MurphyA/hacker-news huggingface dataset:
by kkarich | 2025-08-24 03:31:28+00:00
Really nice writeup!

I've been thinking about this approach. How do you handle updates on this setup? For example, a status component that goes from "loading" to "success".

Does the LLM go back and modify the previous response, sending deltas to the client? Effectively changing the component from loading to success. Or is something else happening behind the scenes?
by bigstrat2003 | 2025-08-24 03:32:39+00:00
That was the first one for me as well and I was surprised they included it. I have never seen a disposable straw that does the job well, except for plastic. I actively avoid restaurants that use the cardboard straws because of it. That's how bad they suck. I can't believe the EU was foolish enough to ban plastic straws when there just isn't an actual viable alternative.
by AnthonyMouse | 2025-08-24 03:32:50+00:00
> No, it’s not. Appeal->higher level review. 97 percent of your regular customers get served with no issues.

Yes, it is, because it causes 10% of the whole ocean to end up needing manual review for an appeal.

> The problem is that the fraudulent ads fetch much higher than average CPV and CPC.

They're sold at auction. They only have to outbid the next highest bidder by a hair.
by hyfgfh | 2025-08-24 03:33:00+00:00
Svgs, date management, Http, so many simpler things we dont have solve and somehow people believe they will do it by putting enough money in LLMs when it cant count

Why some people understood when they tried it with blockchain, nfts, web3, AR, ... any good engineer should know principle of energy efficiency instead of having faith in the Infinite monkey theorem
by rbren | 2025-08-24 03:33:09+00:00
If you’re looking for a non-slop OSS agent, check out OpenHands: https://github.com/All-Hands-AI/OpenHands?tab=readme-ov-file

(It’s written like 30% of its own code, so maybe a little slop if I’m being fair. But it’s mostly humans! Almost 400 of us now!)
by jacobobryant | 2025-08-24 03:34:02+00:00
I've been working on this kind of thing over the past several years (for a while full time as an attempted entrepreneur, now on the side for the past couple years). The latest iteration is https://yakread.com -- hit "take a look around" and you can see the "home page"/a list of recommendations without signing up. The recommendations are personalized, i.e. the probability you'll see any particular post depends on your individual interactions with past posts, if you've signed up. (it does collaborative filtering with spark mllib). So that may be a bit different from what you had in mind, since your comment sounds more like an unpersonalized system, but with some extra exploration thrown in. However in practice I suspect the biggest thing the collaborative filtering is doing at Yakread's current scale (not much) is learning which items are good/bad in general.

I also do have some methods baked in for doing exploration. "Epsilon greedy" is a common simple approach where x% of the recommendations are purely random. I do a bit more of a linear thing where I rank all the posts by how many times they've been recommended, then I pick a percentage 0 - 100, then I throw out the top x% most popular (previously recommended) items. that also gives you some flexibility to try out different distributions for the x% variable.

The source is at https://github.com/jacobobryant/yakread
by dllu | 2025-08-24 03:34:34+00:00
I've taken a couple of pics from a moving train...

Nankai 6000 series, Osaka:

https://i.dllu.net/nankai_19b8df3e827215a2.jpg

Scenery in France:

https://i.dllu.net/preview_l_b01915cc69f35644.png

Marseille, France:

https://i.dllu.net/preview_raw_7292be4e58de5cd0.png

California:

https://i.dllu.net/preview_raw_d5ec50534991d1a4.png

https://i.dllu.net/preview_raw_e06b551444359536.png

Sorry for the purple trees. The camera is sensitive to near infrared, in which trees are highly reflective, and I haven't taken any trains since buying an IR cut filter. Some of these also have dropped frames and other artifacts.
by chazeon | 2025-08-24 03:34:35+00:00
I want to note that: long prompts are good only if the model is optimized for it. I have tried to swap the underlying model for Claude Code. Most local models, even those claimed to work with long context and tool use, don't work well when instruction becomes too long. This has become an issue for tool use, where tool use works well in small ChatBot-type conversation demos, but when Claude's code-level prompt length increases, it just fails, either forgetting what tools are there, forgetting to use them, or returning in the wrong formats. Only the model by OpenAI, Google's Gemini, kind of works, but not as well as Anthropic's own models. Besides they feel much slower.
by chatmasta | 2025-08-24 03:34:55+00:00
Kafka was created at LinkedIn when it was already quite a large web platform, to solve the problem of distributing a unique newsfeed to a wide audience… so while they weren’t Google, they were still closer to Google than the targets of the “UNPHAT” expression. You can apply UNPHAT to most of the people using Kafka today, but it’s not fair to apply it to LinkedIn when they created it.
by wkat4242 | 2025-08-24 03:35:28+00:00
Here in Spain we use telegram a lot. I've heard in the US it's used only for piracy and drugs but we use it for everything. There's groups letting people know of Nvidia card availability. Groups for every community I'm part of (WhatsApp sucks at group chats), from makerspaces, lgbt events to tattoo artists, gigs etc. There's also a group exposing the faces of metro pickpockets because the police doesn't care. Stuff like that.

