MurphyA/hacker-news huggingface dataset:
by apothegm | 2025-08-08 02:56:38+00:00
True. Though if you’re paying for sit-down service anyway, the marginal cost of ingredients is relatively low, especially in places with pricey real estate or where tipped wage is higher than the federal minimum. Might as well pay a few extra bucks for the larger serving and have leftovers, IMO.

Last time I dined out, we noticed the smaller portions (mostly cutting out the potatoes or rice that always used to be served under each entree). What caused us to notice it? We had room for dessert afterward! (And yes, the restaurant made more money from us that way, too.)
by voidhorse | 2025-08-08 02:57:52+00:00
Yes, and I think we'll course correct, eventually.

There's a reason we still (generally) teach people how to do arithmetic with pencil and paper instead of jumping straight to calculators. Learning basic algorithms for performing the computations helps solidify the concepts and the rules of the game.

We'll need to do the same thing eventually with respect to LLMs and software engineering. People who skip the foundations or let their comprehension atrophy will eventually end up in a spot in which they need those skills. I basically never do arithmetic using pen and paper now, but I could if I had to, and, more importantly, the process ingrained some basic comprehension of how the integers relate under the group operations.

I totally agree, re: SQL specifically, by the way. SQL is basically already natural language. It's probably the last thing that I'd need to offload to some natural language prompt. I think it's a bit of a vicious circle problem. There's a lot of people who only need to engage with SQL from time to time, so working with it is a bit awkward each time for lack of practice. This incentivizes them to offload it to the LLM just to get it out of the way, which in turn further atrophies their skills with SQL.
by eru | 2025-08-08 03:01:02+00:00
You are right, though on the other hand feeding it a selection of 1% of the entire corpus is already pretty close to 'all the text' (if you assume exponential growth in training over time).

Even multiplying that to approximately 100% of that corpus plus adding lots of non-internet text, will pale in comparison to all the non-text training data we will (or are) feeding our coming (and existing) multi-modal models.

If I may go out an a limb here: either we will see continuous great progress on text-based LLMs alone, or multi-modal models will become the next big focus. (Or both.)

That's because people are hungry for progress, and going multi-modal is the obvious thing to try to focus on, if text alone proves infeasible to drive progress.

Just to be clear: I make no prediction here on whether multi-modal will lead to progress, just that people will obviously try it and try it hard, if the focus on text starts to stall.
by qdw | 2025-08-08 03:01:05+00:00
One of their line items complains about being unable to bind 65k PostgreSQL placeholders (the linked post calls them "parameters") in a single query. This is a cursed idea to begin with, so I can't fully blame PostgreSQL.

From the linked GitHub issue comments, it looks like they adopted the sensible approach of refactoring their ORM so that it splits the big query into several smaller queries. Anecdotally, I've found 3,000 to 5,000 rows per write query to be a good ratio.

Someone else suggested first loading the data into a temp table and then joining against that, which would have further improved performance, especially if they wrote it as a COPY … FROM. But the idea was scrapped (also sensibly) for requiring too many app code changes.

Overall, this was quite an illuminating tome of cursed knowledge, all good warnings to have. Nicely done!
by nopinsight | 2025-08-08 03:02:23+00:00
1. FWIW, I watched clips from several of Dario’s interviews. His expressions and body language convey sincere concerns.

2. Commoditization can be averted with access to proprietary data. This is why all of ChatGPT, Claude, and Gemini push for agents and permissions to access your private data sources now. They will not need to train on your data directly. Just adapting the models to work better with real-world, proprietary data will yield a powerful advantage over time.

Also, the current training paradigm utilizes RL much more extensively than in previous years and can help models to specialize in chosen domains.
by araes | 2025-08-08 03:02:29+00:00
Re: Granny - Pew Research about Online Scams, granny is far less likely to lose her account (15%) than an 18-29 year old (26%). If she's upper income and white even less likely. Similar trends with falling for large numbers of scams. People who've had 3+, granny (19%), 18-26 year olds (24%). [1] The survey notably has the same perception results. Society views the youth as mostly immune from scams (believe only 22%), yet fall victim to them (26%), while worrying about old people (believe 84% fall for them), who actually don't fall victim that often (15%).

