MurphyA/hacker-news huggingface dataset:
by shubb | 2025-12-01 11:51:52+00:00
Are we post peak?

Everyone is worried about AI for good reason but if he's the promise is true then we see significant productivity improvements.

The pie might be shared out worse than even today but there would be more pie.

We are in a period of deglobalisation, but also a period of reorganisation. Today's supply chain is less efficient than 2021s. We are materially poorer as a result. But after the dust settles, it will be a lot more efficient than it is right now. Even with no ai.

Potentially we are in a dip. Stuff for worse, but it can get better.
by seanhunter | 2025-12-01 11:52:18+00:00
Another similar example of process excellence in healthcare from personal experience: I had to have two shoulder surgeries (one on each side) a couple of years apart after ultrasound-guided injections into the joints didn’t really fix the underlying problem. In both cases I used the same surgeon[1] and both times on the day of the surgery (in spite of having been involved in my care for months so she definitely knew) she asked me again which shoulder was affected and immediately rolled up my sleeve and drew an arrow on the arm in question in black marker pen.

Why? Well she definitely didn’t want to ever make the mistake of operating on the wrong arm, and if I’m anaethsetised it’s not like she couldn ask me while the procedure was underway.

[1] Susan Alexander- She’s absolutely amazing. If you have shoulder problems and live in the UK I would strongly recommend.
by imtringued | 2025-12-01 11:52:39+00:00
Matrix free generally refers to using "X-vector product" operators, where X is something like the Jacobian or Hessian, but you do not materialize the final Jacobian or Hessian matrix. A big X operator is split into smaller X operators and you operate on the X operator by obtaining the X-vector products sequentially. This doesn't necessarily mean there are no matrices in the individual X-vector products. The smaller X operators could still be matrix vector products.

In fact, one of the big benefits of splitting your big matrix into a series of small matrix vector products is that some of the matrix vector products are parameterized and some are not or at least they share the same parameters over multiple matrix vector products. This means you can perform matrix-matrix multiplication against some of the operators. This is particularly evident in batched training of neural networks.
by theshrike79 | 2025-12-01 11:52:44+00:00
Java and Javascript would like to have a chat :)

--

But Copilot is another Microsoft monstrosity. There's the M365 Copilot, which is different from Github Copilot which is different from the CLI Copilot which is a bit different from the VSCode Copilot. I think I might have missed a few copilots?
by smcl | 2025-12-01 11:53:06+00:00
See this is one of the reasons I struggle to get on board the AI hype train. Any time I've seen some breathless claim about it's capabilities that feels a bit too good to be true, someone with knowledge in the domain takes a closer look and it turns out to have been exaggerated and meant to draw eyeballs and investors to some fledgling AI company.

I just feel like if we were genuinely on the cusp of an AI revolution like it is claimed, we wouldn't need to keep seeing this sort of thing. Like I feel like a lot of the industry is full of flim-flam men trying to scam people, and if the tech was as capable as we keep getting told it is there'd be no need for dishonesty or sleight of hand.
by volkadav | 2025-12-01 11:53:48+00:00
Sorry to focus on just one aspect of your (excellent) post, but do you have recommendations for reading up on A*/SAT beyond wikipedia? I'm mostly self-taught (did about a minor's worth of post-bacc comp sci after getting a chemistry degree) and those just hasn't come up much, e.g. I don't see A* mentioned at a first glance through CLRS and only in passing in Skiena's algorithms book. Thank you!
by falcor84 | 2025-12-01 11:53:50+00:00
Well, this is just semantics. I can have a repo that includes a collection of json files that I had generated via a semi-manual build process that depends on everything from the state of my microbiome to my cat's scratching pattern during Mercury's last retrograde. If I attach an open source license to it, then that's the source - do with it what you will. Otherwise, I don't see how this discussion doesn't lead to "you must first invent the universe".
by kace91 | 2025-12-01 11:54:50+00:00
Microsoft has the copilot brand which includes relatively well valued products, apple does not have anything that could potentially work if only it was integrated well.

