MurphyA/hacker-news huggingface dataset:
by zerkten | 2025-06-14 02:32:22+00:00
Interesting app. Planning, expenses, and keeping people on track during the trip are some ways I'd think about using the app. TripIt is what we use for the latter. All things get recorded there starting with flights that bookend the trip. That's particularly low friction to get going. You know what you need to fill in next whether it's transport or accommodation.

Your app seems to appeal to the planner type of personality making it too high friction for me. I like to plan trips, but this approach is just way too heavyweight. If I was to suggest an approach that might augment what you have while being structured to an extent (I don't love the shared doc approach) is to allow someone to sketch an itinerary on a map. Then zoom to each general location and do searches for known things to add. Also allow the option to search for general things like restaurants in the vicinity. Bringing in this Google Maps-esque approach would help me.
by chenquan | 2025-06-14 02:34:02+00:00
Today, with great excitement, we proudly introduce a revolutionary update to the ArkFlow stream processing engine: full support for Python processors! This is not just a simple feature iteration; it marks a solid step towards more intelligent, user-friendly, and powerful real-time data processing. We are keenly aware of Python's immense influence and its vast ecosystem in the fields of artificial intelligence and machine learning. Now, with ArkFlow, you can seamlessly integrate all of this into high-performance, real-time stream processing pipelines.
by Noelia- | 2025-06-14 02:37:05+00:00
The first time I saw a model like this, I assumed that randomness would eventually balance things out. But that is not what happened. The rules were completely fair, yet the system still ended up producing significant inequality.

That stuck with me. Sometimes, all it takes is time and a bit of randomness for imbalance to emerge on its own. Inequality does not always come from someone doing something wrong. It can simply be the long-term result of randomness playing out. So the real question is, once we understand that, what do we do with it?
by inamberclad | 2025-06-14 02:37:45+00:00
I'm frustrated that they push their product on undergrad engineering classes so heavily. Except for a few poorly taught weeks of C++, most of my classmates never leaned anything else. Admittedly, Matlab is a very good product for modeling and learning about controls, but they use this advantage to make sure all the fresh undergrads only know how to program in their product.
by michae2 | 2025-06-14 02:43:01+00:00
Something I’ve wondered about Datalog is whether integers can be added to the language without losing guarantees about termination of query evaluation. It seems like as soon as we add integers with successor() or strings with concat() then we can potentially create infinite relations. Is there a way to add integers or strings (well, really basic scalar operations on integer or string values) while preserving termination guarantees?

This bit at the end of the article seems to imply it’s possible, maybe with some tricks?

> We could also add support for arithmetic and composite atoms (like lists), which introduce some challenges if we wish to stay “Turing-incomplete”.
by safety1st | 2025-06-14 02:47:10+00:00
The fundamental tradeoff a lot of consumer software seems to be based on these days is they will offer you stuff you want (i.e. be feature rich), in exchange for stuff you don't (i.e. steal your data, show you ads). Whereas a FOSS author is a lot more likely to take the "do one thing well" approach.

What I settled for was an approach where I try to minimize the use of commercial software in my personal life, but in my business if we need what the commercial software does we'll just license it and get on with things. For the most part in my life I don't really NEED some feature or another, it might be nice to have, but with any type of commercial software or service there's always going to be the risk that they'll push some update that shoves ads down my throat or introduces microtransactions or something, so I'm OK to just go without and use the FOSS alternative.

In business though, we'll be at a competitive disadvantage if I force everyone to use only FOSS. There are many times where I've looked at the open source equivalent of some big SaaS and it was just going to be more work to set up and maintain a less featureful open source equivalent. So, I'm more inclined to do a deal with the devil because at the end of the day our time and resources need to be focused elsewhere.
by maegul | 2025-06-14 02:47:11+00:00
> Ironically, the best answer to many of the article's suggestions (thousands rather than millions, easy to modify, etc.) is to write your own software with LLMs.