Most of the time, re: granny, women are targeted a much greater amount because of supposed weakness and vulnerability (report 2/3, victim 2/3), yet males send much larger amounts of money. ($112 vs $205) [2] Too be fair though, old people do tend to lose more with scams. Granny would probably lose $300 on average vs $113 for a 18-24. Conflicting numbers on the money #'s though, so some of that depends on which survey you ask.

Old people also tend to write each other a lot of cautionary warning stories such as the AARP article on Stan Lee's swindling in old age (security guard, "senior adviser", "protector", and daughter). [3]

Old people get a bunch of grief, yet old people are actually less likely to fall for the scams.

Also, if she's a retiree in Miami Beach, more likely to be targeted (Adak, AK; Deepwater, NJ; then Miami Beach, FL are the worst for scams.)

[1] https://www.pewresearch.org/internet/2025/07/31/online-scams...

[2] https://bbbmarketplacetrust.org/wp-content/uploads/2025/02/N...

[3] https://www.aarp.org/entertainment/celebrities/stan-lee-elde...
by gwern | 2025-08-08 03:02:54+00:00
The initial tweet, 2020-03-05: https://x.com/joeld/status/1235652084264886272

> "I have been working on a reimagining of the blog idea for a few years, and it includes an idea (“series”) that is quite similar to blogchains. See this section of the design docs https://thelocalyarn.com/code/uv/scribbled/Basic_Notions.htm... and partial screen shot. It’s almost ready!"

My original response, in full:

> "One thought on the docs: if there's always a well-defined 'next', why not overload Space/PgDwn to proceed to the next node, GNU Info-like? At the very least, there should be a 'next' link at the bottom, not solely hidden away at the top.

> (Also, no one likes those silly 'st' ligatures.)

> As far as the current theyarn design goes: I like the use of typographic ornaments as a theme, but the colors are confusing. (What does orange vs red vs green denote?) And the pilcrow? Sometimes it's at the beginning of articles (redundant with the hr), sometimes not?

> Hrs seem overused in general, like the (busy) footer. Appending notes chronologically is interesting but confusing, both date/where they begin/end. Are the caps deliberately not small caps? Full-width images would be useful for photos. Be interested to see the new one finished."

I consider these criticisms reasonable, accurate, and constructive, milquetoast even, and stand by them. I see no difference from the many other site critiques I have made over the years (eg https://www.lesswrong.com/posts/Nq2BtFidsnhfLuNAx/announcing... ), which are usually received positively, and I think this is a 'you' problem, especially after reading your other comments. And I will point out that you made no reply to my many concrete points until you decided to write this HN comment 5 years later.

(I have taken the liberty of adding a link to your top-level comment to the end of the existing thread, for context/updating.)

> But responding as though this is an attack to be countered and defeated further illustrates why I had doubts about your suitability as a creative advisor.

This is a remarkable way to characterize this conversation.
by joshdavham | 2025-08-08 03:03:26+00:00
This is awesome! Does anyone else wanna share some of the cursed knowledge they've picked up?

For me, MacOS file names are cursed:

1. Filenames in MacOS are case-INsensitive, meaning file.txt and FILE.txt are equivalent

2. Filenames in MacOS, when saved in NFC, may be converted to NFD
by appreciatorBus | 2025-08-08 03:03:33+00:00
Sure, but in my experience, people never attribute high insurance costs to the underlying risks being high, rather they blame that on the insurance companies and then vote for people who promise to “do something about it“.

I’m sure there is brand damage from people hearing that a particular car is frequently stolen, because having your car stolen as a pain. I am skeptical the analysis reaches deeper than this first level tho.
by ninkendo | 2025-08-08 03:04:14+00:00
Nah, it’d take all night because it would be using the GPU for a fraction of the time, splitting the time with other customer’s tokens, and letting higher priority workloads preempt it.