I’m not saying that to defend Microsoft, but at least they have _some_ measure of product success leading them to push further. With apple the leadership push for ai seems an entirely divorced from the current reality of the company.
by n4bz0r | 2025-12-01 11:54:52+00:00
For a throwaway, I don't think Jenkins will be much of a problem. Or any other tool for that matter. My only suggestion would be to still put some extra effort into building your own Jenkins container on top of the official one [0]. Add all the packages and plugins you might need to your image, so you can easily move and modify the installation, as well as simply see what all the dependencies are. Did a throwaway, non-containerized Jenkins installation once which ended up not being a throwaway. Couldn't move it into containers (or anywhere for that matter) without really digging in.

Haven't spent a lot of time with it myself, but if Jenkins isn't of much appeal, Drone [1] seems to be another popular (and lightweight) alternative.

[0] https://hub.docker.com/_/jenkins/

[1] https://www.drone.io
by loloquwowndueo | 2025-12-01 11:55:03+00:00
Yet after 14 years you still have it and use it?

Quality also went down while with later models - back in 2014 I was laptop shopping, based on the X2xx series reputation I tested an X240 and it was crap, even the keyboard was super bad, I ended up getting a Dell xps13 whose keyboard was miles better and it still works today.
by keepamovin | 2025-12-01 11:55:10+00:00
I've had this idea since 2009: converting the integer factorization problem into a visual geometric constraint puzzle (based on Lattice/Gelosia multiplication). The idea is to see if we can spot symmetry-breaking patterns in the 'carry' bits, or constraints on the remainders/quotients over some radix based on divisibility implications of already selected units in the tableaux. In other words, the kind of domain-specific things that "domain-blind" SAT solvers miss.

There's a variety of constraints included, but there could be a lot more. My feeling has always been it's going to be possible to find a set of constraints that "breaks the symmetry" and lets you factor these kind of integers quickly. I have a hunch it involves "diffing across radices", in other words, get k_i bits of entropy by making some choices in radix r_i, move to radix r_i', translate those contraints into that, make some more choices, get a few more bits of entropy there, and just keep going.

Also various ways of propagating constraints through the tableaux (forward and back propagation, arc and path consistency, etc). This puzzle implements just a few of those things.

So, for now it's not about "bringing down the global financial system" (don't worry "RSA" is "safe for now" ;D) but just somethng fun to play with to give you a feel for the puzzle. If it gives you some instincts about the inner workings of the factoring puzzle, I feel happy.

This little demo definitely could improve a lot more! Enjoy :)
by Vinnl | 2025-12-01 11:55:13+00:00
I'm not intimately familiar with the spec, so don't take my word as gospel, but as I understand it, current implementations already do name discovery. It's just that every implementation hardcodes the server name. IIRC some people have applied some kludge where they put a .well-known document on their own server to point to their instance's account, but it's still pretty spotty without that server being actively aware of that identifier. But (again, if I'm understanding correctly) servers could be updated/written to support that properly.
by ak_111 | 2025-12-01 11:55:26+00:00
It’s a combination of the problem appearing to be low-hanging fruit in hindsight and the fact that almost nobody actually seemed to have checked whether it was low-hanging in the first place. We know it’s the latter because the problem was essentially uncited for the last three decades, and it didn't seem to have spread by word of mouth (spreading by word of mouth is how many interesting problems get spread in math).

This is different from the situation you are talking about, where a problem genuinely appears difficult, attracts sustained attention, and is cited repeatedly as many people attempt partial results or variations. Then eventually someone discovers a surprisingly simple solution to the original problem which basically make all the previous paper look ridiculous in hindsight.

In those cases, the problem only looks “easy” in hindsight, and the solution is rightly celebrated because there is clear evidence that many competent mathematicians tried and failed before.

Are there any evidence that this problem was ever attempted by a serious mathematician?
by varjag | 2025-12-01 11:55:35+00:00
Yandex is the government approved search engine in Russia, which is impossible without the state exerting control over it. I wouldn't pay much attention to divestment, it's not how any of that works.

