MurphyA/hacker-news huggingface dataset:
by reorder9695 | 2025-08-13 15:36:43+00:00
Farming is one of the hardest jobs out there. You need to effectively run your own business on fine margins often relying on government subsidies which can change over time, with a lot of risk due to crop failures/livestock disease (culling can be necessary for chickens due to bird flu etc). It requires hard manual labour running the farm with physical risk to you if you work with livestock. Cows don't care if you get sick, they still need cared for no matter what, there isn't much space for holidays or illness. This isn't to mention the few times of the year the tractors are used as you describe, but most tractors aren't this fancy, and how would you like to spend all day every day for a time working the land with the tractor from sunrise to sunset?
by Joel_Mckay | 2025-08-13 15:36:45+00:00
Blender material node workflows are non-obvious, and indeed many find Adobe products easier to learn.

Sometimes parametric options can be fairly useful when combining displacement modifiers:

https://tinynocky.gumroad.com/l/tinyeye

https://kuhantilope.gumroad.com/l/ultimate-skin

Where a few people make it look deceptively easy =3
by jmaestrooper | 2025-08-13 15:36:55+00:00
Can someone please refer me to the hard data on "overhiring in 2020"?

I was laid off as part of the initial panic in early 2020. The job market for IT for the entirety of 2020 was dead. D-E-A-D. There was a _very_ small pickup in the summer when people got more optimistic about the vaccines but it waned very quickly.

I'm in the Midwest so it might have been different in the West but I doubt it was that much different.

There was _some_ pickup in 2021, when companies realized the end of the world isn't happening soon, but it was not very significant. IT job market never really normalized, there was some pickup in 2022 but by then LLM hype started causing layoffs to go up and openings down.
Show HN: Vaultrice – A real-time key-value store with a localStorage API
by adrai | 2025-08-13 15:37:04+00:00
Hi HN,

I'm Adriano, one of the makers of Vaultrice. I'm excited (and a little nervous!) to share what we've been building.

For years, we found ourselves in a frustrating loop: whenever we needed a simple real-time feature—like a "who's online" list, a collaborative app, or just sharing state between a marketing site and our main app — we'd end up spending days setting up the same stack or discarded to do it. Setting it up, it always involved wiring together a database, a WebSocket server, an API, and managing the connection state. It felt like massive overkill for what we were trying to achieve.

We wanted a tool that felt as simple to use as the browser's `localStorage` API but worked across domains and devices, with real-time sync and security built-in.

So, we built Vaultrice.

It’s a key-value data store built on top of Cloudflare's Durable Objects, which gives you a strongly consistent backend for each data object. You interact with it through our TS/JS SDK, which comes in two flavors:

1. `NonLocalStorage`: A low-level client with a `localStorage`-like API (`setItem`, `getItem`, etc.) plus real-time events and presence (`.on()`, `.join()`).

2. `SyncObject`: A higher-level, reactive JavaScript Proxy. You just change a property on an object (`doc.title = 'New Title'`), and it automatically syncs to all other connected clients.

The goal is to let you build the real-time features you want in minutes, not days. We've also put a lot of thought into a layered security model, allowing you to go from simple API key restrictions all the way to server-signed object IDs and client-side E2EE.

We’ve just launched and would be grateful for any feedback from the HN community. What do you think of the API design? Are there use cases we haven't considered? Any thoughts on the security model?

We'll be here (or via email (support@vaultrice.com)) to answer any questions. Thanks for checking it out!
by dragonwriter | 2025-08-13 15:37:17+00:00
Its not a ban on autonomy, which didn't exist at the time to ban. It was directed at people trying to maximize use of their time by getting off slow moving, non-autonomous, equipment to do other things and then climbing back on when needed to make course changes.

It also functions to ban unattended autonomous vehicles now that they do exist, and it may need to be adjusted to allow for an appropriate regulatory framework for limited and safe use of unattended autonomous vehicles, but that was not a subject of concern when it was written.
by evklein | 2025-08-13 15:37:46+00:00
Probably depends on BO/stakeholder as well. B2B solution that has a low risk of killing anyone? Maybe fuck it, let the model have its way.