The good thing is that Telegram is not American so you don't get this prude censorship BS that you get on American apps (show half a nipple and get banned). Especially in the LGBT groups this can be a problem but also in the makerspace one (one of our members really loves making certain toys lol). Of course actual porn is not ok but that's fine, we don't use it for that.

I also like that their premium subscription is super affordable, only 2€ per month (it's cheaper if you don't pay through the Apple/Google ripoff stores) and it offers a lot of cool and useful features like automatic translation and transcription (which actually works unlike WhatsApp's)

I'm really quite happy with it and on top of everything bots are a fully supported first class citizen there so you don't have to screw around with hacky code like with WhatsApp. I have several bots for myself. So if there's a feature I want that it doesn't have I can simply add it!
by alangou | 2025-08-24 03:35:34+00:00
My favorite tell-tale sign:

> The gap isn’t just quantitative—it’s qualitative.

> LLMs don’t have memory—they engage in elaborate methods to fake it...

> This isn’t just database persistence—it’s building memory systems that evolve the way human memory does...

> The future isn’t one model to rule them all—it’s hundreds or thousands of specialized models working together in orchestrated workflows...

> The future of AGI is architectural, not algorithmic.
by vel0city | 2025-08-24 03:35:56+00:00
> Sure it's on the menu and they make a profit on it

My point is, the statement "calculators and MSP430s for remote power meters are keeping TI from closing up shop" isn't based in reality. Both of these products are tiny parts of their business. If that's all you know of TI, you don't know TI. Like thinking McDonald's is an ice cream shop and completely being ignorant of the burgers and fries, saying those ice cream cones are keeping McDonald's from closing up shop.

Even for the MSP430, it's a small product line of their wireless and microcontroller products.
by keepgettingban | 2025-08-24 03:36:19+00:00
To be crystal clear - the finding under Biden was that there are non-negligible risks of myocarditis after receiving the vaccine.

This exact fact was downplayed by both Pfizer and Moderna during Operation Warp Speed (oh no, that was under Trump so can we trust it?).

A genuine desire to understand reality would lead you to examine this incongruence.
by tetromino_ | 2025-08-24 03:37:06+00:00
> have drones made combat helicopters obsolete?

Which drones?

Helicopters are vulnerable to small quadcopter drones when landing and taking off. This limits some traditional uses of helicopters (anything that involves landing in enemy territory becomes much more risky) but still leaves others (shooting missiles at surface targets).

Helicopters are very effective at shooting down large fixed-wing drones.

Helicopters are very effective at sinking drone boats without air defenses, but are in turn very vulnerable to drone boats equipped with SAMs.
by conradev | 2025-08-24 03:38:43+00:00
Absolutely! It’s completely, unambiguously legal, which is why Google allows emulators on the Play Store.

Apple, beholden to copyright interests, is wary of software that allows even the possibility of copyright infringement. They just recently allowed video game emulators on their store.

It’s not a legal distinction, sure, but it’s also not apples to apples.
by anileated | 2025-08-24 03:38:52+00:00
> Theft (from Old English þeofð, cognate to thief) is the act of taking another person's property or services without that person's permission or consent with the intent to deprive the rightful owner of it

> for over a thousand years theft has mean taking something from someone permanently

Nothing in your comment is in contradiction to mine, or suggests that the word has been “overloaded”. That’s what theft is. Intellectual property is property, trade secrets are property.
by quectophoton | 2025-08-24 03:39:45+00:00
My thoughts are that LLMs are like cooking a chicken by slapping it: yes, it works, but you need to reach a certain amount of kinetic energy (the same way LLMs only "start working" after reaching a certain size).

So then, if we can cook a chicken like this, we can also heat a whole house like this during winters, right? We just need a chicken-slapper that's even bigger and even faster, and slap the whole house to heat it up.

There's probably better analogies (because I know people will nitpick that we knew about fire way before kinetic energy), so maybe AI="flight by inventing machines with flapping wings" and AGI="space travel with machines that flap wings even faster". But the house-sized chicken-slapper illustrates how I view the current trend of trying to reach AGI by scaling up LLMs.
by jiggawatts | 2025-08-24 03:40:14+00:00
When pair programming was a fad in the early 2000s, I tried it with a coworker for a security-critical piece of code that needed two pairs of eyes on it.

