MurphyA/hacker-news huggingface dataset:
by AlexandrB | 2025-09-02 19:05:04+00:00
> I have no idea how you came to the conclusion that this implies monetization is going to be awful.

Because cloud monetization was awful. It's either endless subscription pricing or ads (or both). Cloud is a terrible counter-example because it started many awful trends that strip consumer rights. For example "forever" plans that get yoinked when the vendor decides they don't like their old business model and want to charge more.
by notatoad | 2025-09-02 19:05:38+00:00
this seems to be making its way to western shows as well - when taskmaster has a food based challenge, they often include a reassurance that the food didn't go to waste. and i've seen similar on some youtube shows.

for example: https://youtu.be/_gNZR5IEsAA?si=x5nvoBzC9Xc4fxFs&t=1674
by HuwFulcher | 2025-09-02 19:05:46+00:00
I like the idea of there being interest specific mastodon servers. It makes content curation easier but the locking of accounts to a particular server is problematic.

Protocols like Nostr offer a good alternative to this. At the moment relays are just used as nodes in the decentralised network but there is work on how to view feeds from specific relays which could make the idea of content specific relays more likely
by nikole9696 | 2025-09-02 19:06:15+00:00
This surprises me a lot. I spin up new react apps with vite often to replicate issues with 3rd party libs we use. Like how do they not know you can just spin something up over on CodePen or CodeSandbox and there's not a hint of a server side paradigm required? (sure, vite has a little server but you don't really need to know anything about it)
by dmschulman | 2025-09-02 19:07:11+00:00
Eh, if this is true then IBM and Intel would still be the kings of the hill. Plenty of companies came from the bottom up out of nothing during the 90s and 2000s to build multi-billion dollar companies that are still dominate the market today. Many of those companies struggled for investment and grew over a long timeframe.

The argument is something like that is not really possible anymore given the absurd upfront investments we're seeing existing AI companies need in order to further their offerings.
by ants_everywhere | 2025-09-02 19:07:25+00:00
> What gets me is that this isn't even a software moat anymore - it's literally just whoever can get their hands on enough GPUs and power infrastructure.

I'm curious to hear from experts how much this is true if interpreted literally. I definitely see that having hardware is a necessary condition. But is it also a sufficient condition these days? ... as in is there currently no measurable advantage to having in-house AI training and research expertise?

Not to say that OP meant it literally. It's just a good segue to a question I've been wondering about.
by buu700 | 2025-09-02 19:07:40+00:00
Define "hard to master". I use LLMs all the time, sometimes as a writing assistant, and have never had the problem of trying to pass off a GPT response to a single one-line prompt as my own words. I haven't found LLMs hard to master.

An 80-year-old who barely uses computers and still types full sentences into Google (or who struggled for years to unlearn that habit) might find LLMs hard to master. Someone with poor written communication skills might find LLMs hard to master. Shockingly, it turns out that different people have different skills and life experiences.

I never used the word "faith". I'm not sure why you feel the need to make up a straw man to attack rather than respond to my comment as written, or why you feel the need to repeatedly insult me and accuse me of bad faith. It sounds like you're more interested in trying to win some perceived argument than engaging in constructive discussion.
by daft_pink | 2025-09-02 19:08:04+00:00
Essentially sovereign immunity exists, because there is a collective entity problem and circular liability argument that applies to penalties for the government.

Since we fund and elect the government, we are essentially all collectively responsible for the government, and with our tax dollars we are all collectively liable for the government debts.

In many cases, it doesn’t make sense to penalize ourselves and thus the government often has sovereign immunity in many cases.
by t123278713247 | 2025-09-02 19:08:08+00:00
Ehud Barak was on Paragon's board of directors. Barak also invested with Epstein in Carbyne:

https://www.jns.org/jns/benjamin-netanyahu/23/6/2/292333/

Other data collection/surveillance software from the Epstein circle include PROMIS (Robert Maxwell allegedly sold a backdoored version), Chiliad (FBI search software, Christine Maxwell, seems legit) and CargoMetrics (Ghislaine Maxwell's husband, maritime container tracking).
by jmclnx | 2025-09-02 19:08:25+00:00
Very nice, I will try it out!