Not sure exactly irony you mean here, but I’ll bite on the anti-LLM bait …

Surely it matters where the LLM sits against these values, no? Even if you’ve got your own program from the LLM that’s yours, so long as you may need alterations, maintenance, debugging or even understanding its nuances, the nature of the originating LLM, as a program, matters too … right?

And in that sense, are we at all likely to get to a place where LLMs aren’t simply the new mega-platforms (while we await the year of the local-only/open-weights AI)?
by AdieuToLogic | 2025-06-14 02:47:46+00:00
> What I was curious about was applying a GC language to a use case that must have extremely low latency. It seems like an important consideration, as a GC pause in the middle of high-frequency trading could be problematic.

Regarding a run-time environment using garbage collection in general, not OCaml specifically, GC pauses can be minimized with parallel collection algorithms such as found in the JVM[0]. They do not provide hard guarantees however, so over-provisioning system RAM may also be needed in order to achieve required system performance.

Another more complex approach is to over-provision the servers such that each can drop out of the available pool for a short time, thus allowing "offline GC." This involves collaboration between request routers and other servers, so may not be worth the effort if a deployment can financially support over-provisioning servers such that there is always an idle CPU available for parallel GC on each.

0 - https://docs.oracle.com/en/java/javase/17/gctuning/parallel-...
by fakedang | 2025-06-14 02:48:09+00:00
Apotheker is basically everything wrong with the EU non-startup tech scene today. Not him personally per se, but you see a lot of characters like him on a much more regular basis in EU companies than you will find in US companies.

These kinds of folks only seem to fail upwards in the EU, whereas in the US, they would have been laughed out.
by acdha | 2025-06-14 02:49:28+00:00
Most of those developers were looking for revenue, though, and there’s a really wicked network effect rewarding the popular platforms. By the time the first WebOS device launched in 2009 Apple had already shipped tens of millions of iPhones and Android was growing, too. By the time decent WebOS hardware was available, there just weren’t many developers looking to target a user base at least an order of magnitude smaller – even Android struggled because not as many users were willing to actually buy software.
by oxygen_crisis | 2025-06-14 02:49:37+00:00
There was a Lenovo and an ASUS and an Acer in between but those all went in the graveyard pile before their second year was up and I had to keep resorting to the 2011 Macbook.

And that's counting the extra ~year I got out of the Lenovo after having to replace the fans.

Having user serviceable parts is nice but having parts that last 14 years is better. If there was a brand that did both, that's what I'd buy.
by kriro | 2025-06-14 02:49:54+00:00
I love Prolog but haven't used it in ages. I should really give it a go again. Whenever I used it my brain needed some adjustment time and then switched to declarative mode. It's a really unique experience and hard to describe. It was also my first contact with immutable data.

Is implementing a Kanren and embedding it as suggested by the author really the recommended approach? Back in the day I used Sicstus mostly but tried to use SWI whenever possible (because I'm a FLOSS guy at heart). I'm asking because we went the opposite direction and used Prolog as the first language and called Java or C when needed (io, GUI). I'd describe the result as a "hot mess".

Random note: "Art of Prolog" and "Craft of Prolog" remain two of my favorite CS books to this day.

I'd be curious what the "state of the art" is these days and would love ve to hear from some folks using Prolog in the trenches.
by minimaxir | 2025-06-14 02:51:13+00:00
They aren't getting increasingly yellow (I don't think the base model has been updated since the release of GPT-4o Image Generation), but the fact that they are always so yellow is bizarre and I am still shocked OpenAI shipped it knowing that effect exists, especially since it has the practical effect of instantly being able to clock it as an AI image generation.

Generally when training image encoders/decoders, the input images are normalized so some base commonality is possible (when playing around with Flux Kontext image-to-image I've noticed subtle adjustments in image temperature), but the fact that it's piss yellow is baffling. The autoregressive nature of the generation would not explain it either.
by rex_gallorum2 | 2025-06-14 02:51:49+00:00
There was a connection between deindustrialization in American cities (and the crappy property market in the 80s) and the music and arts scenes in the 80s and 90s. It was relatively cheap and easy to set up studios, galleries, music venues, or just squat in empty industrial buildings. Property owners were happy to have someone to keep the lights on and keep the bums out. Stages and makeshift bars were built out of scraps, and bands were booked, and people came. Music scenes used to require physical spaces (and arguably still do) to breathe and take shape.