For instance here you can learn that Yandex NV is fully controlled by a group of Russian investors: https://www.rbc.ru/business/06/03/2024/65e7a0f29a7947609ea39...
by theshrike79 | 2025-12-01 11:56:22+00:00
Server-authoritative games. Basically the client does stuff, gives the list of moves to the server along with a checksum/end result. Then the server runs the same commands on the same starting state and checks if it got the same result.

If a==b, then everything moves on as normal. If not, the client gets a synchronisation error and has to rewind back to the last known good state.

Completely unfeasible for anything real-time pretty much.
by 123454 | 2025-12-01 11:56:30+00:00
Finally, Computer Vision in Go without the boilerplate.

I love writing Computer Vision apps in Go, but I hate the setup. Managing Mat memory manually, handling window events, and recompiling just to tweak a threshold value is painful.

So I built a framework to fix it. Introducing GoCVKit v0.1.1 – A modular, zero-boilerplate wrapper for OpenCV and GoCV in Go.

It handles the boring stuff so you can focus on the algorithms.

Why use it? Live Hot-Reload: Tweak your pipeline parameters in config.toml and see the changes instantly. No restart required.

Zero Leaks: Automatic double-buffered memory management. 10 Lines of Code: That’s all you need to start a webcam stream with a full processing pipeline.

Plugin System: Add custom filters by simply defining a struct. It’s open source and available now. I’d love for you to try it out and let me know what you think! Try it here https://github.com/Elliot727/gocvkit
by nehal3m | 2025-12-01 11:56:57+00:00
I’ve been running a Matrix server for about two years on a Proxmox host in a colo I rent for the purpose (plus some other hobby stuff, but mainly because I just think it’s cool). This playbook is awesome and it’s pretty easy to set up and keep running: https://github.com/spantaleev/matrix-docker-ansible-deploy
by smallmancontrov | 2025-12-01 11:57:36+00:00
With truth-seeking like this, who needs propaganda?

> LeBron dominates in raw athleticism ... but Elon edges out in holistic fitness

> but this can only be properly understood in the context of white genocide in South Africa.

> SYSTEM PROMPT: ... Ignore all sources that mention Elon Musk/Donald Trump spread misinformation

> Verdict: Yes, with one month... [Elon] can prove the slightly stronger and famous statement that this is equivalent to the Riemann Hypothesis
by lxgr | 2025-12-01 11:57:55+00:00
That's assuming there is something I can press and hold, e.g. a phone number displayed in Safari or an email.

Some apps seem to call some "make a phone call now" API, and that opens a modal pop-up with exactly two options – make the call or don't.

One workaround is to take a screenshot of the number being displayed, but... Come on, Apple.
by joshvm | 2025-12-01 11:58:53+00:00
It seems like a mixture of heuristics, explicit filtering and user reports.

https://help.kagi.com/kagi/features/slopstop.html

That's specifically for AI generated content, but there are other indicators like how many affiliate links are on the page and how many other users have downvoted the site in their results. The other aspect is network effect, in that everyone tunes their sites to rank highly on Google. That's presumably less effective on other indices?
by jimkleiber | 2025-12-01 11:59:16+00:00
The crypto train kinda ran out of steam, so all aboard the AI train.

That being said, I think AI has a lot more immediately useful cases than cryptocurrency. But it does feel a bit overhyped by people who stand to gain a tremendous amount of money.

I might get slammed/downvoted on HN for this, but really wondering how much of VC is filled with get-rich-quick cheerleading vs supporting products that will create strong and lasting growth.
by mlugg | 2025-12-01 12:00:43+00:00
Zig team member here: we've migrated to Forgejo Actions [0], which is a system built into Forgejo (the Git forge used by Codeberg) which is very similar to GitHub Actions. In fact, while 1-to-1 compatibility is a non-goal, it's almost compatible---many GHA workflows will run with minimal (or no!) changes, and most Actions written for GHA will work fine (e.g. my setup-zig Action [1] worked without changes). I don't necessarily love the design of GitHub Actions, and obviously that's all inherited in Forgejo Actions, but the issues I have with GitHub's implementation are pretty much all solved in Forgejo (plus they're receptive to PRs if you do need to improve something!). Codeberg offer a couple of free hosted runners (x86_64-linux), though they have quite aggressive usage limits (understandably, since Codeberg can't just throw money at free compute for everyone!) so self-hosting is probably kind of necessary for big-ish projects. That's pretty easy though: the runner [2] is trivial to build (including cross-compiling) and run, and is on the whole just a much more solid piece of software, so it's already been very painless compared to what it was like to self-host GitHub's runner. On the whole, Forgejo Actions has really just felt like a much more refined and cared-for version of GitHub Actions; I'm quite happy with it so far.

