MurphyA/hacker-news huggingface dataset:
by xpe | 2025-10-09 06:43:51+00:00
I'm going to take this slowly and non-controversially in the hopes of building a foundation for a useful conversation. There are no gotchas or trick questions here.

1. Deploying any LLM where a person can use them (whether an employee or customer) has risks. Agree?

2. The report talks about risks. Agree?

3. There are various ways to compare risk levels. Agree?

4. One can compare the risk relative to: (a) not deploying an LLM at all; (b) deploying another kind of LLM; (c) some other ways. Agree?

If you can't honestly answer "yes" to these questions, this suggests to me there is no point in continuing the conversation.
by beeflet | 2025-10-09 06:44:04+00:00
>Think about it - the claim is that those systems can prove aspects of someone's identity (eg age), without the site where the proof is used obtaining any knowledge about the individual and without the proof provider knowing where the proof is used.

That is not nessisarially true. There are ZK setups where you can tell when a witness is reused, such as in linkable ring signatures.

Another simple example is blind signatures, you know each unblinded signature corresponds to a unique blind signature without knowing who blinded it.
by zhassan699 | 2025-10-09 06:45:06+00:00
Remote: Yes

Willing to relocate: no

Resume: https://github.com/ziad-hsn/Resume/blob/main/Ziad-Hassan.pdf

http://linkedin.com/in/ziad-hassan-334688216

Technologies: AWS, GCP, Kubernetes, Prometheus, Elastic Stack, Python3, Go

Email: ziad.hassan.dev@gmail.com
by teiferer | 2025-10-09 06:45:10+00:00
Buying more land, building more housing to ultimately charge rent would definitely be good for everybody. The housing crisis is a supply side shortage and every dollar going into building new rentals would alleviate that pressure. Instead, the money goes to building more AI datacenters so that the family of 5 with mom and dad working at Walmart can have higher definition cat videos. They'd be better served with more supply in the rental market, ultimately lowering rent.
by MrJohz | 2025-10-09 06:46:14+00:00
> [...] we'd arrive at stability and consensus.

Honestly, that's basically happened, but just a generation later.

Most modern frameworks are doing very similar things under the hood. Svelte, SolidJS, and modern Vue (i.e. with Vapor mode) all basically do the same thing: they turn your template into an HTML string with holes in it, and then update those holes with dynamic data using signals to track when that data changes. Preact and Vue without Vapor mode also use signals to track reactivity, but use VDOM to rerender an entire component whenever a signal changes. And Angular is a bit different, but still generally moving over to using signals as the core reactivity mechanism.

The largest differences between these frameworks at this point is how they do templating (i.e. JSX vs HTML vs SFCs, and syntax differences), and the size of their ecosystems. Beyond that, they are all increasingly similar, and converging on very similar ideas.

The black sheep of the family here is React, which is doing basically the same thing it always did, although I notice even there that there are increasing numbers of libraries and tools that are basically "use signals with React".

I'd argue the signal-based concept fits really well with the DOM and browsers in general. Signals ensure that the internal application data stays consistent, but you can have DOM elements (or components) with their own state, like text boxes or accordions. And because with many of these frameworks, templates directly return DOM nodes rather than VDOM objects, you're generally working directly with browser APIs when necessary.
by sxp | 2025-10-09 06:46:42+00:00
Another place where LLMs have a problem is when you ask them to do something that can't be done via duct taping a bunch of Stack Overflow posts together. E.g, I've been vibe coding in Typescript on Deno recently. For various reasons, I didn't want to use the standard Express + Node stack which is what most LLMs seem to prefer for web apps. So I ran into issues with Replit and Gemini failing to handle the subtle differences between node and deno when it comes to serving HTTP requests.

LLMs also have trouble figuring out that a task is impossible. I wanted boilerplate code that rendered a mesh in Three.js using GL_TRIANGLE_STRIP because I was writing a custom shader and needed to experiment with the math. But Three.js does support GL_TRIANGLE_STRIP rendering for architectural reasons. Grok, ChatGPT, and Gemini all hallucinated a GL_TRIANGLE_STRIP rendering API rather than telling be about this and I had to Google the problem myself.

