MurphyA/hacker-news huggingface dataset:
by dwrensha | 2025-08-29 12:00:37+00:00
> David Renshaw recently gave a formal proof in Lean that the triakis tetrahedron does have Rupert's property

That's me!

This result appears to be significantly harder to formalize.

Steininger and Yurkevich's proof certificate is a 2.5GB tree that partitions the state space into 18 million cells and takes 30 hours to validate in SageMath.

Formalizing the various helper lemmas in the paper does seem achievable to me, but I suspect that applying them to all of the millions of cells as part of a single Lean theorem could present some significant engineering difficulties. I think it'd be a fun challenge!

If that turns out to be infeasible, an alternate approach might be: we could write a Lean proof that the 2.5GB tree faithfully encodes the original problem, while still delegating the validation of that tree to an external SageMath process. Such a formalization would at least increase our confidence that there are no math errors in the setup. A similar approach was taken recently by Bernardo Subercaseaux et al in their recent paper where they formally verified a SAT-solver encoding for the "empty hexagon number": https://arxiv.org/abs/2403.17370
by varispeed | 2025-08-29 12:00:47+00:00
You also need to state your background somehow and at what level you want the answer to be. I often found LLM would give answer that what I ask is too complex and would take months to do. Then you have to say like ignore these constraints and assume I am already an expert in the field, outline a plan how to achieve this and that. Then drill down on the plan points. It's a bit of work, but its fascinating.

Or it would say to do X it involves very complex math, instead you could (and proceeds with stripped down solution that doesn't meet goals). So you can tell it to ignore the concerns about complexity and assume that I understand all of it and it is easy to me. Then it goes on creating the solution that actually has legs. But you need to refine it further.
by nbaugh1 | 2025-08-29 12:01:27+00:00
For me, on small personal projects, I can get a project to a point in about 4 hours where previous to new AI tools it would’ve taken about 40. At work, there is a huge difference due to the complexity of the code base and services. Using agents to code for me in these cases as 100% been the loop of iterating on something so often, I would’ve been better off with a more hands on approach, essentially just reviewing PRs written by AI.
by acdha | 2025-08-29 12:02:30+00:00
As others have pointed out there are multiple implementations of XSLT, but I’d also argue that this situation seems like a decent argument in favor of that policy. If everyone is using a single implementation then in practice that implementation is the standard and things like Hyrum’s law become serious considerations.

XSLT is grandfathered in from the early days of the web, and while it’s turned out better than Microsoft exposing random COM interfaces which even Windows developers hated it’s still something of a cautionary example of a feature which never really caught on but browser developers have to support decades later or be willing to break a modest number of sites, some relatively important in particular niches like government information. I think of what happened with WebSQL as a reaction to the maintenance costs of a decade earlier.
by somenameforme | 2025-08-29 12:03:26+00:00
I mostly agree, but I'd argue that this is largely because of funny money. Check out this great site. [1] The event it's alluding to is the end of Bretton Woods, which is the point that the government completely unrestricted in their ability to 'print money'. In an economy it may or may not be true that money trickles down, but it's indisputable that it gushes upward. And so each time the government dumps trillions of dollars into the economy, that money makes its way straight to the top in very rapid fashion.

Next thing you know you have people and companies that literally have more money than they know what to do with. And then government and industry become increasingly incestuous as politicians filter money to various companies while in office, and then those companies not only stuff their election coffers full of money, but then have cushy 7+ figure 'advisory' roles for these politicians, or their inner circle, once they leave office - sometimes not even waiting for that. And then the government ends up printing endless amounts of money to keep this businesses afloat after they come crashing down to their own incompetence, completely wrecking the natural process of progression over time. All the while the stock market continues to reach record highs even in the midst of an economy destroying epidemic simply because it's all fake and driven on endless speculation, backed by endless injections of funny money.

And then on top of all of this you have various meta-effects. For instance when you live in an economy without much inflation or deflation, it's practically impossible to lower wages simply because people won't accept that. But in an inflationary economy? Somebody might even be happy about earning 25% more than they were in 2020, when in reality that means they've actually taken a pay cut thanks to inflation. And inflation is driven by the excesses of funny money.