If you buy enough GPUs to do 1000 customers’ requests in a minute, you could run 60 requests for each of these customers in an hour, or you could run a single request each for 60,000 customers in that same hour. The latter can be much cheaper per customer if people are willing to wait. (In reality it’s a big N x M scheduling problem, and there’s tons of ways to offer tiered pricing where cost and time are the main trafeoffs.)
by eru | 2025-08-08 03:05:08+00:00
> The large language models are not that much better than a single artist / programmer / technical writer (in fact they are significantly worse) working for a couple of hours.

That's like saying sitting on the train for an hour isn't better than walking for a day?

> [...] (unless you are very cheap; but then maybe your workers will organize against you).

I don't understand that. Did workers organise against vacuum cleaners? And what do eg new companies care about organised workers, if they don't hire them in the first place?

Dock workers organised against container shipping. They mostly succeeded in old established ports being sidelined in favour of newer, less annoying ports.
by massysett | 2025-08-08 03:05:37+00:00
I think this sort of comment turns people off from Emacs.

Most people don’t want to become experts in the editor. The editor is a means to an end: writing code, writing text, etc. This comment suggests to the new user: if I don’t program Emacs and publish packages in it, I’m not really using it, I’m just dabbling in it. But I don’t want to program the editor, so I shouldn’t use it at all.

I also don’t think the comments you criticize discourage users who would have discovered something transformative. Someone interested in programming their editor isn’t discouraged by someone who complains that Emacs is missing some modern prettiness, or that it’s not popular. There is plenty of Emacs evangelism that will hook those receptive to it.

I would like to balance out your comment by saying: it is just fine to, as you would say, dabble in Emacs. Don’t write advice. Don’t publish packages. Use customize. Don’t write a .emacs. Use the pull-down menus. It is still a delightfully powerful and well-documented editor even if you do none of the “expert” things. The developers have added so many of these features precisely so Emacs is easier to learn and use, and don’t let commenters who call you a dilettante convince you that if you’re not an Emacs Lisp maestro, you shouldn’t bother with Emacs.
by doctor_radium | 2025-08-08 03:06:15+00:00
Speaking as a person over 40 who has been job-hunting and has encountered Workday roughly 10 times, what I don't understand is whether the "AI-based applicant screening tools, which include personality and cognitive tests" cited in the article are present in every installation, or if they are optional. Optional for either the employer (i.e. it can be switched off, or requires a higher payment tier) or the applicant. I recall one HR platform (probably not Workday) outright requesting my permission to use AI as part of the screening. Something like that. I've always opted out.
by ryanscio | 2025-08-08 03:06:23+00:00
Yes, [1] though a bit vague given "Some organizations may already have access to these models and capabilities without having to go through the Verification process."

I never verified but have access to all models including image gen, for example.

[1] https://help.openai.com/en/articles/10910291-api-organizatio... [2] https://help.openai.com/en/articles/10362446-api-reasoning-m...
by sterlind | 2025-08-08 03:07:14+00:00
it's not erotic role-play, but I have a use case of making an AI-powered NetHack clone. specifically, to generate dungeon layouts, dialog for NPCs and to fill in the boatloads of minutae and interactions which NetHack is famous for.

you kind of need soul for that, and a lot of background knowledge on mythology/fantasy lore, but also tool use to work the world systems.
by kkukshtel | 2025-08-08 03:08:15+00:00
Something that's really hitting me is something brought up in this piece:

https://www.interconnects.ai/p/gpt-5-and-bending-the-arc-of-...

When a model comes out, I usually think about it in terms of my own use. This is largely agentic tooling, and I mostly us Claude Code. All the hallucination and eval talk doesn't really catch me because I feel like I'm getting value of these tools today.