It feels like current Coding LLMs are good at replacing junior engineers when it comes to shallow but broad tasks like creating UIs, modifying examples available on the web, etc. But they fail at senior-level tasks like realizing that the requirements being asked of them aren't valid and doing something that no one has done in their corpus of training data.
by growse | 2025-10-09 06:46:52+00:00
> Why do people doing normal trading want to avoid the exchanges that have HFT computers skimming money off their trades?

What's "normal trading"? A prop desk at an investment bank? A hedge fund? A pension fund? Someone who's just installed Robin Hood on their phone?

Most rational participants want lower trading costs and overheads, smaller spreads etc. HFT provides that - the evidence being "look at what the spreads are today, compared with what they were pre computerised trading".

And you don't have to take my word for it, Vanguard thinks this too. https://www.cnbc.com/2014/04/25/vanguard-chief-defends-high-...

> The price is going to get discovered either way just as it has for hundreds of years, it happening a billion times per second does normal traders no good.

Could you explain how a market participant who makes one trade a day is negatively impacted by high resolution price discovery?
by usrusr | 2025-10-09 06:46:56+00:00
Taking an "optimist's advocate" position here (I share your scepticism):

65% are almost easy to achieve, with a bit of clever accounting: you'd look at fuel per ton-mile (that much is clear and perfectly fine) and then you just pick a tow plane that's maybe a bit overpowered but doesn't have much cargo capacity. If you look at fuel saving through that lense, the sky is the limit.

The contingency page in the pitch deck for when the "bigger plane is always more efficient" argument comes up would be looking at big end of the hypothetical size spectrum: when you want efficiency, a bigger plane means bigger wingspan. Air travel is in something not too dissimilar to the "panamax" situation on the oceans, everything on the ground stops at 747-sized (the A380 was carefully squeezed to mostly fit that profile). A formation can get a similar effect as a larger wingspan without exceeding runway dimensions.

(and as for landing in tow: perhaps some stupid legal angle, "it's all fully automated, but technically this is not autonomous because the lead aircraft pilot is in charge"?)
by jandrewrogers | 2025-10-09 06:47:28+00:00
Real-world geometry is a mess and an endless headache. You can write brute-force tooling to grind through it and auto-repair issues it can classify across the myriad formats but it isn’t computationally cheap and you’ll still find “wtf” cases that you have to investigate manually. I’ve worked with official government GIS data sets where 1-5% of all geometry was defective in some way. You have to check it, the percentage of data sets with no defects is much smaller than you’d hope.

8,000 rows is small but the typical processing isn’t fast. Optimizing it has limited ROI. I use a custom Python library I wrote for this kind of work, which makes it a bit slow, but you constantly run across new types of inexplicable geometry issues so the ability to rapidly write custom routines is paramount, which Python excels at.

GIS data is computationally expensive to process even beyond its obvious properties.
by jeroenhd | 2025-10-09 06:47:36+00:00
The AI moderation tools are trained on the Reddit data that is actively being sabotaged by a competitor. If an AI were to take up moderation now, mentioning this specific bootcamp would probably get you warned or banned because of how bad it is according to the training data.

AI is as biased as humans are, perhaps even more so because it lacks actual reasoning capabilities.
by stevev | 2025-10-09 06:48:07+00:00
No doubt the industry suffered due to a market downturn, but your continuous posts and attacks worsened the situation for that company. Based on your Reddit activity, it appears to have been driven by a personal vendetta. If they pursue a defamation case, the evidence could strongly work against you. The overwhelming proof he presented of your actions toward the company would be difficult to defend. I honestly can’t understand why anyone would risk their own reputation—and that of their family—for dishonest gain. Most people are civil in such cases, but not everyone is if they conclude that evil was done. Scary situation to be in.
by ziotom78 | 2025-10-09 06:48:48+00:00
I fully resonate with point #2. A few days ago, I was stuck trying to implement some feature in a C++ library, so I used ChatGPT for brainstorming.

