MurphyA/hacker-news huggingface dataset:
by euroderf | 2025-11-26 12:37:48+00:00
Part of the appeal of UFO was the music by Barry Gray. Great stuff. The opening montage always grabbed me.

And the Moonbase uniforms were very eyecatching to say the least. And some of the plots were almost as mindwarping as The Prisoner.

OTOH why did the alien craft always approach the Earth from the side where the Moon is ?
by bossyTeacher | 2025-11-26 12:38:00+00:00
We are not ready for social media. And we are definitely not ready for transformers let alone some sort of sub-AGI that is still powerful enough to complete most projects. Economies would fall quicker than the stock market on that fateful black monday. Our economies still operate on the assumption that only humans can do most of the work that delivers value. Remove that assumption, and you have nearly zero operating costs but also nearly zero revenue for virtually every single company operating mostly in the knowledge sector.
by Yizahi | 2025-11-26 12:38:02+00:00
> So you think the thing, who holds more control/force at doing arbitrary things as the thing sees fit, is more intelligent? That sounds to me more like the definition of power, not intelligence.

I want to address this item. I think not about control or comparing something to something. I think intelligence is having at least some/any voluntary thinking. A cat can't do math or write text, but he can think on his own volition and is therefore intelligent being. A CPU running some externally predefined commands, is not intelligent, yet.

I wonder if LLM can be stepping stone to intelligence or not, but it is not clear for me.
by zmgsabst | 2025-11-26 12:38:24+00:00
Curry-Howard literally says that a proof your object has a property is equivalent to an algorithm which constructs a corresponding type.

I’m not “sprinkling magic powder”, but using the very core of the correspondence:

A proof that your network has some property is an algorithm to construct an instance of appropriate type from your network.

In this case, we’re using algorithms originally designed for protocols in CS to construct a witness of a property about a graph coloring. In the article, it details exactly his realization this was true — during a lecture, seeing the types of things constructed by these algorithms corresponding to the types of objects he works with.
by vrighter | 2025-11-26 12:38:26+00:00
And all that stuff you mentioned is stuff you can't buy. You can't buy a preconfigured router that fits your setup. You need to configure it yourself. And if it's the CEO who's provisioning servers and installing and configuring routers and setting up networking routes and crap like that, then there's your problem!

And if he's running an e-commerce store, then why the hell would he be stuggling with pipewire? What the hell is xdg-desktop-portal even used for when hosting a website. What does your audio obsession (nothing wrong with it, I have my own obsessions) making you fuck with amplifiers and DACs have to do with security in any way shape or form?

It really sounds like you started out with the conclusion of "This is boring, I don't want to do it" and finding reasons to justify it.
by seec | 2025-11-26 12:38:53+00:00
I have been doing all kind of strategies since I have lived largely alone for over 15 years. I have also worked in restaurant kitchens that were on the premium side. I can do very sophisticated pastries from the Ferrandi book.

If there is one thing I know for sure is that there is very little benefits in cooking, apart from the pleasure of eating something good. Even if you want to eat healthy there are plenty of ways that require very little cooking. The only problem is how much money you can throw at the problem, the easier it is the more expensive it will be. Sometimes you don't even have a choice because of time constraints (people who do 2 hours commute everyday just can't allocate time to that).
by DavidPeiffer | 2025-11-26 12:39:14+00:00
>This is one of the reasons I am so skeptical of the current AI hype cycle. There are boring, well-behaved classical solutions for many of the use-cases where fancy ML is pushed today.

In 2013 my statistics professor warned that once we are in the real world, "people will come up to you trying to sell fancy machine learning models for big money, though the simple truth is that many problems can be solved better by applying straightforward statistical methods".

There has always been the ML hype, but the last couple years are a whole different level.
by death_eternal | 2025-11-26 12:39:58+00:00
1. It manages memory through deterministic ownership rules and optional arena allocation. Pointers never outlive the allocator that created them, and the compiler performs lifetime checks to prevent use-after-free or double-free errors.

2. Axe does not use C++-style RAII. It employs deterministic cleanup through defer, which allows resources to be released predictably. Also, objects allocated inside an arena are freed as a group when the corresponding arena is destroyed.