And an inflationary society also strongly incentivizes the hoarding of things which, in turn, drives rent seeking behavior. Your things become worth more over time, but money becomes worth less over time. So you want to accumulate as many things as you can and rent access to them. Whereas in a stable or deflationary economy, things remain a comparable cost or even become worth less over time - so there's less motivation to hoard things and more motivation to hoard money.

[1] - https://wtfhappenedin1971.com/
by dmatech | 2025-08-29 12:03:40+00:00
This is why it's absolutely essential to always be aware of which types are value types in the .NET type system. Attempts by either users or the designers to conflate or unify them are ill-conceived. The nullability semantics could have been kept consistent if they went all the way back to the beginning of the CLR and did it that way, but this would have not been consistent with Java's JVM and type system (which they were trying to mimic).

That said, we already have value types like System.Int32 which inherit from System.ValueType (an abstract type) which inherits from System.Object (a non-abstract reference type), so things are already a bit weird.
by throw0101c | 2025-08-29 12:04:05+00:00
> I thought /var/tmp is for applications while /tmp is for the user.

/tmp is for stuff that is 'absolutely' temporary, in that on many/most systems it is nuked between reboots. /var/tmp is 'relatively' temporary in that applications can put stuff there that they're working on, but if there is a crash, the contents are not deleted and can be recovered across reboots.
by imiric | 2025-08-29 12:04:16+00:00
Not gatekeeping, just pointing out that they're different activities with very different experiences. What you're talking about and what the article is talking about are different things.

When using ML tools you have no deep understanding of the behavior of the program, since you don't understand the generated code. If you bother to review the code, that is a huge context switch from anything you were doing previously. This doesn't happen during deeply focused programming sessions.

You may have been a software engineer for decades without ever experiencing the programming flow state. I'm not passing judgement.
by logicchains | 2025-08-29 12:05:15+00:00
HFTs competing with each other at market making lower spreads; the cost retailers/institutions need to pay to enter a position. Prior to algorithmic trading, you might need to pay a whole percentage point or more (100 basis points), now spreads on the most popular products are so tightly quoted that it can cost less than 1 basis point (0.01%) to enter a position.
by doovd | 2025-08-29 12:05:19+00:00
It's a common rhetoric from someone who has no clue about financial markets (the person you replied to).

Suppose you want to invest in S&p500 so you want to buy the ETF. Someone like Jane Street can create sell you this ETF, and take care of the risk that comes along with it. For example, the price they sell you this ETF should take into account the pricing of underlying stocks. While it sounds trivial, doing this profitably (and therefore sustainably) is a tough job. And doing it competitively to offer you a good price on it is an even tougher job.
by nbaugh1 | 2025-08-29 12:05:52+00:00
Greenfield development of small web apps. I’m familiar enough with everything that I can get something up and running on my own, but I don’t do it regularly so I need to read a lot of docs to be up to date. I can describe the basic design and requirements of an app and have something like Claude Code spit out a prototype in a couple of hours
by visarga | 2025-08-29 12:06:32+00:00
I think there is amazing signal inside the chat logs. Every idea or decision taken can be analyzed in hindsight 20 messages later, or days later. Eventually a feedback signal or outcome lands back in the chat logs. That is real world idea validation. Considering the hundreds of millions of users and their diverse tasks that collect across time - this is probably the most efficient way to improve AI. I coined it the human-AI experience flywheel.

To make it respect user privacy I would use this data for training preference models, and those preference models used to finetune the base model. So the base model never sees particular user data, instead it learns to spot good and bad approaches from feedback experience. It might be also an answer to "who would write new things online if AI can just replicate it?" - the experience of human-AI work can be recycled directly through the AI model. Maybe it will speed up progress, amplifying both exploration of problems and exploitation of good ideas.