ChatGPT proposed a few ideas, all apparently reasonable, and then it advocated for one that was presented unambiguously as the "best". After a few iterations, I realized that its solution would have required a class hierarchy where the base class contained a templated virtual function, which is not allowed in C++. I pointed this out to ChatGPT and asked it to rethink the solution; it then immediately advocated for the other approach it had initially suggested.
by kaoD | 2025-10-09 06:49:05+00:00
Reactivity has a specific meaning in programming:

https://en.wikipedia.org/wiki/Reactive_programming

https://en.wikipedia.org/wiki/Functional_reactive_programmin...

Which I think React doesn't really fit. React is not about data streams, nor about inferred dependencies.

> Technically you could just getElementById and update it, but react has what I call a whole "reactivity engine" to do it for you.

I would call that "declarative", not "reactive".

https://en.wikipedia.org/wiki/Declarative_programming

The closest thing to reactivity React has are dependency arrays in `useCallback` but I'd say it's a stretch to call that reactive programming.

Compare it with SolidJS's data flow. https://docs.solidjs.com/ Also notice how "reactive" is all over their landing page while React doesn't mention "reactive" at all https://react.dev/
by Al-Khwarizmi | 2025-10-09 06:50:30+00:00
With bag of words, the representation of a word is a vector whose dimension is the dictionary size, all components are zeros except for the component corresponding to that word, which is one.

This is not good to train neural networks (because they like to be fed dense, continuous data, not sparse and discrete) and it treats each word as an atomic entity without dealing with relationships between them (you don't have a way to know that the wprds "plane" and "airplane" are more related than "plane" and "dog").

With word embeddings, you get a space of continuous vectors with a predefined (lower) number of dimensions. This is more useful to serve as input or training data to neural networks, and it is a representation of the meaning space ("plane" and "airplane" will have very similar vectors, while the one for "dog" will be different) which opens up a lot of possibilities to make models and systems more robust.
by seec | 2025-10-09 06:51:23+00:00
This happens because of bad incentives. Since the welfare state is on the spot to pick up the tabs via unemployment benefits they would rather have industries keep paying for as a long as possible even if it means killing the goose that laid the golden eggs in the long run.

But all of this is largely amplified by globalisation. The welfare is not compatible with a world where companies can decide to set up shop somewhere else in the world to benefit from cheaper labour cost and lower regulations and still being able to sell their stuff in the market they somewhat destroyed.

It ends up strengthening the state because workers defer to it and ask it to foot the bill. This all ends up being a vicious cycle where over time the state because massively obese and nothing moves because almost everything is dependent on it to some extent.

Now to be fair it is absurd that companies are allowed to make so much profit and keep most of it, not redistributing to the workers who are actually contributing the most. But it all starts with bad regulations and incentives. Companies cannot be expected to compete with foreign imports that benefit from much lower costs in every dimension, that is just unfair competition.

Free markets are an illusion that only benefits those at the top and this is largely where the problem lies. If imports were to be taxed appropriately, there would be less reasons to delocalize and the job market would be much more competitive for the demand side, rendering the layoff problem mostly moot. Who cares about benefits/compensation if the next job is right there?
by selcuka | 2025-10-09 06:51:44+00:00
0.01% of 65M is 6,500. Also apparently only 70K people uploaded their IDs.

That being said, you can still hash faces and metadata (such as ID numbers) instead of storing the whole ID as a scanned photo, if the information is only used for duplicate checking. Hashing does not increase the racial bias. If your model has a bias it will always have a margin of error.
by LargoLasskhyfv | 2025-10-09 06:52:08+00:00
Dude. This is getting OT. Since I've never cared about M.

Anyway, I can assure that using AntiX was simpler/more hasslefree than using plain Debian. Because they give a shit about not including needed drivers for hardware relying on "big bad binary blobs" (Oh Noez!1!!) on their installation media, instead just focusing on getting things done, or rather UP on crappy hardware in innovative ways. That aside you're free to remaster that thing, once it's running, to your hearts content, removing anything you wouldn't want, or adding anything which is missing, styling, theming, choosing window-manager or desktop-environment, potentially making YOUR personalized installation media even smaller, and thus using even LESS RAM, thereby running more stuff even faster.

