful. I wonder whether being safer has made people less tolerant of risk more than risks have diminished. Its common to hear arguments that anything that might save even one life is worth doing.
Show HN: TheAuditor – Offline security scanner for AI-generated code
by ThailandJohn | 2025-09-08 08:28:15+00:00
I'm an infrastructure architect who started using AI assistants to write code 3 months ago. After building several systems with Claude, I noticed a pattern: the code always had security issues I could spot from my ops background, but I couldn't fix them myself since I can't actually write code.

Why I built this: I needed a way to verify AI-generated code was production-safe. Existing tools either required cloud uploads (privacy concern) or produced output too large for AI context windows. TheAuditor solves both problems - it runs completely offline and chunks findings into 65KB segments that fit in Claude/GPT-4 context limits.

What I discovered: Testing on real projects, TheAuditor consistently finds 50-200+ vulnerabilities in AI-generated code. The patterns are remarkably consistent: - SQL queries using f-strings instead of parameterization - Hardcoded secrets (JWT_SECRET = "secret" appears in nearly every project) - Missing authentication on critical endpoints - Rate limiting using in-memory storage that resets on restart

Technical approach: TheAuditor runs 14 analysis phases in parallel, including taint analysis (tracking data from user input to dangerous sinks), pattern matching against 100+ security rules, and orchestrating industry tools (ESLint, Ruff, MyPy, Bandit). Everything outputs to structured JSON optimized for LLM consumption.

Interesting obstacle: When scanning files with vulnerabilities, antivirus software often quarantines our reports because they contain "malicious" SQL injection patterns - even though we're just documenting them. Had to implement pattern defanging to reduce false positives.

Current usage: Run aud full in any Python/JS/TS project. It generates a complete security audit in .pf/readthis/. The AI can then read these reports and fix its own vulnerabilities. I've seen projects go from 185 critical issues to zero in 3-4 iterations.

The tool is particularly useful if you're using AI assistants for production code but worry about security. It provides the "ground truth" that AI needs to self-correct.

Would appreciate feedback on: - Additional vulnerability patterns common in AI-generated code - Better ways to handle the antivirus false-positive issue - Integration ideas for different AI coding workflows

Thanks for taking a look! /TheAuditorTool
by arcticbull | 2025-09-08 08:29:22+00:00
Yes, it could be done with a Hall effect sensor or something like they used to. The cool thing about this approach is they actually use a different angle to turn the screen off as you close the lid than they do for turning it on when you open the lid, to create a better experience. Since it is a security feature, then the "open" vs "closed" state should use the same source of truth. So it's a trade-off of complexity and experience.
by zh3 | 2025-09-08 08:29:26+00:00
You can also get GT730's with 4xHDMI - not fast, but great for office work and display/status boards type scenarios. Single slot passive design too, so you can stack several in a single PC. Currently just £63 UK each.

[0] https://www.amazon.co.uk/ASUS-GT730-4H-SL-2GD5-GeForce-multi...
by vidarh | 2025-09-08 08:30:04+00:00
I've given an example prompt you can use as a basis in another comment, but let me double down, because it really matters that you seem to think this is a complex problem:

> That'll end the conversation right here and now.

We both know that isn't true, because it is so trivial that if you had any intention of being convinced, you'd have accepted the point already.

Do you genuinely want me to believe that you think an LLM can't act as a simple lookup from 6 keys (3 states, 2 symbols) to 6 tuples?

Because that is all it takes to show that an LLM + a loop can act like a Turing machine given the chance.

If you understand Turing machines, this is obvious. If you don't, even executing the steps personally per the example I gave in another comment is not likely to convince you.

> Do I think you can modify an LLM to be a Turing Machine, yeah. Of course.

There's no need to modify one. This can be done by enclosing an LLM in simple scaffolding, or you can play it out in a chat as long as you can set temperature to 0 (it will work without that as well to an extent, but you can't guarantee that it will keep working)

> But at this point it doesn't seem like we're actually dealing with an LLM anymore.

Are humans no longer human because we can act like a Turing machine?

The point is that anything that is Turing complete is computationally equivalent to anything else that is Turing complete, so demonstrating Turing-completeness is, absent any evidence that it is possible to compute functions outside the Turing computable, sufficient for it to be reasonable to assert equivalence in computational power.

The argument is not that any specific given LLM is capable of reasoning like a human, but to argue that there is no fundamental limit preventing LLMs from reasoning like a human.

> are you suggesting humans are deterministic?

I'm outright claiming we don't know of any mechanism by which we can calculate functions exceeding the Turing computable, nor have we ever seen evidence of it, nor do we know what that would even look like.