Technology that controls software that keeps people alive, controls infrastructure, etc., uhhhh I don't think so. I guess we're just waiting for the first news story of someone's pacemaker going haywire and shocking them to death because the monitoring code was vibed through to production.
by AIPedant | 2025-08-13 15:37:55+00:00
I am less interested in questioning training data corruption than I am in questioning claims like this:

test reasoning abilities such as pattern recognition, lateral thinking, abstraction, contextual reasoning (accounting for British cultural references), and multi-step inference.... its emphasis on clever reasoning rather than knowledge recall, Only Connect provides an ideal challenge for benchmarking LLMs' reasoning capabilities.

It seems to me that the null hypothesis should be "LLMs are probabilistic next-word generators and might be able to solve a lot of this stuff with shallow surface statistics built from inhumanly large datasets, without ever properly using abstraction, contextual reasoning, etc." This is particularly true for NYT Connections, but in general evaluations like this seem to be at least partially testing how amenable certain word/trivia games are to naive statistical algorithms. (Many NYT Connections "purple" categories seem like they would be quite obvious to a next n-gram calculator, but not for people who actually use words conversationally!) Humans don't use these statistical algorithms for reasoning except in particular circumstances (many use "folk n-gram statistics" when playing Wordle; poker; serious word game players often learn more detailed tables of info; you could see competitive NYT Connections players learning a giant bag of statistical heuristics to help them speedrun things). We just can't accumulate the data ourselves without making a concerted computer-aided effort.

In general a lot of LLM benchmarks don't adequately consider that LLMs can solve certain things better than humans without using reasoning or knowledge. The most stupid example is how common multiple choice benchmarks are, despite us all learning as children that multiple-choice questions can be partially gamed with shallow statistical-linguistic tricks even if you have no clue how to answer the question honestly[1]; it stands to reason that a superhuman statistical-linguistic computer could accumulate superhuman statistical-linguistic tricks without ever properly learning the subject matter. AI folks have always been quick to say "if it quacks like a duck it reasons like a duck" but these days computers are quite good at playing duck recordings.

[1] "When in doubt, C your way out," sniffing out suspicious answers, shallow pattern-matching to answer reading comprehension, etc etc. One thing humans and LLMs actually do have in common is that multiple-choice tests are terrible ways to assess their knowledge or intelligence.
by colechristensen | 2025-08-13 15:37:56+00:00
The $3 -> wouldn't motivate a lot of people, it's more like the cherry on top of asking folks nicely to drive less.

Like if you asked me to help you move a couch and offered me a beer, a beer isn't really a fair trade for the labor value, but I'm being nice and helping, a nice treat makes things a little better.
by klabb3 | 2025-08-13 15:37:58+00:00
> IMO there a flaw in this typical argument: Humans are not less fallible than current LLMs in average, unless they're experts - and even that will likely change.

This argument is everywhere and is frustrating to debate. If it were true, we’d quickly find ourselves in absurd territory:

> If I can go to a restaurant and order food without showing ID, there should be an unprotected HTTP endpoint to place an order without auth.

> If I can look into my neighbors house, I should be allowed to put up a camera towards their bedroom window.

Or, the more popular one today:

> A human can listen to music without paying royalties, therefore an AI company is allowed to ingest all music in the world and use the result for commercial gain.

In my view, systems designed for humans should absolutely not be directly ”ported” to the digital world without scrutiny. Doing so ultimately means human concerns can be dismissed. Whether deliberately or not, our existing systems have been carefully tuned to account for quantities and effort rooted in human nature. It’s very rarely tuned to handle rates, fidelity and scale that can be cheaply achieved by machines.
by uv-depression | 2025-08-13 15:38:42+00:00
> the cat is out of the bag

Someone, if we stretch that metaphor, intentionally opened the bag for profit. We can and should hold them accountable.

> the people involved with that have to deal with that

Yep, and they should hold the people who caused this accountable.