All by simply pressing a few function-keys during initial boot/install, and easy clicking in their graphical tools, afterwards.

If you'd apply your reasoning thoroughly to all the stuff you're using, you should probably disconnect from the net right now, never come back again, and try to live in a cabin in the woods, sustaining yourself. Have fun with that.
by teiferer | 2025-10-09 06:52:20+00:00
> Ending all school programs that separate children by ability is the most radically egalitarian position possible, even in theory. There is no more extreme position one can take.

There are many things I can imagine that are much more radical than this. Everybody has to live the same, wear the same, eat the same, think the same. That's pretty insanely dystopian for sure, but much more egalitarian than barely mixing kids of different ability in the same classroom.
by johnisgood | 2025-10-09 06:52:44+00:00
You're right that `unsafe` and `SPARK_Mode(Off)` are structurally analogous escape hatches - both let implementers use operations outside the verified/safe subset. I accept that the VCs-for-callers difference exists whether or not `SPARK_Mode(Off)` is used - it's a SPARK-vs-Rust language difference, not a construct difference.

I was conflating the constructs with their language contexts. The constructs are analogous; the languages are not.

That said: the original thread is comparing Ada/SPARK vs Rust for high-assurance systems, and in that context, the language-level difference is what matters. When you use `SPARK_Mode(Off)`, you still get integrated caller verification. When you use `unsafe`, you don't - you need external tooling. That ecosystem difference drives language choice for formal verification work, even though the constructs themselves are analogous.
by mindslight | 2025-10-09 06:52:54+00:00
Sure, but making use of that introduces new problems.

Fundamentally it limits a person to one account/nym per site. This itself removes privacy. An individual should be able to have multiple Discord nyms, right?

Then if someone gets their one-account-per-site taken/used by someone else, now administrative processes are required to undo/override that.

Then furthermore it still doesn't prevent someone from selling access to all the sites they don't care about. A higher bar than an activist simply giving it away for free, but still.
by ____mr____ | 2025-10-09 06:52:58+00:00
1) Despite the quite liberal lobbying laws the US seems to have, corruption is still rampant and illegal donations continue. Cracking down on lobbying would probably remove some of the money in lobbying but not all of it.

Points 2-5 are all "impactful for the average american" but most people will disagree with how and how far these should be implemented. Why did you signal out asset forfeiture as your example of police overstep but not no knock warrants, stop and search laws or the current ICE street gang situation? The problem with the view that all members of a nation share common struggle and therefore have the same political wants and needs is naive and these seemingly shared frustrations are often oversimplifications that disguise various political interests
by raxxorraxor | 2025-10-09 06:53:02+00:00
> I don't particularly blame any one corporation, this is a systemic issue of governments not having/not enforcing serious security measures

Wrong, governments caused the issue because they demand customers to ID themselves. There exists not a single viable security measure aside from not collecting the data. Government is also not able to propose any security measures.

Unlikely that the data will ever be deleted now, no matter if Discord pays any ransoms or not.
by timschmidt | 2025-10-09 06:53:34+00:00
It's tough to find figures, but the amount of aluminum lost during smelting not accounted for in dross is as much as half a percent. World smelting capacity is 113 million tons per year. Which maths to as much as 565,000 tons of vaporized aluminum per year.

You're right that it's released into the lower atmosphere, though I'm sure smoke stacks loft that significantly in many cases. And it's difficult for me to believe that a few hundred kg per day, even if all of it ended up in the upper atmosphere, is anything more than a blip in comparison to what lofts up from industry.

The difference would have to be many thousands of times worse for upper atmosphere releases for it to even register.
by 8fingerlouie | 2025-10-09 06:54:06+00:00
yes, but before you "panic", look into if it's really a problem. Kopia is a fine tool, and while it's a bit lacking in native integration, it works well, and for some things even better than Arq.