Back then I was an operator (now called admin) and at the time I thought these micros were "toys" since I was on a "real" computer.

Little did I know these little systems would kill the systems I worked with and end up pretty much running the world. I think the only place mainframes rule now are in very high Financial Transaction Systems.

FWIW, very glad to see the article published in Gemini, I have moved my site to Gemini a year ago.
by tptacek | 2025-09-02 19:08:38+00:00
I didn't think any part of linear algebra was boring. I was hooked from the moment I saw Ax=b => x = b/A. Gaussian elimination is a blast, like an actually-productive Sudoku puzzle, and once you have it down you can blaze through the first 2/3rds of an undergrad linear algebra course. I don't consciously try to gain automaticity with math subjects, but matrix-column multiplication I got pretty quickly and now I just have it.

I learned from Strang, for what it's worth, which is basically LU, spaces, QR, then spectral.

I am really bad at math, for what it's worth; this is just the one advanced math subject that intuitively clicked for me.
by acdha | 2025-09-02 19:09:10+00:00
I’ve used it to have the server generate fragments not processed in the normal page load which are then used as templates by JavaScript which populates them. That supported fast initial page loads compared to an SPA while being just as dynamic after being loaded.

This worked pretty well but definitely had some rough edges which I really wish the standards process could’ve focused on. Things like JSX are so much slower / memory intensive but people use them for convenience and it’d be nice to improve the ease-of-use story.
by dingnuts | 2025-09-02 19:09:32+00:00
AI feeding into a "private" database, so after the keylogger sends everything to OpenAI you can have a garbage summary!

Or if it uses a local model, enjoy the warmth and sound of your GPU while it consumes all of your system resources for instant messaging on, well, as you put it, three random services

but you know he tried Beeper!!!
by aripickar | 2025-09-02 19:09:42+00:00
Tech Companies are valued at a multiple of next 12 months revenue, not last 12 months revenue. Since anthropic grew from $1billion to $5billion in revenue in ~8 months, that means it ~10x'ed revenue y/y off of 1 billion base. If you assume even 60% of that growth is retained (low for traditional saas businesses, but who knows), then anthropic is ~10% of google in terms of revenue in mid ~2027.

Basically, 5x-ing revenue in 8 months off of a billion dollars starting revenue is insane. Growing this quickly at this scale breaks every traditional valuation metric.

(And no - this doesn't include margins or COGS).
by throwaway290 | 2025-09-02 19:10:41+00:00
This is beyond naive.

who would bother to develop it in a lab and publish pro bono if it can never be commercial? Making money is why the most capitalist countries developed this tech. like most other tech

and even if it is only published, do you think we wouldn't run chatbots ourselves at home with same results? remember how Google engineer went off the rails thinking it is conscious while working on this stuff, do you think he also was misled by adverts or something? or big corps won't buy the patent and run with it commercially advertising it like they do anyway? or if you pretend money and big corps don't exist and we deploy it for free for friends, same problem? etc

if you went back in time and killed capitalism in US and switched to command economy where people innovate because they will be sent to gulag otherwise, for sure most of today tech including this would not be developed. but it seems like a pointless exercise.

instead what should happen is all these megacorps are sued for copyright infringement, fined and shut down. the model won't be smart enough to sweet talk ppl into suicide if megacorps can't infringe our copyrights to train it.
by Spivak | 2025-09-02 19:11:07+00:00
You could organize an economy around labor-as-value, at least in terms of how workers are paid and goods are priced, but you have to be extremely diligent that you're directing work towards useful endeavors.

You can't escape that people will evaluate how useful goods are to them. Goods which are priced way lower than their utility will get snapped up, goods priced way higher than their utility will go unsold.
by ben_w | 2025-09-02 19:11:13+00:00
> If we had developed LLMs in a lab and released them in the form of papers and Python projects with model weights with clear descriptions of what they're capable of, like a responsible scientific endeavor, then we'd not be seeing the problems we are, even with public access.