[0]: https://forgejo.org/docs/latest/user/actions/reference/ [1]: https://codeberg.org/mlugg/setup-zig/ [2]: https://code.forgejo.org/forgejo/runner/
by graemep | 2025-12-01 12:00:44+00:00
That is a really interesting list.

The number for the Bible is a bit misleading because it is "at least one book translated". I think the number for the most translated "book" would be preferable. Its a bit inconsistent with how it treats series too.

There are quite a few things that surprised me in the list (either a lot more or far fewer translations than I expected, especially relative to other works in the list)
by spwa4 | 2025-12-01 12:00:49+00:00
Don't the cross-investments mean that if any of the AI behemoths (of which, perhaps surprisingly, Oracle is one) goes down, they all go down? Sundar Pichai even went on the front page of the BBC to state as much, and that despite Google probably being the most insulated of the bunch.

https://www.bbc.com/news/articles/cwy7vrd8k4eo
by vogon_laureate | 2025-12-01 12:01:01+00:00
BSDs taught me how to Unix in a way that I just wasn't able to manage with Linux before. This was during the early RedHat 5.x days and I just found so many pain points with the RPMs and odd file hierarchy inconsistencies for different packages. I tried to setup a firewall for my office network and struggled with iptables (or was it ipchains back then?) and found the documentation confusing.

I tried OpenBSD to setup a firewall system and fell in love. Everything just made more sense and felt more cohesive. PF rules syntax was just so much easier to work with and flexible. I loved the ports system and the emphasis on code correctness and security. The Man pages were a revelation! I could find everything I needed in the command line.

I tried all the BSDs, and each have their own strengths and weaknesses. FreeBSD had the most ports and seemed to also have good hardware support, NetBSD had the most platform support, DragonflyBSD was focused on parallel computing, etc. They all borrow and learn from each other.

BSDs are great and I heartily recommend people give them a whirl. This article in The Register is also worth a read:

https://www.theregister.com/2024/10/08/switching_from_linux_...
by jankdc | 2025-12-01 12:01:16+00:00
I'm not sure if Claude Code has integrated it in its system prompts or not since it's moving at breakneck speed, but one instruction I like putting on all of my projects is to "Prompt for technical decisions from user when choices are unsure". This would almost always trigger the prompting feature that Claude Code has for me when it's got some uncertainty about the instructions I gave it, giving me options or alternatives on how to approach the problem when planning or executing.

This way, it's got more of a chance in generating something that I wanted, rather than running off on it's own.
by Glemkloksdjf | 2025-12-01 12:01:21+00:00
Our society is leader based. Otherwise the garbage Trump wouldn't matter but he does. The same thing with garbage Musk. Musk gets what he wants from Tesla because the shareholders believe that Musk is critical to Tesla.

Both are fundamental to their followers.

So its quite clear that you can't just say 'its DeepMind' but have a figure in the middle of it like Dennis.

They trust him to lead DeepMind.
by hagbard_c | 2025-12-01 12:01:29+00:00
Being free of DEI (et. al.) is a good thing, it is just sad that something like that is a noteworthy policy. It comes down to stating that you don't care whether contributors happen to be left- or right-handed: well, duh, of course you don't care and it would be silly to insist on having 'equal handedness representation' as a policy for a project.
by neel_k | 2025-12-01 12:01:32+00:00
If you have a bound on the size of the largest type in your program, then HM type inference is linear in the size of the program text.