It felt horrendously unproductive to have two people at one keyboard but we compared commit rates and the surprising result was that we produced the same rate of changes as working separately.
by majormajor | 2025-08-24 03:40:14+00:00
All the disadvantages of those stacks still exist.

So if you need to avoid GC issues, or have robust type safety, or whatever it is, to gain an edge in a certain industry or scenario, you can't just switch to the vibe tool of choice without (best case) giving up $$$ to pay to make up for the inefficiency or (worst case) having more failures that your customers won't tolerate.

But this means the gap between the "hard" work and the "easy" work may become larger - compensation included. Probably most notably in FAANG companies where people are brought in expected to be able to do "hard" work and then frequently given relatively-easy CRUD work in low-ROI ancillary projects but with higher $$$$ than that work would give anywhere else.

And the places currently happy to hire disaffected ex-FAANG engineers who realized they were being wasted on polishing widgets may start having more hiring difficulty as the pipeline dries up. Like trying to hire for assembly or COBOL today.
by stonecharioteer | 2025-08-24 03:41:48+00:00
Burnout. I'm enjoying building things again, I burnt out because I didn't finish projects.

I finally do now.

I have done so much in the last 3 months.

1. Cleaned up my personal website and blogs 2. Built a couple of learning tools for myself - https://rfc.stonecharioteer.com and https://github.com/stonecharioteer/goforgo 3. Setup OpenWRT and Adguard+Unbound at home, with a non-trivial failover with multiple WANs.

It's helping heal my burnout, something that crippled me for years and kept me from my side projects. It showed in my career too, because I've stagnated since 2021. I'm trying to improve now, and I'm relying on Claude Code and ChatGPT (albeit on legacy models) to do so. 3.
by nout | 2025-08-24 03:42:00+00:00
And so if you try installing the Bluesky app, how many relays does it have? And in Mississippi you now won't be install the app or you won't able to use the bluesky relay either?

I'm coming from understanding nostr - each app usually starts with ~10 relays and as you start interacting with other people it collects more paths/routes/relays (the new "outbox model"). So as soon as you install any nostr app, it's usually not affected by any single relay issue.
by majormajor | 2025-08-24 03:42:13+00:00
What is it that you think would make a certain non-Python language "more optimal" for an LLM? Is there something inherently LLM-friendly about certain language patterns or is "huge sets of training examples" and "a robust standard library" (the latter to conserve tokens/attention vs having to spit out super-verbose 20x longer assembly all day) all "optimality" means?
by arp242 | 2025-08-24 03:42:19+00:00
Cheapest Fiat Panda seems to go for €14,700[1], so colour me sceptical on that "€30k+ for a new small car". In a quick check, it seems it was about €10k in 2011.[2]

The price increase is more than inflation, but you can't just assume that it's primarily due to safety regulations and emission standards.

[1] https://www.fiat.it/omni/configuratore/#/customize?color=CL-...

[2] https://supercarblondie.com/how-much-the-fiat-panda-has-incr...
by surajrmal | 2025-08-24 03:42:28+00:00
It would be nice if folks linked crates up into ecosystems thst shared maintainers and guidelines. We don't need everyone using the same stuff, but I'd rather prefer to get 10 different dependences rather than 30. In c++ this plays out in libraries like absl, folly, boost and others. Fewer larger dependencies that bring in a mix of functionality.
by anileated | 2025-08-24 03:42:38+00:00
> It's pretty metaphorical to describe such things as property that can be stolen.

Stealing is a pretty wide term meaning deprivation of a good, asset, property, service, etc. If it means deprivation only of physical goods at some point in time, sure; this is 2025 outside now. Theft of physical goods is so first millenium.
by AnthonyMouse | 2025-08-24 03:43:31+00:00
> Adding AEB specifically is estimated to cost $100-$300 per vehicle in the US, and it wouldn't be much different in Europe.

Isn't this exactly the issue? Any given thing is "only" $300 but you add one of these requirements a year for several decades straight and now you've added thousands of dollars to the price of a car.

> And AEB is proven to work: reducing the rate of accidents by 40% or more.

It reduces the rate of accidents that occur under certain circumstances. Pretty good chance that those circumstances are "in a city in traffic". But then the feature is required on all cars, even when the owner knows they'll rarely if ever be driving it under the conditions where it's useful. Or worse, when they know they'll be commonly driving under circumstances where it's more likely to encounter a false positive and cause an accident.
by defrost | 2025-08-24 03:44:54+00:00
"the vaccine" ... which vaccine?