Arq wins on system integration. It supports waking the machine from sleep at backup time, keeping it awake while backing up, materializing cloud only files, and many other "nice to have" things.

Kopia however wins on efficency and speed. The same ~3TB backup (incremental) done with Kopia and Arq here finishes in 3-5 minutes with Kopia, and 45 minutes with Arq, and Kopia supports deduplication across multiple clients, meaning if you backup your family photo library from multiple locations, Kopia will only store it once.

In any case, even Apple doesn't recommend backing up Apple Photos libraries, and instead recommend exporting the photos, which is what i do with Parachute.

https://www.arqbackup.com/documentation/arq7/English.lproj/s...
by pimeys | 2025-10-09 06:54:14+00:00
Yep. One of the things I've found agents always having a lot of trouble with is anything related to OpenTelemetry. There's a thing you call that uses some global somewhere, there's a docker container or two and there's the timing issues. It takes multiple tries to get anything right. Of course this is hard for a human too if you haven't used otel before...
by VBprogrammer | 2025-10-09 06:54:18+00:00
"Have you heard the phrase "You're not Google, you're not Facebook, and you're not Netflix"? The TL;DR; is those tech giants that have 1M+ concurrent users. They have a hard requirement for no downtime."

Actually, one of the more interesting parts of the Google SRE book was that they don't try to aim for 0 downtime. They consider the background error rate of any network request and optimising much beyond this is counter productive.

Even for individual services they make a point of not trying to make them perfectly available, as this means downstream services are less likely to build in adequate provision for failure.
by freetonik | 2025-10-09 06:54:49+00:00
I see a pattern in these discussions all the time: some people say how very, very good LLMs are, and others say how LLMs fail miserably; almost always the first group presents examples of simple CRUD apps, frontend "represent data using some JS-framework" kind of tasks, while the second group presents examples of non-trivial refactoring, stuff like parsers (in this thread), algorithms that can't be found in leetcode, etc.

Tech twitter keeps showing "one-shotting full-stack apps" or "games", and it's always something extremely banal. It's impressive that a computer can do it on its own, don't get me wrong, but it was trivial to programmers, and now it is commoditized.
by sidgtm | 2025-10-09 06:55:53+00:00
As a UX designer I see they lack the ability of being opinionated about a design piece and go with the standard mental model. I got fed up with this and made a simple java script code to run a simple canvas on the localhost to pass on more subjective feedback using highlights and notes feature. I tried using playwright first but a. its token heavy b. it's still for finding what's working or breaking instead of thinking deeply about the design.
by rossant | 2025-10-09 06:56:32+00:00
Recently, I asked Codex CLI to refactor some HTML files. It didn't literally copy and pasted snippets here and there as I would have done myself, it rewrote them from memory, removing comments in the process. There was a section with 40 successive <a href...> links with complex URLs.

A few days later, just before deployment to production, I wanted to double check all 40 links. First one worked. Second one worked. Third one worked. Fourth one worked. So far so good. Then I tried the last four. Perfect.

Just to be sure, I proceeded with the fifth one. 404. Huh. Weird. The domain was correct though and the URL seemed reasonable.

I tried the other 31 links. ALL of them 404ed. I was totally confused. The domain was always correct. It seemed highly suspicious that all websites would have had moved internal URLs at the same time. I didn't even remember that this part of the code had gone through an LLM.

Fortunately, I could retrieve the old URLs on old git commits. I checked the URLs carefully. The LLM had HALLUCINATED most of the path part of the URLs! Replacing things like domain.com/this-article-is-about-foobar-123456/ by domain.com/foobar-is-so-great-162543/...

These kinds of very subtle and silently introduced mistakes are quite dangerous. Be careful out there!
by kinix | 2025-10-09 06:56:45+00:00
Unrelated to the content: why on earth is super-light grey a good "bold" colour for a white background? I'm having to highlight each of the bolded parts of the text just to understand it :/

edit: console command for anyone else struggling to read this `document.documentElement.style.setProperty('--bulma-strong-color', '#000');`