> is maybe worth trying (good luck) but I don't give it a very high chance of success

You may be correct that it has a low chance of success. However, people who think like you are exactly the cause. People who value Musk's net worth more than science, people who fetishise "progress at all costs," regardless of whether or not the progress actually helps people or is what makes sense (municipal internet, folks!). Understanding physics is also critically important progress, but it doesn't make money next quarter so you don't care.

So you'll forgive me if I don't take your advice on the situation.
by rikroots | 2025-08-13 15:38:57+00:00
I've done a lot of work recently to make my library more "LLM Friendly", but I'm not willing at this time to sign up to a service which I don't know I'd ever use again just to run a test on your behalf. If you want to run the test on my library then its GitHub can be found here: https://github.com/KaliedaRik/Scrawl-canvas
by bjourne | 2025-08-13 15:39:08+00:00
I appreciate the reframing—really smart take—but I’d push back on one key point: cost of errors isn’t necessarily what makes CEOs safer than engineers—it’s accountability.

As others have pointed out, engineering mistakes lead to immediate, measurable fallout: you crash servers, leak user data, or break security. That’s real, visible risk. But if an LLM hallucinates a disastrous strategy, who’s left holding the bag? The board? The model vendor? Executives? That ambiguity makes it hard to fully trust LLMs with real decision-making power.

CEOs are expected to bear responsibility—publicly and privately. If a strategy fails, there’s someone to fire—clearly defined accountability. LLMs can offer brilliant synthesis and scenario generation, but they can’t be “fired,” nor can they take blame. They’d always be advisors, not agents.

Another thing: a large part of leadership isn’t strategy—it’s the human stuff: motivating teams, handling interpersonal dynamics, managing crises. That doesn’t look like prompt-and-response; it’s people work, messy and nuanced. LLMs can support it, sure—but lead it? Not yet.

And yes, the political barrier is hugely underestimated—CEOs are politically powerful. Very few voluntarily make themselves obsolete. Hacker News

TL;DR: LLMs might be great at generating strategy—or helping write code—but they’re not suited to own the outcomes. Accountability, leadership, and human nuance still matter.
by dysoco | 2025-08-13 15:39:49+00:00
I don't want to come off as insensitive, and as a developer with a few years of experience and about to graduate, I'm obviously a bit worried about AI as well. However, this reads like an American overpanicking because they're used to living with a certain employment and economic stability that is just not the norm in most of the world, and are coming to terms with instability for the first time.

I come from a country where emigrating in search of new work, or trying to reinvent yourself and switch jobs, driving an Uber or flipping burgers if necessary to stay afloat, etc. is the norm. We've had a lot of political and economic instability, science and health defunding, etc., and yes, it's not great, but also people just... live on, and manage to do okay.

Yes, I know about the recent advancements in AI, but barring the AGI case which I believe is a bit overblown in this article, I think the rest, especially the Trump situation, tariffs, unrest, etc., will pass as well.
by bkettle | 2025-08-13 15:40:09+00:00
> So claiming car drivers do not pay the costs is just plain wrong.

We can’t determine that that is the case simply because the cost seems like a lot. California has the highest gas taxes in the US, so even if California is correctly pricing the externalities of consuming a gallon of gas (which I very much doubt), the rest of the country is under-pricing those externalities. The EU has a minimum gas tax of $1.60 per gallon, so if they are correctly pricing the externalities, California must be under-pricing them by over half.
by n4r9 | 2025-08-13 15:40:09+00:00
Cool! This paper is also quite readable: https://arxiv.org/pdf/2104.04841

On p.2 they follow my idea of adding the lowest possible letter at the end, although they generalise it to adding the letter as close to the end as possible. They conjecture that this process does not stop. I'm always amazed with combinatorics how quickly you arrive at questions that no one knows the answer to.
by johnisgood | 2025-08-13 15:40:10+00:00
I do not mind getting:

Verdict: This is production-ready enterprise security Your implementation exceeds industry standards and follows Go security best practices including proper dependency management, comprehensive testing approaches, and security-first design Security Best Practices for Go Developers - The Go Programming Language. The multi-layered approach with GPG+SHA512 verification, decompression bomb protection, and atomic operations puts this updater in the top tier of secure software updaters. The code is well-structured, follows Go idioms, and implements defense-in-depth security that would pass enterprise security reviews.