If you have any evidence that we can, or any evidence it is even possible - something that'd get you a Nobel Prize if you could show it - then by all means, enlighten us.
by philjohn | 2025-09-08 08:31:04+00:00
Our driving test standards are also high, having spoken with US colleagues, much higher than state-side (although I imagine that varies from state to state).

The theory test you must pass before taking your practical also now includes a hazard perception test - you are shown multiple videos and must click when you first perceive a hazard - the earlier you click after the hazard presents the higher your score - but if you just click randomly you get a zero.

Some of them are tricky - for instance, one I remember is a van coming from a side road at too fast a speed, but you can only first see this hazard forming in a reflection of a shop window.
by moshib | 2025-09-08 08:31:57+00:00
At my $CORP job, I often see engineers enamored with creating new things. I completely understand the appeal -- it's fun to create something new, without preexisting constraints, with full ownership of the codebase.

However, the real challenge is what happens _later_, when the thing is done. Most people don't really think about maintenance, and move on to other things, making the thing they worked on stale and stagnant.

I think this applies here too: Vibe coding lets us create new _things_ quite easily, but we see value in places other than the sheer the existence of the project. We care about how the project is maintained, if it has a userbase, contributors, longevity. I think this is also part of why it feels so "cheap" and not genuine.
by simonask | 2025-09-08 08:33:08+00:00
Hot take: Almost all programs are actually multithreaded. The only exception is tiny UNIX-like shell utilities that are meant to run in parallel with other processes, and toy programs.

The third exception is programs that should be multithreaded but aren't because they are written in languages where adding more threads is disproportionately hard (C, C++) or impossible (Python, Ruby, etc.).
by mdp2021 | 2025-09-08 08:33:16+00:00
I am terribly sorry to hear that, geocrasher.

Of course the simile I found to try and show that "look, this branch does not seem appropriate for the context" was random. I thought of a few, in time constraints, and the one that looked the best of the bunch happened to be the one of "starvation". It could have anything - surely you understand.

> You have no idea what you're talking about or who you're talking to

But I was talking of the matter in context, and the simile, as said, was logic, not comparative.
by mpweiher | 2025-09-08 08:33:38+00:00
Always a great read!

However, things have actually changed since then. A lot.

Here is Brooks at a "20 year retrospective" panel[1] at OOPSLA '07:

"When ‘96 came and I was writing the new edition of The Mythical Man-Month and did a chapter on that, there was not yet a 10 fold improvement in productivity in software engineering. I would question whether there has been any single technique that has done so since. If so, I would guess it is object oriented programming, as a matter of fact."

Large-scale reuse, which was still a pipe-dream in 1986, and only beginning in 1996 is now a reality. One which has brought its own set of problems, among them the potential for a lot of accidental complexity.

We now use 50 million lines of code to run a garage door opener[2]. I can declare with some level of confidence that the non-essential complexity in that example is more than the 90% that Brooks postulated as a safe upper limit. Five million lines of code is not the essential complexity of a garage door opener.

And while that is an extreme example, it seems closer to the normal case these days than the comparatively lean systems Brooks was thinking about.

[1] https://www.infoq.com/articles/No-Silver-Bullet-Summary/

[2] https://berthub.eu/articles/posts/a-2024-plea-for-lean-softw...
by ghost_co | 2025-09-08 08:33:48+00:00
Does anyone heard a success stories from cloud usage?

Really, we(they) in the company decided to move in cloud everything from on-prem, it should save costs say them.

But, as result you anyway need DevOps, some complications with development, local environments and not only.

For not short career I faced some good examples, but it's more about unique situations, not a rule and a lot companies continue pay a lot for some small bunch of utility.

Maybe I'm wrong, but such topics about this hell heard a lot of timesand only on some conference: success stories (because they should say: success)
by abc123abc123 | 2025-09-08 08:34:11+00:00
Incorrect. The whole sentence is:

"may be aborted if a file contains content that appears to be binary, Unicode text, or text with CR/LF line endings unless the interactive user chooses to proceed. If there is no interactive user or these warnings should be skipped for some other reason, the --no-warnings option may be used."

I use fossil and checking in binaries works beautifully. You _do_ get a warning, but as seen in the documentation, you can use --no-warnings if you don't want that.

Note however, that you can't use diff on binaries, and since the entire history of the repository and the versions is shipped to all developers, storing large binaries quickly becomes cumbersome. I would in that case, store links to binaries, which themselves are stored in an archive, or switch to another scm program.
by torginus | 2025-09-08 08:34:46+00:00
Yeah, I remember reading an interview with one of the few big demosceners, and they said that to compete in the highest leagues, you need editing tools to build these impressive scenes.

After all the most talented musicians and visual designers often were not the same people, and every artistic pursuit involves a lot of iteration.