Considering OpenAI has 700M users, and worldwide there are probably over 1B users, they generate probably over 1 trillion tokens per day. Those collect in 2 places - in chat logs, for new models, and in human brains. We ingest a trillion AI tokens a day, changing how we think and work.
by esrauch | 2025-08-29 12:06:56+00:00
The reason is that the uniform distribution is very rare. Nearly no real world scenario were something is equally likely to be the values 2, 0 and -2, and where it's literally impossible to be -2.01. It exists but it's not the normal case.

In noisy sensors case there's some arbitrary low probability of them being actually super wrong, if you go by true 10^-10 outlier bounds they will be useless for any practical use, while the 99% confidence range is a relatively small rent.

More often you want some other distribution and say (-2, 2) and those are the 90th percentile interval not the absolute bounds, 0 is more likely than -2 and -3 is possible but rare. It's not bounds, you can ask you model for your 99th or 99.9th percentile value or whatever tolerance you want and get something outside of (-2,2).
by dn97 | 2025-08-29 12:07:13+00:00
the premise here is that market makers and arbitrageurs are crucial for efficiently allocating capital. enabling sellers to sell to the highest bidder and buyers to buy from the cheapest vendor means less capital wasted(?)

in my experience Jane Street make no attempt to defend the financial system; such societal benefits are obvious or implicit.

whether you (or they!) really buy that is irrelevant
by acdha | 2025-08-29 12:07:35+00:00
> Apparently, GNOME bureaucracy is holding up the processing the application of a new maintainer for over a month now.

This wording seems unjustly negative. You’re talking about software which is shipped in every browser, all Linux distributions, and bundled in a ton of languages. A short delay doesn’t seem unwarranted for key bits of infrastructure.
by sltr | 2025-08-29 12:07:37+00:00
When I go to a retail store, my primary emotion is empathy for the workers: I think, "sorry you have to stand here for 8 hours and listen to entitled upper middle class customers". Sometimes at the grocery store, if there's no bagger I'll start bagging my own groceries instead standing there waiting for the cashier to do it. Gets me out of there quicker, and they're often surprised in a grateful way.

Love your neighbor as yourself.
by sigmoid10 | 2025-08-29 12:07:37+00:00
The are valued at $170 Billion. Not quite the same as, but in same order of magnitude as OpenAI - while having only a single digit percent fraction of active users. They probably need to prepare for the eventual user data sellout, as it is becoming increasingly more obvious that none of the big players has a real and persistent tech leadership anymore. But millions and millions of users sharing their deepest thoughts and personal problems is gonna be worth infinitely more than all the average bot bullshit written on social media. That's also why Zuck is so incredibly desperate to get into the game. It's not about owning AI. It's about owning the world's thoughts and attention.
by rimbo789 | 2025-08-29 12:07:49+00:00
You got there in the end. Hiring people is a necessary evil and ai allows companies to massive reduce the necessity of that evil. Having done budgeting and forecasting for a wide range or organizations companies will do anything to avoid hiring an employee. I’ve seen companies spend 3x what an employee would cost just to avoid the increased headcount.

The forces of capital do not want to share a single penny and are solely focused on getting to a place of rent.
by bdd8f1df777b | 2025-08-29 12:07:56+00:00
Let's say the upstream server is apple.com. The TLS handshake is always performed by the real apple.com servers, and the ShadowTLS server is only a middle man forwarding raw TCP contents.

If both sides are ShadowTLS (client & server) holding the same key, they will stealthily switch to a different encryption protocol after the handshake, disregarding the TLS key exchange. The TLS handshake is a facade to fool the deep packet inspection of the censor.

In all other cases, such as the censor actively probing the ShadowTLS server, the server will keep forwarding the encrypted traffic to apple.com without anyway to decrypt it (it's not a MitM proxy). To the active prober, it is just apple.com all the way.
by trklausss | 2025-08-29 12:08:16+00:00
You can always work with backports! It's the way Debian has to bring more recent packages to older stable versions.

https://backports.debian.org/Instructions/

If I'm not mistaken, repo is already included by default, so you just need:

''' # apt install -t trixie-backports <package> '''

This will install backported package _and_ dependencies, so you will be good to go :)
by jibal | 2025-08-29 12:08:22+00:00
> Everyone keeps harping on type safety, but it just doesn't play out in reality.