3. Not yet. There is an overload system currently:

overload println(x: generic) { string => print_str; char* => println_chrptr; i32 => println_i32; char => println_char; }(x);
by metalman | 2025-11-26 12:41:00+00:00
"chat~fu"

cachonk!

snap your cuffs, wait fot it eyebrows!

and demonstrate your mastery ,to the muterings of the golly gee's

it will last several more months untill the , GASP!!!, bills ,maintenance costs, regulatory burdens, and various legal issues combine to, pop AI's balloon, where then AI will be left automating all of the tedious, but chair filling, beurocratic/secretarial/appretice positions through out the white collar world. technology is slowly pushing into other sectors, where legacy methods and equipment can now be reduced to a free app on a phone, more to the point, a free, local only app. fact is that we are way over siliconed going forward and that will bite as well, terra bite phones for $100, what then?
by javipas | 2025-11-26 12:41:53+00:00
Ever wonder how your cheap HP printer became a subscription service? This story goes back to King Camp Gillette and his disposable razor. It’s part of a bigger story on how the 'razor-and-blades' business model (expensive consumables!) infected everything from ink and coffee pods (Keurig/Nespresso) to modern razor clubs. And from that we arrived to the curse of the subscription economy.
by cbeach | 2025-11-26 12:41:58+00:00
I think if you watch the two videos (original vs edited) you'll understand just how egregious this editing was. And it's not the first time the BBC has deliberately misquoted Trump to make him look like he is inciting.

There is another news show where they did similar.

And 2018, the BBC to to Twitter to misquote Trump as saying "war [with Iran] will follow" as opposed to what he actually said ("more will follow").

Their "apology" was blatent trolling - when called out on their fake quote, they replied "#ourbad" (yes, hashtag "ourbad")

https://www.telegraph.co.uk/news/2018/09/26/bad-bbc-accused-...
by menaerus | 2025-11-26 12:42:39+00:00
I thought the OCR was one of the obvious examples where we have a classical technology that is already working very well but in the long-run I don't see it surviving. _Generic_ AI models already can do the OCR kinda good but they are not even trained for that purpose, it's almost incidental - they've never been trained to extract the, let's say name/surname from some sort of a document with a completely unfamiliar structure, but the crazy thing is that it does work somehow! I think that once somebody finetunes the AI model only for this purpose I think there's a good chance it will outperform classical approach in terms of precision and scalability.
by bossyTeacher | 2025-11-26 12:44:13+00:00
This. This is what I find hilarious that even smart HN folks seem unable to understand. Transformers tech products are a service offered by private companies who are under no obligation to serve it to you indefinitely. At any given point, they are free to end public access. And you better believe that they will do so if it is in their interest. inb4 open source models, those models are also hosted on the servers of private companies who are also under no obligation to maintain public access indefinitely. And even if you were smart enough to download one in advance, cloud services providers can stop providing access for transformers and you can rest assure that your machine won't be powerful enough to run it. Plus, NVIDIA and co can just keep their GPUS to themselves and only offer subpar versions to customers.

An individual will never win a fight against a corporate entity. And certainly not one in possession of a near AGI system.
by tripflag | 2025-11-26 12:44:34+00:00
Ah, a small correction regarding this... What I /meant/ to say in the video was that a lot of the INITIAL code was written this way, so the statement is mostly true for v0.2.3. Since then I've primarily been using vscodium (and recently zed) on my linux laptop, but I still tend to do quick prototyping on the phone when i get a bugreport or a sudden idea.

That part of the video was recorded at 3am as I just wanted to "get it done", which also explains the other mistakes (typos, phrasing). I tried to replace the audio-track of the video when i noticed the phonecoding part after uploading, but turns out that's not really possible, so I figured what's done is done, impractical as it is -- I've been trying to offer this correction when I see it come up.

So my workflow right now is mostly zed and pyright+black, and no AI/LLM except for localization of new strings to languages I don't speak.
by thunky | 2025-11-26 12:44:43+00:00
> What exactly is being de-valuated for a profession

You're probably fine as a more senior dev...for now.