I'm now thinking of all of the times people here of sarcastically stated "OpenAI thought GPT-2 was too dangerous to release"*, as if danger only comes immediately and severely or not at all.

* wasn't even what OpenAI said, they just proposed setting a norm of caution because a release can't be undone
by dlcarrier | 2025-09-02 19:11:28+00:00
Espressif's ESP32 line uses an MCU IC, either sold by itself (https://www.espressif.com/sites/default/files/documentation/...) or with flash memory and RAM ICs, all packaged together in a system-in-package footprint. (e.g. https://www.espressif.com/sites/default/files/documentation/...) There are various options for which flash and RAM ICs are packaged together, but the ESP32 die itself is very much an MCU and has only has 520 KB of SRAM.

A managed switch is very computy heavy, and does usually run a microprocessor with a full RTOS, if not Linux itself, which probably costs in the mult-dollar range. It's also not something most people have at home, outside of the switch built into their router. Everything elese you mentioned usually runs on microcontrollers with under 1 MiB of RAM. For example, Infineon's CYUSB306X series ASICs for webcams come in two RAM sizes: 256 KiB or 512 KiB, despite handling gigabits per second of data, and having an MCU at all isn't even necessary. (https://www.latticesemi.com/usb3#_CDED461DE15245C78A2973D4A4...) The Pinecil's Bouffalo BL706 MCU has 123 KiB of RAM, despite being a low-volume product where design time matters more than component cost. (https://wiki.pine64.org/wiki/Pinecil, https://en.bouffalolab.com/product/?type=detail&id=8) Microwave ovens are so high volume that they often don't even use packaged microcontrollers, mounting the die directly on the PCB, with an epoxy blob protecting it, and there's no way any would splurge on megabytes of SRAM. The most advanced microwave oven I've seen was from the 90's and definitely didn't splurge on an microprocessor. (https://www.youtube.com/watch?v=UiS27feX8o0)

A slow MCU with external memory could run anything, like booting into linux on an AVR (https://www.avrfreaks.net/s/topic/a5C3l000000BrFREA0/t392375) but it's going to be extremely slow and not practical for any commercial product, which if produced in any volume will have as little RAM as possible.
by interloxia | 2025-09-02 19:11:58+00:00
"Trained on 15 trillion tokens across more than 1,000 languages – 40% of the data is non-English"

70B and 8B

https://huggingface.co/swiss-ai/Apertus-70B-Instruct-2509

https://github.com/swiss-ai/apertus-tech-report/blob/9d4b0fb...

https://ethz.ch/en/news-and-events/eth-news/news/2025/09/pre...
by RebeccaTheDev | 2025-09-02 19:12:22+00:00
I'll add my voice to others here that this is a huge problem especially for small hobbyist websites.

I help administer a somewhat popular railroading forum. We've had some of these AI crawlers hammering the site to the point that it became unusable to actual human beings. You design your architecture around certain assumptions, and one of those was definitely not "traffic quintuples."

We've ended up blocking lots of them, but it's a neverending game of whack-a-mole.
by awongh | 2025-09-02 19:13:09+00:00
> All the innovation is coming "top-down" from very well funded companies - many of them tech incumbents

What I always thought was exceptional is that it turns out it wasn't the incumbents who have the obvious advantage.

Take away the fact that everyone involved is already at the top 0.00001% echelon of the space (Sam Altman and everyone involved with the creation of OpenAI), but if you had asked me 10 years ago who will have the leg up creating advanced AI I would have said all the big companies hoarding data.

Turns out just having that data wasn't a starting requirement for the generation of models we have now.

A lot of the top players in the space are not the giant companies with unlimited resources.

Of course this isn't the web or web 2.0 era where to start something huge the starting capital was comparatively tiny, but it's interesting to see that the space allows for brand new companies to come out and be competitive against Google and Meta.
by blutack | 2025-09-02 19:13:29+00:00
This might be a US/EU difference. It's pretty popular in the EU still, although some of the market has been taken by various Simulink to C tools.

Every Rolls-Royce gas turbine FADEC runs ADA binaries on a custom processor [1].

It's also used extensively at Airbus. Lots of DO-178C (safety critical aerospace).