I've watched interviews in which veteran musicians from one city in Texas describe how things developed in the 80s - it was all made possible by rock bottom rents and tons of empty warehouse space. I think the situation was similar across much of the US. Space was cheap enough to allow for low-profit activities and businesses to take root. The stakes were very low compared to today.

An analogous situation emerged in other places (in part for different reasons) such as the former East Berlin. I would guess similar circumstances also emerged in the UK around the same time - perhaps someone here can confirm.
by esafak | 2025-06-14 02:51:55+00:00
Shojaee et al. (2025) report that Large Reasoning Models (LRMs) exhibit "accuracy collapse" on planning puzzles beyond certain complexity thresholds. We demonstrate that their findings primarily reflect experimental design limitations rather than fundamental reasoning failures. Our analysis reveals three critical issues: (1) Tower of Hanoi experiments systematically exceed model output token limits at reported failure points, with models explicitly acknowledging these constraints in their outputs; (2) The authors' automated evaluation framework fails to distinguish between reasoning failures and practical constraints, leading to misclassification of model capabilities; (3) Most concerningly, their River Crossing benchmarks include mathematically impossible instances for N > 5 due to insufficient boat capacity, yet models are scored as failures for not solving these unsolvable problems. When we control for these experimental artifacts, by requesting generating functions instead of exhaustive move lists, preliminary experiments across multiple models indicate high accuracy on Tower of Hanoi instances previously reported as complete failures. These findings highlight the importance of careful experimental design when evaluating AI reasoning capabilities.
by perching_aix | 2025-06-14 02:52:30+00:00
I largely agree, and upon reading this article is sadly also in that camp of applying this perspective to be dismissive.

However, I find it incredibly valuable generally to know things aren't magic, and that there's a method to the madness.

For example, I had a bit of a spat with a colleague who was 100% certain that AI models are not only unreliable because from a human perspective, insignificant changes to their inputs can cause significant changes to their outputs, but because, in their idea, they were actually random, in the nondeterministic sense. That I was speaking in hypotheticals when I took an issue with this, as he recalled my beliefs about superdeterminism, and inferred that "yeah if you know where every atom is in your processor and the state they're in, then sure, maybe they're deterministic, but that's not a useful definition of deterministic".

Me "knowing" that they're not only not any more special than any other program, but that it's just a bunch of matrix math, provided me with the confidence and resiliency necessary to reason my colleague out of his position, including busting out a local model to demonstrate the reproducibility of model interactions first hand, that he was then able to replicate on his end on a completely different hardware. Even learned a bit about the "magic" involved myself along the way (that different versions of ollama may give different results, although not necessarily).
by skissane | 2025-06-14 02:52:44+00:00
> If enumerate actually works as advertised, then it can't ever find unenumerated. Because if (enumerate N) is unenumerated, then ((enumerate N) N) will hit infinite recursion and therefore doesn't return a boolean.

Okay, but if we take the position that only non-halting (for all inputs) programs represent functions over N, if your program “unenumerated” never halts for some N, it doesn’t represent a function, so your argument isn’t a case of “using the enumeration of all functions to produce something which doesn’t belong to the enumeration”

Obviously an enumeration of all computable functions isn’t itself computable. But if we consider Axiom CompFunc “if a function over N is computable then it exists” (so this axiom guarantees the existence of all computable functions, but is silent on whether any non-computable functions exist) and then we consider the additional Axiom CountReals “there exists a function from N to all functions over N”, then are those two axioms mutually inconsistent? I don’t think your argument, as given, directly addresses this question
by hackinthebochs | 2025-06-14 02:54:37+00:00
LLMs are modelling the world, not just "predicting the next token". They are not akin to "stochastic parrots". Some examples here[1][2][3]. Anyone claiming otherwise at this point is not arguing in good faith. There are so many interesting things to say about LLMs, yet somehow the conversation about them is stuck in 2021.