But if I was a junior I'd be very worried about the longevity I can expect as a dev. It's already easier for many/most cases to assign work to a LLM vs handholding a human through it.

Plus as an industry we've been exploiting our employer's lack of information to extract large salaries to produce largely poor quality outputs imo. And as that ignorance moat gets smaller, this becomes harder to pull off.
by jermaustin1 | 2025-11-26 12:45:01+00:00
But the LLM can't execute code. It just predicts the next token.

The LLM is not doing anything. We are placing a program in front of it that interprets the output and executes it. It isn't the LLM, but the IDE/tool/etc.

So again, replace Gemini with any Tool-calling LLM, and they will all do the same.
by xxs | 2025-11-26 12:45:03+00:00
>Generic erasure is a giant pain in the rear

Personally, I don't get the sentiment. Yeah, decompiling might not produce the original source code, which is fair. It's possible to generate code using invokeDynamic and what not - still being valid code if a compiler opts to do so.

When decomiling bytecode there has to be a reason for, and a good one. There has to be a goal.

If the code is somewhat humanly understandable that's ok. if it's more readable than just bytecode, that's already an improvement.

Reading bytecode alone is not hard when it comes to reverse engineering. Java already comes with methods and fields available by design. Having local variable names and line numbers preserved is very common, due to exception stack traces being an excellent debugging tool. Hence debugging info gets to be preserved.

try/finally shares the same issues, albeit less pronounced.
by stavros | 2025-11-26 12:45:08+00:00
> did you not run into this problem described by ilya below

I used to run into a related issue, where fixing a bug would add more bugs, to the point where it would not be able to progress past a given codebase complexity. However, Codex is much better at not doing that. There are some cases where the model kept going back and forth between two bugs, but I discovered that that was because I had misunderstood the constraints and was telling the model to do something impossible.

> how did you discover that and why it slip out.

Sentry alerted me but I thought it was an edge case, and I didn't pay attention until hours later.

I use a spiral allocation algorithm to allocate plots, so new users are clustered around the center. Sometimes plots are emptied (when the user isn't active), so you can have gaps in the spiral, which the algorithm tries to fill, and it's meant to go to the next plot if the current one can't be assigned.

For one specific plot, however, conditions were such that the database was giving an integrity error. The exception handling code that was supposed to handle that didn't take into account that it needed to roll back before resuming, so the entire request failed, instead of resuming gracefully. Just adding an atomic() context manager fixed it.

> looks like site wasn't working at all when you posted that comment?

It was working for a few hundreds (thousands?) of visitors, then the allocation code hit the plot that caused the bug, and signup couldn't proceed after that.
by vidarh | 2025-11-26 12:45:14+00:00
It is categorically not wrong. With an MCP you have at a minimum all the same dependencies and on top of that a dependency on your agent supporting MCP. With skills, a lot of the time you don't need to ship code at all - just an explanation to the agent of how to use standard tools to access an API for example, but when you do need to ship code, you don't need to ship any more code than with an MCP.

The trivial evidence of this, is that if you have an MCP server available, the skill can simply explain to the agent how to use the MCP server, and so even the absolute worst case for skills is parity.
by dataflow | 2025-11-26 12:45:37+00:00
I think there are at least two degrees of freedom being discussed here, though I'm quite unsure, so someone please correct me if I'm wrong:

- What happens when MyCoroutine() is invoked (as an ordinary function invocation - no await etc.): does execution of the body start right then, or do you just get some sort of awaitable object that can be used to start it later?

- What happens when the result of said invocation is awaited (using your language's await operator plus any extra function calls needed to begin execution): is there a forced yield to the scheduler at any point here, or do you directly start executing the body?

The article seems to be treating the two as an indivisible pair, and thus discussing the behavior merely before and after the pair as a whole, but your link seems to be discussing the first?