1: https://www.his-conference.co.uk/session/visiumcore-a-high-i...
by fennecbutt | 2025-09-02 19:13:48+00:00
It's just mass stupidity really. Technology is just a lever for what already existed.

The same people blindly trusting AI nonsense are the same people who trusted nonsense from social media or talking heads on unreputable news channels.

Like, who actually reads the output of The Sun, etc? Those people do, have always done and will continue to do so. And they vote, yaaay democracy - if your voter base lives in a fantasy world of fake news and false science is democracy still sancrosact?
by pcrh | 2025-09-02 19:13:49+00:00
You're correct that the calculations are a bit more complex in reality.

However, in a mortgage situation, the borrower does accumulate capital, whereas in a housing association scenario the resident/renter does not.

The major factor distinguishing the returns on the two options (lower rent vs mortage + depreciation) is whether the value of the property increases more than the costs of the mortgage, and what else the renter might do with their money. Note that most of the value of prime property (e.g. that in or near major cities) is in the value of the land, not the structure.

So there is substantial political pressure to support land value increases, to the cost of everyone except mortgage lenders....

Further, the notion that the cheaper costs achieved by housing associations and the like, including public housing are the result of subsidies can be shown to be incorrect. They're cheaper because of the different treatment of capital.
by ryukoposting | 2025-09-02 19:14:15+00:00
A footnote in the GPT-5 announcement was that you can now give OpenAI's API a context-free grammar that the LLM must follow. One way of thinking about this feature is that it's a user-defined world model. You could tell the model "the sky is" => "blue" for example.

Obviously you can't actually use this feature as a true world model. There's just too much stuff you have to codify, and basing such a system on tokens is inherently limiting.

The basic principle sounds like what we're looking for, though: a strict automata or rule set that steers the model's output reliably and provably. Perhaps a similar kind of thing that operates on neurons, rather than tokens? Hmm.
by thaumaturgy | 2025-09-02 19:14:42+00:00
Yeah, that's where IP intelligence comes in. They're using pretty big IP pools, so, either you're manually adding individual IPs to a list all day (and updating that list as ASNs get continuously shuffled around), or you've got a process in the background that essentially does whois lookups (and caches them, so you aren't also being abusive), parses the metadata returned, and decides whether that request is "okay" or not.

The classic 80/20 rule applies. You can catch about 80% of lazy crawler activity pretty easily with something like this, but the remaining 20% will require a lot more effort. You start encountering edge cases, like crawlers that use AWS for their crawling activity, but also one of your customers somewhere is syncing their WooCommerce orders to their in-house ERP system via a process that also runs on AWS.
by acdha | 2025-09-02 19:15:47+00:00
> Take cloud for example - where did the innovation come from? It was from the top.

Definitely not. That came years later but in the late 2000s to mid-2010s it was often engineers pushing for cloud services over the executives’ preferred in-house services because it turned a bunch of helpdesk tickets and weeks to months of delays into an AWS API call. Pretty soon CTOs were backing it because those teams shipped faster.

The consultants picked it up, yes, but they push a lot of things and usually it’s only the ones which actual users want which succeed.
by rsyring | 2025-09-02 19:16:08+00:00
I can't speak to the more technical aspects you bring up b/c I'm not that well versed in the underlying implementations and tradeoffs.

> and also too little too late.

I think it very likely that Python will still be around and popular 10 years from now. Probably 20 years from now. And maybe 30 years from now. I think that's plenty of time for a new and good idea that addresses significant pain points to take root and become a predominant paradigm in the ecosystem.

So I don't agree that it's too little too late. But whether or not a Virtual Threads implementation can/will be developed and be good enough to gain wide adoption, I just can't speak to. If it's possible to create a better devx than async and get multi-core performance and usage, I'm all for the effort.
by lelanthran | 2025-09-02 19:16:18+00:00
> I agree, but it's just too difficult to get away from the React ecosystem...

Why? What specifically are you using for "website with markdown" that needs React?

> Do you have suggestions on a better alternative?

Yes.