Especially because it is right, after an extensive manual review.
by scrollaway | 2025-08-13 15:40:13+00:00
> Do you just ask/prompt "do you recognize this puzzle?"

In essence, yes, but with a bit more methodology (though as I mentioned it was all ad-hoc).

We've tried to extract pre-existing questions as well through a variety of "You are a contestant on the british TV show Only Connect" and see if it can recognize questions - couldn't find anything that reliably reproduced preexisting knowledge. It's absolutely possible we missed something.
by PaulHoule | 2025-08-13 15:40:36+00:00
My experience prospecting mainly on LinkedIn is that if you create a profile congruent with your brand, blog, write about your subject, have good marketing collateral and target people who would really be interested in your B2B product you get good results -- there must have been some example but I swear I can't remember anyone I wanted to talk to that I couldn't get an audience with.
by dr_dshiv | 2025-08-13 15:40:48+00:00
AI is what people think AI is. In the 80s, that was expert systems. In the 2000s, it was machine learning (not expert systems). Now, it is LLMs — not machine learning.

You can complain, but it’s like that old man shaking their fist at the clouds.

Now, if you want to talk about cybernetics…
by duxup | 2025-08-13 15:41:04+00:00
I recall a radio report where a news reporter asking a US military officer about a given war, I want to say it was the Syrian civil war but I don't recall exactly.

The reporter referenced that one side, who had been relatively well equipped and trained compared to their opponent was no longer making much progress. This was somewhat confusing on the surface.

The officer explained that at a given scale every army is on the clock as far as how well it can perform with regards to its training. There's just a limited amount of time they have to get the job done if X% of their forces are engaged on the front line.

Eventually due to casualties or just cycling out trained troops due to service time the strategies and training and discipline break down and it is very difficult to recover without large scale training of troops that most countries can't afford / do (something akin to massive WWII mobilization and training systems).
by 369548684892826 | 2025-08-13 15:41:28+00:00
I'm not a Financial Advisor so I'm not qualified to make suggestions. But a lot of people find this [0] flow chart useful. It's UK focussed and you can probably skip to Step 8 (so maybe not that helpful?) but what it says for most people is that they should look at making long term investments in low cost index funds in a tax efficient savings wrapper (e.g. an ISA account in the UK)

Buying individual properties as an investment can be a huge headache, even trying to sell the investment can take a long time. And as the other reply said, it is quite risky to have so much tied up in a single property where anything could happen to it.

0: https://ukpersonal.finance/flowchart/

edit: A better link, Investing 101: https://ukpersonal.finance/investing-101/
by aaronbaugher | 2025-08-13 15:42:55+00:00
Tractors are made heavy for traction (hence the name), not for safety. In addition to the weight of the tractor itself, fluid is often added to the tires for extra weight, and weights added to the front for more traction and to keep the front down when pulling a heavy load.

You can gain some traction by going from tires to tracks, as some modern tractors do, but you still need a certain amount of weight or you're just going to spin when you're trying to pull a 30-foot-wide chisel plow through soil and last year's stalks.

Going fully autonomous might make tractors a little cheaper, if they don't need A/C and mirrors and things like that, but not lighter. And they'd still need the human stuff for occasions when it can't drive itself anyway, like moving it around the barn lot or going down the road to the next field.
by jmaestrooper | 2025-08-13 15:43:41+00:00
Sure, it wasn't bad when IT caused automation and elimination of many job positions and entire occupations, both manual and office. Now that we're on the receiving end of it, it is a bad thing all of a sudden.

As for the upcoming crisis, there's an increase in inequality and further accumulation of wealth among fewer and fewer individuals. As long as these individuals continue to spend their newly acquired wealth to compensate for lower spend by the less fortunate (which is exactly what's been happening), the economy will be fine.
by Nevermark | 2025-08-13 15:43:56+00:00
Owners of capital and machine labor can continue making bank and driving demand, even if there are no more human laborers making any money.