[1] https://arxiv.org/abs/2405.15943

[2] https://x.com/OwainEvans_UK/status/1894436637054214509

[3] https://www.anthropic.com/research/tracing-thoughts-language...
by eqvinox | 2025-06-14 02:54:48+00:00
Technical/pedantic answer: you can store a 'normalized' hashed form of the password, e.g. before hashing it, convert it to all lowercase, replace all digits with 0, sort the characters, … and then do the same to the new password before hashing it, so a whole bunch of stuff will compare "equal".

Practical/actual answer: this is stupid either way.
by Leo-thorne | 2025-06-14 02:55:17+00:00
A lot of mentors helped me when I was completely lost, and at that stage I really had nothing to give back. Later, I just focused on doing my best, trying to make sure what they taught me actually got used, so their time wasn’t wasted. Every now and then I share some progress with them, and they always seem happy to hear it. And now I try to help the next group of people who are going through the same phase I once did.
by wlesieutre | 2025-06-14 02:55:34+00:00
> Users are there to consume videos, photos, articles - not to stare at your buttons

But if I want to use the buttons, that necessitates that I see the buttons first in order to use them. If I don't need to see a button, the button probably shouldn't be there at all.

It's not the worst design I've ever seen, but it does feel like they've swung a bit too far in the "users want to focus on the content" direction. The tools to interact with the content are also an important part of the interface and if you can't see them clearly they're not very usable.
by arduanika | 2025-06-14 02:56:15+00:00
This title is pretty bait-and-switch, enough so that @dang might consider swapping it out for something more accurate. Only the first paragraph is about job trends per se. The rest is making a case for repealing the changes to Section 174, and it basically reads like a lobbyist's copy. I am weakly in agreement with the author on this topic, but the title should probably reflect the actual meat of the article.
by fakedang | 2025-06-14 02:58:09+00:00
Can we talk about the LibreOffice UI/UX? It's shit. It doesn't feel like MS Office, but like some Frankenstein's version of it. I would much rather prefer if OnlyOffice were pushed as the open source standard for office apps instead of Libre. OnlyOffice mirrors everything that MS Office offers, the only difference being the lack of VBA coding (instead replaced by JS coding).
by jfengel | 2025-06-14 02:59:30+00:00
Tax cuts are always made more palatable by pretending they will expire. That way the total effect on the debt is minimized.

Usually Congress just renews them anyway, and it gets less attention than the original cuts. It's just preserving the existing incentive, and handwave over the fact that it still affects the deficit projections.

The relationship between taxes and the deficit is complicated, but it's not that complicated. Deficit equals income minus expenditure. You can tell people that tax cuts pay for themselves, and they do seem content to keep believing it.
by Terr_ | 2025-06-14 03:00:02+00:00
> Do you say similar stuff when someone talks about the motivations of a character in fiction?

Depends, are we faced with the same problem where a disturbingly-large portion of people don't know the character is fictional, and/or make decisions as if it were real?

If that's still happening, then yes, keeping our unconscious assumptions in check is important.
by dbetteridge | 2025-06-14 03:01:23+00:00
Follow up question from someone who's mostly forgotten his university physics.

Do photons actually exist, in the traditional sense of physical matter.

Or are they just a convenient short hand to describe the transfer of energy via waves in the fabric or space time, if they dont experience the universe when passing through it but only when interacting with matter and matters "dents" in space-time.
by yieldcrv | 2025-06-14 03:03:47+00:00
This is the second post I've seen on HN lobbying hard for full Section 174 restoration (repealing the bad version, putting back in full engineering salary deductions) while completely ignoring that this is in the giant budget bill that already passed the House and is in the Senate hands

I feel like its partially ignorance, and partially trying to distance themselves from benefitting from this law

Kind of annoying. This country has a class system. Wish people would just stop pretending and acknowledge where they're at, everyone for Section 174 updates will benefit from the budget and tax bill.
by andrewaylett | 2025-06-14 03:04:46+00:00
You can store a normalised form -- so if the password is `PaSsWoRd` and the user tries to change it to `pA55wOrD`, a normalisation that lower-cases, turns 1 and i into l, turns 2 and 5 into s, and turns 4 into a, would normalise both to `password`.