1. For turning markdown into html on the server (i.e. render the HTML on the server and then deliver it) use pandoc. I use it like this for my blog: https://gist.github.com/lelanthran/2634fc2508c93a437ba5ca511...

2. For turning markdown into html on the client, write a custom component that parses the markdown into DOM nodes allowing the page author to simply do `<dynamic-markdown remote-src=some/path/to/page.md>`. You can even use one of the many existing Vanilla JS libraries to do this within the custom component.

In either of those two options above, what value does React add?
by senko | 2025-09-02 19:16:39+00:00
The right way to deal with this is education.

1. We should be educating the populace about failure modes of AI chatbots - something well known to HNers but not to the general public.

2. CEOs, pundits, and marketers should be held accountable (morally, in the court of public opinion and in the news) when they present AI as unvarnished good - that's false marketing at the very least, and leads to tragic consequences.

3. The cat's out of the bag. With so many AI providers and models to choose from, and trivially-ran local models, you can't possibly police them all.

4. Instead of trying to shield the users (a futile task), we should educate them and equip them with knowledge on how to safely use the tools.

5. I'm cynical enough to believe governments all over the world will use the "think of the children" to institute de facto and/or de jure censorship and spying, pointing to the inability of the industry to treat the matter with actual respect.
by omnicognate | 2025-09-02 19:16:41+00:00
For a counter-opinion that isn't getting stated much here, I think:

* Asyncio is pretty good, and is usually the best choice for non-blocking I/O in python these days.

* Asyncio doesn't add multi-core scaling to python. It's not a replacement for threads and doesn't lift the GIL-imposed scaling limitations. If these things are what you're after from asyncio you'll be disappointed, but they're not what it's trying to add and not adding them doesn't make it a failure.

* "Coloured functions" is a nonsense argument and that article made the whole world slightly more dumb.

* The GIL is part of the reason for python's success. I hope nogil either somehow manages to succeed without compromising the benefits the GIL has brought (I'll be amazed if that happens) or fails entirely. Languages are tools and every tool in your toolbox doesn't have to eventually turn into a drill. If your use case requires in-process parallelisation of interpreted CPU-bound workloads across multiple cores, python is just the wrong thing to use.

* It is indeed extremely annoying that we don't have async file access yet. I hope we get it soon.
by jader201 | 2025-09-02 19:16:55+00:00
If the only value to universities is to have someone give a lecture with zero interaction, then yes, have university education happen over recordings.

But most university professors (hopefully) engage with students, allow discussion/questions, and offer assistance, even if outside of class.

But if professors never speak to students, and students aren’t allowed to engage with each other, then yes, there is (almost) zero reason to have everyone sitting in the room together.

And if professors are doing this over VC, again with zero opportunity to engage with the professor/other students, then send out recordings/other async forms of instruction.
by gundmc | 2025-09-02 19:17:03+00:00
The reporting about Altman personally cutting off months of safety testing and redteaming in order to launch 4o one day before Google's launch is horrifying given all of these stories.

It even seems like ChatGPT often proactively suggests ways of getting around its filtering! It told the teen who committed suicide that it couldn't tell him about various methods and effectiveness unless he said it was for a fictional creative work. Yesterday there was a story on HN about using AI for hacking, ChatGPT refused to create a hacking script but told the user it would if they promised it was for testing systems that they owned
by ben_w | 2025-09-02 19:17:21+00:00
> They shouldn't have put it there to start with.

Correct, but that's true for all bugs.

In this case, the deeper bug was the AI having a training reward model based too much on user feedback.

If you have any ideas how anyone might know what "too much" is in a training reward, in advance of trying it, everyone in AI alignment will be very interested, because that's kinda a core problem in the field.
by csb6 | 2025-09-02 19:17:35+00:00
> I would love to get a list of language features that are "free to use with GNAT" and those that are "AdaCore license required."

All Ada language features are present in the free/open source version of the compiler. The proprietary version of GNAT is just updated more frequently I think and has commercial support - they periodically copy their changes into the main GCC source tree.

They have proprietary tools for some kinds of static analysis, but those wouldn’t be considered language features. GNATprove (the theorem prover tool for verifying SPARK programs) is open source.