However, this model is not _for_ me in the same way models normally are. This is for the 800m or whatever people that open up chatgpt every day and type stuff in. All of them have been stuck on GPT-4o unbeknwst to them. They had no idea SOTA was far beyond that. They probably dont even know that there is a "model" at all. But for all these people, they just got a MAJOR upgrade. It will probably feel like turning the lights on for these people, who have been using a subpar model for the past year.

That said I'm also giving GPT-5 a run in Codex and it's doing a pretty good job!
by amy_petrik | 2025-08-08 03:08:59+00:00
Realmovies were the new hotness, evolution of video piracy was >vivoactive is the OG (stream only format, like 50x50 pixels, NO KEYFRAMES - no fast forward, rewind, or seeking), talking about 1995 here >realmovies - higher quality, seeking, around 1998 >DIVX (format, not the discs also at the same time) - mindblowing quality update, around 2000 >VCDs - concurrent with DIVX around 2000 >XVID - (DIVX backwards) arose as DIVX failed, 2001 >then wherever we are now, 9999 formats and VLC supports them all
by rayiner | 2025-08-08 03:09:03+00:00
> Why should banks be required to do business with you (for non-protected class reasons)?

Because most people aren’t libertarians and hate Wall Street. It’s a layup. And there’s nothing magic about “protected class reasons.” With respect to private entities, it’s just Congress’s Commerce Clause power. Congress can expand the categories to include whatever it wants.

> Why should Democrats want to make sure that colleges can ignore non-white and non-Asian applicants

Democrats should want to enforce SFFA, which bans racial preferences, whether those policies favor whites, asians, or anyone else. Not only because it’s the law of the land, and necessary to maintain a functioning multi-ethnic society, but because it’s popular: https://thehill.com/homenews/education/4411246-majority-supp...

Using racial preferences to create a unified “people of color” political identity loyal to Democrats has failed and it’s time to declare it dead: https://www.latimes.com/delos/story/2025-07-02/pew-research-...
by eru | 2025-08-08 03:09:10+00:00
We are mixing up two meanings of the word 'warm' here.

There's no emotional warmth involved in manning a call centre and explicitly being confined to a script and having no power to make your own decisions to help the customer.

'Warm body' is just a term that has nothing to do with emotional warmth. I might just as well have called them 'body shops', even though it's of no consequence that the people involved have actual bodies.

> A frigging robot solving your unsolvable problem ? You can try, but witness the backlash.

Front line call centre workers aren't solving your unsolvable problems, either. Just the opposite.

And why are you talking in the hypothetical? The impact on call centres etc is already visible in the statistics.
by robjellinghaus | 2025-08-08 03:13:30+00:00
Hindenburg indeed killed hydrogen blimps. Of everything else on your list, the disaster was in the minority. The space shuttle was the most lethal other item -- there are lots of cruise ships, oil rigs, nuke plants, and jet planes that have not blown up.

So what analogy with AI are you trying to make? The straightforward one would be that there will be some toxic and dangerous LLMs (cough Grok cough), but that there will be many others that do their jobs as designed, and that LLMs in general will be a common technology going forward.
by bee_rider | 2025-08-08 03:16:06+00:00
It would be funny to think of what might actually be a human thing. Like, our arms are quite weird, right? So potentially another intelligent species even on a rocky planet might not invent throwing spears, right? Even our close relatives, the chimpanzees, can’t use them well at all. Even fairly flighty animals seem to barely have the idea that a creature standing, like, tens of feet away from them might be “in range.”

I wonder what the trajectory (no pun intended) of the development of melee spears would be, without throwing spears.

The spear being a wildly popular a successful weapon for almost all of history, any changes to spears would, I guess, make a big difference.
by lutusp | 2025-08-08 03:17:00+00:00
I have a canonical test for chatbots -- I ask them who I am. I'm sufficiently unknown in modern times that it's a fair test. Just ask, "Who is Paul Lutus?"

ChatGPT 5's reply is mostly made up -- about 80% is pure invention. I'm described as having written books and articles whose titles I don't even recognize, or having accomplished things at odds with what was once called reality.

But things are slowly improving. In past ChatGPT versions I was described as having been dead for a decade.