Or if you want a slightly more convoluted mechanism, when someone changes their password you have both in plain-text and you can take a copy of the old password at that point -- after all, it's not being used as a password any more! For bonus fun, submit all previous passwords to pwned passwords. Password reuse makes this a bad idea in general, specific policies attempting to mandate it will not be an issue notwithstanding.
by petesergeant | 2025-06-14 03:06:07+00:00
I had some time in a non-tech gatekeeping position and was able to help a bunch of people, who occasionally thank me for it, and I generally don't remember the details at all, and it's nice and all to be thanked, but I was just doing it because it was the right thing to do. On the other hand I'd be absolutely psyched to hear they were doing it for someone else -- that would put a huge smile on my face.
by PeelingLayers | 2025-06-14 03:06:27+00:00
Section 174 was permanent, until the Tax act of 2017 pushed by the current President made them expire in 2022, under a different President. That was when the market tanked and the Layoffs began. The current bill debated in congress that has the renewal of 174 also removes judicial protection against abuse of power. Enabling government employees to do as they please without having to comply with Judicial oversight. That would give dictatorial powers to the President. 174 needs to be restore without destroying this democracy. Keep that in mind when advocating to Senators.
by liquidiguisante | 2025-06-14 03:07:35+00:00
Hey everyone! This is Manuel from Nomadful (https://nomadful.io) with some exciting news for the health and internet industry. Over the last year, I've been working on a mobile app that provides users with a handful of mental health features like breathing sessions and a journal, completely free of charge. Nomadful is finally available on the App Store (https://apps.apple.com/us/app/nomadful-breathing-journal/id6...) and it is free to download. The mission behind this project is simple and clear: to give free mental health to everyone holding a phone.

Apart from offering this set of basic features, I spent time paying close attention to services from NGOs across more than 40 countries. The result: an integrated help portal users can access when in need for help.

Nomadful is a student project that sets a new standard for how the future of health should be: immediate and free.
by GMoromisato | 2025-06-14 03:08:20+00:00
> Surely it matters where the LLM sits against these values, no?

Yes, I agree, but it's all trade-offs. The core problem is this:

1. Software is very expensive to write

2. So, you need to sell to as many people as possible

3. So, you need to add lots of features to attract as many people as possible

4. And you need to monetize it with ads, data-selling, and SaaS subscriptions.

5. But that makes software complicated, brittle, and frustrating.

LLMs can break the cycle if they make it cheap to write software. Instead of buying a mass-market product with 10x more features than you need, you create custom software that does exactly what you need and no more.

But aren't we trading one master of another? Instead of bowing down to Microsoft/Meta/Google, we bow down to OpenAI/Anthropic/Meta/Google? Maybe, but when an LLM writes code for you, you own the code. The code runs outside of the LLM (usually) on an open platform.

But what if you have to modify the code? Then you ask an LLM (maybe not the original LLM) to modify the code. That's far easier than asking Google to modify Gmail.

If you believe in the suggestions of the author, then I don't think there is a better answer than LLMs. We don't live in a world where everyone can solve their software problems by forking some code, much less modifying it themselves.

And the reason I think it's ironic is because I suspect the author hates LLMs.
by eschaton | 2025-06-14 03:08:22+00:00
It can result in something that looks like/reads as a decent-ish business plan, or an analysis of one or two. But that doesn’t make it such because despite outward appearances no amount of planning, analysis, or comparative analysis actually took place prior to or concurrent with the generation of the tokens.

That’s the fundamental problem with anthropomorphizing LLMs: Giving their output more weight than it deserves.