Again, I'm quite unsure, so curious if anyone has thoughts.
by LadyCailin | 2025-11-26 12:46:01+00:00
But LLMs don’t get a pass on the billions of years of front loading either. I mean, I see what you’re saying, and I get your point for sure, but my point is that we should be able to find a more clever way to accomplish this that builds off our billions of years of front loading. LLMs seem like the lazy way out in a way.
by Daviey | 2025-11-26 12:46:32+00:00
BBC Newsnight aired the story first in June 2020.

Also, the BBC first reported on the boat immigration crisis on "BBC South East" regarding small boat arrivals in 2014.

GB News wasn't launched until June 2021, so they can't take much credit here.

Daily Mail is likely to buy The Telegraph, which honestly worries me.
by LiamPowell | 2025-11-26 12:46:41+00:00
The main reason I'm posting this is not because this malware is particularly interesting (although seeing this sort of AI use in the wild is interesting) but because of how it's ending up on people's machines. Specifically, it's being widely advertised via Google ads using the most obviously malicious ads I've seen in a very long time: https://adstransparency.google.com/advertiser/AR129387695568...

I'm really surprised to see that Google has let 2000 of these ads through without catching them and that they have not removed them after reports from weeks ago. When clicking in the ads an exe file is immediately downloaded, which you'd think some tool at Google would be able to trivially catch.
We built an AI-powered platform for investing in real SMBs (feedback welcome)
by rivellium | 2025-11-26 12:46:49+00:00
Hi HN,

We’ve been building Rivellium — a multi-asset investment platform that lets people invest in real, revenue-generating SMBs (manufacturing, logistics, service companies, etc.) rather than high-risk startups or crypto tokens.

The core idea: make real-economy investing accessible, transparent, and supported by automated AI scoring + a future P2P secondary market.

A few technical details: • Scoring engine: combines structured SMB financial data with operational metrics and sector-level benchmarks. • Stripe + INXY Payments for multi-method deposits (card, bank transfer, local methods). • Built on a Python backend with async pipelines for risk/financial modeling. • Frontend: React + modular UI system. • Infrastructure: GCP + Vercel. • KYC/AML handled via Medallion (auto-verification + sanctions/PEP checks).

We launched our MVP recently — first users and initial investments have started to come in. Currently working on: • Public-assets layer (indexed instruments) • P2P secondary market for liquidity • New updated UI (ships this week) • Referral system • Extended reporting for investors

We’re still early, so I’d really appreciate feedback from the HN community: — thoughts on the model? — risks we might be underestimating? — ideas for making the scoring engine more robust? — anything that looks unclear, unsafe, or technically weak?

Happy to answer any questions. Not trying to sell anything — I’m mostly looking for honest technical/product feedback from people who have built financial or marketplace systems before.

Thanks for reading.
by throw0101c | 2025-11-26 12:47:28+00:00
> So if I as an artist paint a painting, I could not sell it in my small personal gallery by the beach? That is ridiculous.

It is so ridiculous that it is how movies were made and distributed in the US for decades:

* https://en.wikipedia.org/wiki/United_States_v._Paramount_Pic....

* https://en.wikipedia.org/wiki/Studio_system#The_end_of_the_s...
by balamatom | 2025-11-26 12:48:20+00:00
>Retconning 2049 into that was.. Hard.

After Deckard did an exemplary job, everyone liked it so much that they they replaced his entire cadre with simulacra.

>Personally I prefer the PKD book. It was more nuanced.

Oh absolutely! Just recently bought a fake animal and pondered it. Love PKD for selling various angles on the same trip for decades; wonder if his OG exegesis can be read anywhere...
by scribu | 2025-11-26 12:48:44+00:00
> But isn't it true for JavaScript too?

You're right, the equivalent JS script produces the same sequence of outputs.

It turns out there is a way to emulate Python's asyncio.create_task().

Python:

await asyncio.create_task(child())

JavaScript:

const childTask = new Promise((resolve) => { setTimeout(() => child().then(resolve), 0) }) await childTask
by t0duf0du | 2025-11-26 12:48:45+00:00
There are great big software projects and shitty ones. IRCTC, UPI being examples of great ones.

Insurance and RTO being shitty ones.

I had an insurance deadline very near and the payment was not showing up in the insurance providers dashboard so had to do it twice and now it was still not showing up.