I'm waiting for the day when, instead of hallucinating, a chatbot will reply, "I have no idea."

I propose a new technical Litmus test -- chatbots should be judged based on what they won't say.
by tzs | 2025-08-08 03:17:12+00:00
> For this new attack to work, all that is needed is a single button-press capture from the keyfob, without any jamming. Just from that single capture, it is able to emulate all the keyfob's functions, including lock, unlock, and unlock trunk.

If I don't press the buttons on my keyfob am I safe from this?

The only keyfob functionality I normally use is that when it is outside the car but within about a meter of the door handle the door can be locked or unlocked by pressing a button on the door handle.
by techpineapple | 2025-08-08 03:18:20+00:00
I’m curious what this means. Maybe I’m stupid but I read through the sample gpt-4 vs got-5 and I largely couldn’t tell the difference and sometimes preferred the gpt-4 answer. But like what are the average 800 million people using this for that the average 800 million user will be able to see a difference?

Maybe I’m a far below average user? But I can’t tell the difference between models in causal use.

Unless you’re talking performance, apparently gpt-5 is much faster.
by famouswaffles | 2025-08-08 03:19:02+00:00
>Can you clarify what this threshold is? I know that's one sentence, but I think it is the most important one in my reply. It is really what everything else comes down to. There's a lot of room between even academic scale and industry scale. There's very few things with papers in the middle.

Something like GPT-2. Something that even before being actually useful or particularly coherent, was interesting enough to spark articles like these. https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-g... So far, only LLM/LLM adjacent stuff fulfils this criteria.

To be clear, I'm not saying general R&D must meet this requirement. Not at all. But if you're arguing about diverting millions/billions in funds from x that is working to y then it has to at least clear that bar.

> My argument is simply "there should be no threshold, it should be continuous".

I don't think this is feasible for large investments. I may be wrong, but i also don't think other avenues aren't being funded. They just don't compare in scale because....well they haven't really done anything to justify such scale yet.
by jjani | 2025-08-08 03:19:17+00:00
Neither will be. Both OpenRouter and Azure (through requiring and enterprise agreement, only available to large orgs with 500+ devices) require it for o3 to this very day, and already do so for GPT-5, the main model under discussion in this thread (sure, not mini and nano, but those aren't where 95% of the attention is focused on).
by EthanHeilman | 2025-08-08 03:19:27+00:00
> It is frequently suggested that once one of the AI companies reaches an AGI threshold, they will take off ahead of the rest.

This seems to be a result of using overly simplistic models of progress. A company makes a breakthrough, the next breakthrough requires exploring many more paths. It is much easier to catch up than find a breakthrough. Even if you get lucky and find the next breakthrough before everyone catches up, they will probably catch up before you find the breakthrough after that. You only have someone run away if each time you make a breakthrough, it is easier to make the next breakthrough than to catch up.

Consider the following game:

1. N parties take turns rolling a D20. If anyone rolls 20, they get 1 point.

2. If any party is 1 or more points behind, they get only need to roll a 19 or higher to get one point. That is being behind gives you a slight advantage in catching up.

While points accumulate, most of the players end up with the same score.

I ran a simulation of this game for 10,000 turns with 5 players:

Game 1: [852, 851, 851, 851, 851]

Game 2: [827, 825, 827, 826, 826]

Game 3: [827, 822, 827, 827, 826]

Game 4: [864, 863, 860, 863, 863]

Game 5: [831, 828, 836, 833, 834]
by alenguo | 2025-08-08 03:20:12+00:00
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by hodgehog11 | 2025-08-08 03:20:13+00:00
People often talk in terms of performance curves or "neural scaling laws". Every model architecture class exhibits a very similar scaling exponent because the data and the training procedures are playing the dominant role (every theoretical model which replicates the scaling laws exhibit this property). There are some discrepancies across model architecture classes, but there are hard limits on this.

Theoretical models for neural scaling laws are still preliminary of course, but all of this seems to be supported by experiments at smaller scales.