If you ignore the vast number of cases where it does, and cherry pick an extraordinarily non-representative example like the Linux kernel.

> This is just laughable. Clearly you have extremely little experience with Python.

Or you have extremely little experience with the use cases where it applies, extremely little knowledge of the ongoing effort by the Python developers to address it, and think that ignorant mocking is an argument.
by Bender | 2025-08-29 12:08:29+00:00
I only know how to do comments vs submissions in uBlock

news.ycombinator.com##tr.athing.comtr:has(a.hnuser):has-text(/\bUsername\b/)

And then there are topics themselves

# Filter some topics # top (title / url) news.ycombinator.com##tr.athing span.titleline > a:has-text(/(Elon|lockchain)/):upward(tr) # bottom (stats / comments) news.ycombinator.com##tr.athing span.titleline > a:has-text(/(Elon|lockchain)/):upward(tr) + *

But I'm sure it could be done in uBlock, guess I need to play around with it. This removes the subline which would indicate something is up but I need to encompass the two rows. It feels like there should be a class that spans the two rows but I am awful at this.

news.ycombinator.com##tbody > tr#bigbox > td > table > tbody > tr:has-text(username)
by ethersteeds | 2025-08-29 12:09:02+00:00
As I understand it, they forked years ago when btrfs was very much not ready to be used for production NAS storage. Their value prop was they took it and added lots of their own special patches that they claimed made it highly dependable.

Over time their advantage has eroded as upstream has caught up, to the point that it looks ridiculously out of date today.
by somenameforme | 2025-08-29 12:09:05+00:00
Grok also happily answers. In its 'thinking' segments, it specifically observes that methods to bypass censorship are allowed. Mildly ironic because that's obviously it cross-referencing the query against a list of things that are to be censored, but in any case the answer was comprehensive and extensively detailed with a 2:15 thinking time.
by vessenes | 2025-08-29 12:09:28+00:00
Terrible, terrible leadership at the top of the AI org. Plus a fundamental commitment to being a 'product first' company.

This same commitment would be why I wouldn't count them out on the AI side, btw. It's not clear that a private internal foundation model is any kind of required competitive moat. It's also not clear that having one is useless, and all the cool kids do have one or want one, but from a product view it might be that integrating makes sense.

Llama 4 (a terrible release) shows also that making such a model is still really hard. There are not enough ML leads at the pointy tip of the spear to support even 10 high quality foundation model teams globally.

If you have billions of dollars in cash and you are secure in your customer base, and you don't believe AGI liftoff will happen or change your business model, maybe you work out the kinks on product integration now using best in breed providers, not getting locked in on one of them, keep spending 1/10 to 1/100th to stay relevant and on it internally, use your incredibly powerful silicon buying power to get a next gen version of TPUs done, and wait until you know for sure you can spend under $10bn in cash on getting a great proprietary model done, one that you are certain will serve your needs.

Also this will give you time to get better leadership in the AI org.

Upshot - I think it's a mix of reasons, but not fatal, I'm not sure being slow erodes their product customer base, personally I'd like much better and more private AI out of Apple ASAP. We'll see what we get. I predict they'll move internal by 2031.
by Crestwave | 2025-08-29 12:09:44+00:00
Small correction, a significant amount of Chinese migrants are from Fujian, which borders Guangdong. You can usually tell from the language spoken—Fujian descendants speak Hokkien while Guangdong descendants speak Cantonese, though it's not a hard rule with the regions being adjacent, of course.

In countries like Malaysia, it seems to be an even mix of both but in others like Philippines 90% are actually from Fujian.
by scott_w | 2025-08-29 12:10:02+00:00
> If a human being talked confidently about something that they were just making up out of thin air by synthesizing based (consciously or unconsciously) on other information they know you wouldn’t call it “hallucination”: you’d call it “bullshit”.