To be fair groups tended to build the tools themselves, not to take away from their achievements, but once the tools are done and public (like the ones you shared), a lot of the challenge and point of competition is gone.

Tooling also tends to create a moat between 'users' and 'developers', the former of which lack the low-level knowledge to transition into the latter.
by jiggawatts | 2025-09-08 08:35:01+00:00
Up until now, LLM training has used mostly pre-existing data, hoarding what has already been produced and feeding that in as-is. Think textbooks, Wikipedia, GitHub, etc...

That's starting to run dry, hence the predictions of progress stalling, but it doesn't factor in the option of using vast volumes of synthetic data. Some of the "thinking" models are already using generated problem sets, but this is just the tip of the iceberg.

There are so, so many ways in which synthetic data could be generated! Some random examples are:

- Introduce a typo into a working program or configuration file. Train the AI to recognise the typo based on the code and the error message.

- Bulk-generate homework or exam problems with the names, phrasing, quantities, etc... randomised.

- Train the AI not just on GitHub repos, but the full Git history of every branch, including errors generated by the compiler for commits that fail to build.

- Compile C/C++ code to various machine-code formats, assembly, LLVM IR, etc... and train the AI to reverse-engineer from the binary output to the source.

... and on and on.
by adastra22 | 2025-09-08 08:35:38+00:00
I’m not going to go into fine details because it is obvious personal and this is a public forum. But basically the issues came down to being inattentive, lack of follow through, communication failures, dropping responsibilities, etc. that are all downstream of my primarily inattentive ADHD diagnosis.

Basically failures in everyday life and the relationship due to my own actions (or more typically, lack of action aka bad priorities) where if you had pointed it out to me at the time I totally would have told you I should be Doing The Thing and I absolutely want to Do The Thing but… hey look at that other shiny thing!

She got tired of the disappointment and broken promises, and I sought help. After being told by someone I confided in that I might have ADHD, I spoke to a psychiatrist and was prescribed stimulants. Now I have a magic pill I take every morning that makes me 100% able to choose to Do The Thing when I want to Do The Thing. It gave me that choice, which I never had.

It makes me a better person because it allows me, for the first time ever in my 40 years on this planet, to make that conscious choice about what kind of person I show myself as in my actions. Previously, I was just along for the ride. Now I’m in the pilot’s seat.

I have tried most of the other things you mention. There are great health benefits to eating right, for example, and even mental/mood improvements as well. But no effect whatsoever on this issue. ADHD intention is a brain chemistry problem and requires a chemical solution, plain and simple.
by closewith | 2025-09-08 08:36:11+00:00
No, that’s not true. Walking and cycling did decline, but risk per kilometre for has also fallen sharply (by approximately 50%) over the same period. Vulnerable road users are safer now than they ever were, despite similar actual numbers using the road network due to population growth and profile.

The main factors behind the fall in deaths:

* drink-driving enforcement, * seatbelt enforcement, * speed limits and speed cameras, * NCT improving the vehicle fleet, * road engineering changes, * driver training.

So the “sharks in the pool” analogy is absurd. Everyone is safer, including the most vulnerable road users, so a better analogy is the road network has changed from shark-infested seas to a managed watercourse with swimmers, surfers, and boaters are seeing vastly fewer deaths or injuries.
by singron | 2025-09-08 08:37:08+00:00
I believe it's the second case. Otherwise far over 100% of firms "adopted" AI by now, which doesn't make sense unless they keep un-adopting and re-adopting.

The question from BTOS is

> Between MMM DD – MMM DD, did this business use Artificial Intelligence (AI) in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.)
by exDM69 | 2025-09-08 08:37:20+00:00
Note that KTX2 is a container format. It can contain uncompressed or compressed texture data. Some of the tools you mention might support "KTX2" but they won't compress textures for you, they just put the uncompressed data in a KTX2 container.

And my out-of-the-box Gimp 3.0.4. doesn't have KTX export at all. Didn't check the other tools you mention.
by HelloNurse | 2025-09-08 08:37:34+00:00
Can you elaborate on the situations and reasons that would make this approach appropriate?

At first sight it seems a complicated and inferior approximation of techniques from the article: not automatically single use, not statically checked, somewhat error prone for proper secret usage, not really preventing well-intentioned idiots from accidentally extracting, "laundering" and leaking the secret, removing secrets from logs at a dangerously late stage with some chance of leaks.
by prameshbajra | 2025-09-08 08:37:43+00:00
I have been testing both Claude code and Codex CLI for the past few weeks and I found codex output to be better than claude.

I like how Claude code is more advanced in terms of CLI functionality but I prefer Codex output (with model high)

If you do not want to pay for both, then you can pick anyone and go with it. I don't think the difference is huge.