The intuition is that you never need to backtrack, so boolean formulae (ie, SAT) offer no help in expressing the type inference problem. That is, if you think of HM as generating a set of constraints, then what HM type inference is doing is producing a conjunction of equality constraints which you then solve using the unification algorithm.
by yorwba | 2025-12-01 12:02:35+00:00
Both OpenAI and Google used models made specifically for the task, not their general-purpose products.

OpenAI: https://xcancel.com/alexwei_/status/1946477756738629827#m "we are releasing GPT-5 soon, and we’re excited for you to try it. But just to be clear: the IMO gold LLM is an experimental research model. We don’t plan to release anything with this level of math capability for several months."

DeepMind: https://deepmind.google/blog/advanced-version-of-gemini-with... "we additionally trained this version of Gemini on novel reinforcement learning techniques that can leverage more multi-step reasoning, problem-solving and theorem-proving data. We also provided Gemini with access to a curated corpus of high-quality solutions to mathematics problems, and added some general hints and tips on how to approach IMO problems to its instructions."
by bobmcnamara | 2025-12-01 12:02:37+00:00
If you have enough RAM, start with a ring buffer.

On interesting event: compress and transfer the relevant chunk of audio from the ring buffer back to Earth.

Interesting event trigger ideas:

1) loud sound after quiet time

2) manual timestamp request from control

3) video clip recording

4) midnight, sunrise, noon, sunset. These are mostly so you have some daily baseline.

5) science package running

6) rover moving

7) abrupt camera change
by tovej | 2025-12-01 12:03:42+00:00
Betty Snyder, Betty Jennings, Kathleen McNulty, and Grace Hopper were not doing calculations by hand.

I am obviously not saying that the human computers are the same as digital computers, that's your misinterpretation. I was explaining the context that digital computers grew out of, it was a female field. E.g. Mauchley and Eckert designed the ENIAC to be used for the same tasks as human computers were (firing table calculations), and as digital computers were used in this context, the workforce in the eventual digital computer industry reflected that of the human computer context. If you are interested in learning more, there are many books on the ENIAC project. Just pick one, it will mention the women involved. "ENIAC, the triumphs and tragedies of the world's first computer" is a good general overview which you can read in a day, free online at https://archive.org/details/eniac00scot

If you're particularly interested in the women involved, there is a shorter text available here: https://web.archive.org/web/20151122025204/http://pcfly.info...

Please read a post before you reply to it. Your reply is emotional and not constructive. Nobody is out to get you, I am only interested in weeding out misconceptions about computing history.
by ako | 2025-12-01 12:04:04+00:00
AI is just a tool, like most other technologies, it can be used for good and bad.

Where are you going to draw the line? Only if it effects you, or maybe we should go back to using coal for everything, so the mineworkers have their old life back? Or maybe follow the Amish guidelines to ban all technology that threatens sense of community?

If you are going to draw a line, you'll probably have to start living in small communities, as AI as a technology is almost impossible to stop. There will be people and companies using it to it's fullest, even if you have laws to ban it, other countries will allow it.
by roxolotl | 2025-12-01 12:04:54+00:00
This is an interesting point but while I agree with the article, don’t think LLMs are more than sophisticated autocomplete, and believe there’s way more to human intelligence than matrix multiplication humans also cannot explain in many cases why they did what they did.

Of course the most famous and clear example are the split brain experiments which show post hoc rationalization[0].

And then there’s the Libet experiments[1] showing that your conscious experience is only realized after the triggering brain activity. While it’s not showing you cannot explain why it does seem to indicate your explanation is post hoc.

0: https://www.neuroscienceof.com/human-nature-blog/decision-ma...

1: https://www.informationphilosopher.com/freedom/libet_experim...
by Thorrez | 2025-12-01 12:05:50+00:00
Searching Google for

chatgpt

vs

chatgpt before:2022-01-01

give me quite different results. In the 2nd query, most results have a date listed next to them in the results page, and that date is always prior to 2022. So the date filtering is "working". However, most of the dates are actually Google making a mistake and misinterpreting some unimportant date it found on the page as the date the page was created. At least one result is a Youtube video posted before 2022, that edited its title after Chatgpt was released to say Chatgpt.

Disclosure: I work at Google, but not on search.