I'd recommend you watch https://www.youtube.com/watch?v=u9CE6a5t59Y&t=2134s&pp=ygUYc... which covers the topic of bullshit. I don't think we can call LLM output "bullshit" because someone spewing bullshit has to not care about whether what they're saying is true or false. LLMs don't "care" about anything because they're not human. It's better to give it an alternative term to differentiate it from the human behaviour, even if the observed output is recognisable.
by sarchertech | 2025-08-29 12:10:13+00:00
The problem with those quotes is the lack of definition of “quality”. Machine woven cloth in many ways is better because of consistency and uniformity.

If your goal is to make 1000 of the exact same dress, having a completely consistent raw material is synonymous with high quality.

It’s not fair to say that machines produced some kind of inferior imitation of the handmade product, that only won through sheer speed and cost to manufacture.
by js8 | 2025-08-29 12:11:10+00:00
This is what HasanAbi mentioned the other day. Betting on AI to do a job (especially if it fails to replace it) is a double economic whammy. You get rid of original people who did the job, and then you don't have funding for other things (also includes people) because you need to recover the AI costs.

Collective delusion about AI (or similar craze) can be large enough to actually tank the economy.
by trklausss | 2025-08-29 12:11:57+00:00
That is true, at least for laptops that came to market after the respective Debian release.

You can however get all stability of a released version with newer packages if you use stable+backports. This would give you a stable system, and allow you to upgrade selected packages to newer versions. This can be tedious, so running testing is also possible.

And well, overall, you can also install other distributions that are bleeding-edge (Arch based?). That's why I like about the distro ecosystem :)
by ubermonkey | 2025-08-29 12:12:05+00:00
That's not really true.

Speaking in a meeting, or delivering a talk in a larger context, often works better with visuals. Delivering information in this way is not "pandering" to people who don't or won't read a detailed paper. They're different contexts with different goals.

Before Powerpoint, having any kind of visual aid to a talk was incredibly onerous. You had to print up transparancies, or literally have SLIDES made, and the whole thing was just an enormous pain in the ass.

The PROBLEM here isn't Powerpoint, or the existence of visuals during a talk. It's that humans are bad at communicating generally, and that the use of slides during a talk is something many folks absolutely do NOT understand or do well.

You've been to a talk where the speaker basically just reads the slides, right? That's pointless. What you want is slides that compliment and amplify what's actually being said, not duplicate it. You also want slides that "scan" well -- if your audience has to pause and read a 150 words on a slide, you've fucked up. (DoD and defense industry presentations are INFAMOUS for this, btw.)
by troad | 2025-08-29 12:12:15+00:00
Two weeks left in the sub to figure it out, but I'm not yet sure. I was never all in on all the tooling, I mostly used it as smart search (e.g. ImageMagick incantations) and for trivial scripting that I couldn't be bothered writing myself, so I might just stick to whatever comes with Kagi, see if that doesn't cover me.
by asib | 2025-08-29 12:12:16+00:00
Yes, it's honestly a joke.

Zelle limits the amount you can send per day, starting at $500, so you can't even necessarily pay your rent in one go the first month.

With Chase, I don't have the ability to do ACH transfers to accounts I don't own (I hear other banks allow free ACH transfers), so if Zelle limit is too low, my only option would be a paid wire...
by twoquestions | 2025-08-29 12:12:36+00:00
I 90% agree with you, though Apple did stand up to the FBI some years ago. The US gov't at least is much more restricted on what data it can collect and act on due to the 4th Amendment among other laws, and as another commenter said Apple can't blackbag me to El Salvador.

Apple/FBI story in question: https://apnews.com/general-news-c8469b05ac1b4092b7690d36f340...
by mexicocitinluez | 2025-08-29 12:12:53+00:00
> The correct way is to treat it as a somewhat autistic junior dev: give it examples and process to follow, tell it to search the web, read the docs, how to execute tests. Especially important is either directly linking or just copy pasting any and all relevant documentation.

Like "Translate this pdf to html using X as a templating language". It shines at stuff like that.

As a dev, I encounter tons of one-off scenarios like this.