Also I have faced huge problems with getting the learner's licence online.

Do let me know if you've faced anything same.
by srean | 2025-11-26 12:49:08+00:00
In general I agree. For OCR I agree vehemently. Part of the reason is the structure of the solution (convolutions) match the space so well.

The failure cases are those where AI solutions have to stay in a continuous debug, train, update mode. Then you have to think about the resources you need, both in terms of people as well as compute to maintain such a solution.

Because of the way the world works, it's endemic nonstationarity, the debug-retrain-update is a common state of affairs even in traditional stats and ML.
by auxiliarymoose | 2025-11-26 12:49:56+00:00
> Today we have AI models that can already do as good, almost as good, or even better than the average human in many many tasks, including the ones you mentioned.

We really don't. There are demos that look cool onstage, but there is a big difference between "in store good" and "at home good" in the sense that products aren't living up to their marketing during actual use.

IMO there is a lot of room to grow within the traditional approaches of "yesterday" - The problem is that large orgs get bogged down in legacy + bureaucracy, and most startups don't understand the business problems well enough to make a better solution. And I don't think that there is any technical silver bullet that can solve either of these problems (AI or otherwise)
by tgsovlerkhgsel | 2025-11-26 12:49:58+00:00
The main takeaway for me is that in Python, this doesn't work:

async def somethingLongRunning(): ... x = somethingLongRunning() ... other work that will take a lot of time ... await x # with the expectation that this will be instant if the other work was long enough

That's counterintuitive coming from other languages and seems to defeat one of the key benefits of async/await (easy writing of async operations)?

I've seen so many scripts where tasks that should be concurrent weren't simply because the author couldn't be arsed to deal with all the boilerplate needed for async. JavaScript-style async/await solves this.
by oliwarner | 2025-11-26 12:50:11+00:00
And rightly so. If you use a calculator instead of learning the fundamentals of how to do maths, you don't learn. This is reflected on them not being touched until 11+ in the UK, and even then there are exams where they are forbidden.

I'm not against the calculator and I'm not against LLMs. I'm against people choosing ignorance.
by autoexec | 2025-11-26 12:50:49+00:00
> The idiotic clickbait images and titles WORK. People don't use them because they want to, they use them because they have to.

They only "work" if your only goal is to get clicks. Lots of literal toddlers and stupid adults will click on idiotic clickbait. Will they stay and watch the content? Will they understand it? Will they appreciate it? Or, will they just smash their fist at the screen when the next shiny obnoxious looking thing pops up or drool all over themselves until the next video auto-plays?

If all you care about are clicks and views and you don't give a shit about your audience you might as well just start posting disturbing videos of Elsa and pregnant Spider-man because as it turns out that WORKS also.

If on the other hand you respect your audience and don't want to mislead or annoy them with click-bait titles and irrelevant bullshit thumbnails then, yes you will get fewer clicks and views, but the smaller number of people viewing your videos will be people who clicked because they actually care about your content and not just because of bullshit clickbait. Those users will be thankful that your channel isn't polluted with the garbage that plagues so many other videos made by youtubers who don't care about anything but clicks.

Having and maintaining integrity is usually a little inconvenient, but it is also very much appreciated and people with integrity improve the spaces we share. Youtubers sacrificing their integrity for clicks and views isn't something they "have to do", it's just what they choose to do. If their content is actually worth watching then people will watch it without that crap, especially when it comes to an already well established channel like LTT. Don't make excuses for youtubers who care more about clicks and views than they do about their viewers or the quality of what they put out into the world.
by lazide | 2025-11-26 12:51:38+00:00
When people say ‘agentic’ they mean piping that token to various degrees of directly into an execution engine. Which is what is going on here.

And people are selling that as a product.

If what you are describing was true, sure - but it isn’t. The tokens the LLM is outputting is doing things - just like the ML models driving Waymo’s are moving servos and controls, and doing things.

It’s a distinction without a difference if it’s called through an IDE or not - especially when the IDE is from the same company.

That causes effects which cause liability if those things cause damage.