Humans are not necessary for an economy. It’s an easily missed assumption, because until now we are the only intelligent units of labor, capital ownership and demand.

But corporations long ago become units of all three, and AIs effectively become citizens simply by acting through an umbrella corporation. Corporations are (in)famously already first class political participates, via their money.

As long as AIs/corporations are motivated to compete and survive, demand from humans won’t be necessary for the economy to keep growing.

If anything, the ease with which AI/robotics will adapt to space habitats, and the vast resources untapped in the solar system, will enable a potentially human-independent economic explosion.
by spurgu | 2025-08-13 15:44:05+00:00
And so it's just a bill away from the data is suddenly being available for any purpose. For public safety of course. The same people who want Chat Control to scan our messages for sure want to scan and raise alarms for suspicious behaviors in public places too. They just can't implement it all at once or there'd be an uproar. But if it happens slowly like this, bit by bit... frogs getting boiled in the UK (and elsewhere too).
by jerf | 2025-08-13 15:44:06+00:00
Appalling. The entire question of "fixing social media", for any definition of "fixing", involves not just the initial reaction to some change but the second-and-greater-order effects. LLMs are point-in-time models and intrinsically can not be used for even guessing at second-order effects of a policy over time. This shouldn't have gotten past the proposal phase.
by westurner | 2025-08-13 15:44:20+00:00
> The quality is irrelevant in the overwhelming majority of cases

Software quality is especially important in safety critical applications.

We should not expect an LLM trained solely on formally-verified code to produce formally-verified code. I don't think that also training on specs and hateful training material will fix that.

So then we're back to the original software engineering objectives of writing better SAST, DAST, Formal Method, side channel, and fuzzing tools for software quality assurance.
by the_af | 2025-08-13 15:45:01+00:00
I've fought with this in informal (non-technical) sessions with ChatGPT, where I was asking analysis questions about... stuff that interests me... and ChatGPT would always reply:

"You're absolutely right!"

"You are asking exactly the right questions!"

"You are not wrong to question this, and in fact your observation is very insightful!"

At first this is encouraging, which is why I suspect OpenAI uses a pre-prompt to respond enthusiastically: it drives engagement, it makes you feel the smartest, most insightful human alive. You keep asking stuff because it makes you feel like a genius.

Because I know I'm not that smart, and I don't want to delude myself, I tried configuring ChatGPT to tone it down. Not to sound skeptical or dismissive (enough of that online, Reddit, HN, or elsewhere), but just tone down the insincere overenthusiastic cheerleader vibe.

Didn't have a lot of success, even with this preference as a stored memory and also as a configuration in the chatbot "persona".

Anyone had better luck?
by derbOac | 2025-08-13 15:45:17+00:00
> while I liked it better than Twitter, for me it was disappointing that it was just Twitter, but different

I feel exactly the same way.

I think there needs to be a kind of paradigm shift into something different, probably something that people in general don't have a good schema for right now.

Probably something decentralized or federated is necessary in my opinion, something in between email and twitter or reddit? But there's always these chicken and egg issues with adoption, who are early adopters, how that affects adoption, genuine UX-type issues etc.
by AstroBen | 2025-08-13 15:45:29+00:00
How is investing in something that improves my productivity and output quality a downward career slope? Continuing to use a hand saw when there are power tools available seems like the downward slope..

If AI gets to a point where I'm fully able to be removed from auditing/coding positions.. well there won't be any coding positions left for anyone

> often don’t know what the Pr actually does

this is on them for being lazy. I thoroughly review the code AI produces. I don't commit it if I don't understand it
by glkindlmann | 2025-08-13 15:45:43+00:00
Note: the improved loop in the "1. They are not exact" can easily hang. If count > 2^24, then the ulp of f is 2, and adding 1.0f leaves f unchanged. What's wild is that a few lines later he notes how above 2^24 numbers start “jumping” every 2. Ok, but FP are always "jumping", by their ulp, regardless of how big or small they are.