None the less:

Long-term follow-up data from a new NCIRS study have revealed low hospitalisation rates, improved health-related quality of life over time and no deaths among individuals with myocarditis associated with mRNA COVID-19 vaccination who were followed up over 18 months following their diagnosis. ‘This is the longest and most comprehensive prospective follow-up study of individuals diagnosed with myocarditis following mRNA COVID-19 vaccination to date that includes direct assessment of the individuals’ clinical progression and health-related quality of life.’ ‘Our study suggests that while a proportion of mRNA COVID-19 vaccine-associated myocarditis cases remained symptomatic at 12–18 months, they were clinically mild compared with myocarditis caused by viral infections – including SARS-CoV-2 – and the subsequent impact on health-related quality of life was also mild,’ concluded Dr Deng.

~ https://ncirs.org.au/ncirs-study-assesses-clinical-progressi...

From Australia, a country of ~ 25 million where ~ 98% of the population were triple vaccinated for COVID with pre-existing comprehensive population wide medical records going back to at least the 1970s.

Despite the "flood" of vaccine there was no significant increase of myocarditis in the population before | after mass vaccination.

A genuine desire to understand reality would lead you to examine this incongruence.
by jppope | 2025-08-24 03:45:05+00:00
I've said this a lot but I'm going to say it again AGI has no technical definition. One day Sam Altman, Elon Musk, or some other business guy trying to meet their obligation for next quarter will declare they have built AGI and that will be that. We'll argue and debate, but eventually it will be just another marketing term, just like AI was.
by justcallmejm | 2025-08-24 03:45:40+00:00
I'd argue that it's because intelligence has been treated as a ML/NN engineering problem that we've had the hyper focus on improving LLMs rather than the approach you've written about.

Intelligence must be built from a first principles theory of what intelligence actually is.

The missing science to engineer intelligence is composable program synthesis. Aloe (https://aloe.inc) recently released a GAIA score demonstrating how CPS dramatically outperforms other generalist agents (OpenAI's deep research, Manus, and Genspark) on tasks similar to those a knowledge worker would perform.
by Nevermark | 2025-08-24 03:47:11+00:00
I don't have any "beliefs", just best understandings at any give time, which I am constantly and actively improving.

Of course I don't know everything about anything. It floors me that people ever think they do. And that many are not motivated learners or listeners, even/often in the areas they most care about.

I can't make sense of your negative assessment of a few private cars paying their way on public tracks, already used by large organizations.

But the way you described public access in general was a good viewpoint, and that helped me clarify my own reasoning.

You didn't explicitly use the words marginal cost, but your description was very close to that, and it really struck me as the heart of the matter. A consistent way to think about moral economic policies for public things being made available to private parties, at serious discounts, but without public tax dollars subsidizing those private parties. (Unless subsidizing for everyone is the point, like libraries.)

All things being equal, it is morally wrong when taxes subsidize something only wealthy people can afford. That seems like a point of agreement.

Subtle distinctions can matter a lot, as it did here, so thank you.

Cheers!
by hoyo1s | 2025-08-24 03:47:13+00:00
Sometimes one just need [language or tech stack] to do something, especially for some performance/security considerations.

For now LLMs still suffers from hallucination and lack of generalizability, The large amount of code generated is sometimes not necessarily a benefit, but a technical debt.

LLMs are good for open and fast, prototype web applications, but if we need a stable, consistent, maintainable, secure framework, or scientific computing, pure LLMs are not enough, one can't vibe everything without checking details
by XorNot | 2025-08-24 03:47:23+00:00
They don't run their own lives.

They have people to coordinate their housing, transportation and children.

They don't cook or clean for themselves, they can simply rent out luxury accomodations wherever they land and if an idea hits them at any hour then some person is being paid to answer the phone and figure out what the heck it actually means they should do at 3am when they thought of it.

And then when they turn up somewhere, they talk solely about how hard they worked before someone tells them their next meeting, where dinner will be tonight and here's your private driver.
by justcallmejm | 2025-08-24 03:47:34+00:00
The missing science to engineer intelligence is composable program synthesis. Aloe (https://aloe.inc) recently released a GAIA score demonstrating how CPS dramatically outperforms other generalist agents (OpenAI's deep research, Manus, and Genspark) on tasks similar to those a knowledge worker would perform.

I'd argue it's because intelligence has been treated as a ML/NN engineering problem that we've had the hyper focus on improving LLMs rather than the approach articulated in the essay.

Intelligence must be built from a first principles theory of what intelligence actually is.
by jjani | 2025-08-24 03:48:15+00:00
> So you want examples of developed countries going after parents, taking children away, because of what someone else did?

No. I want examples where the driver doesn't get charged and faces zero consequences (not even getting fired from their job, fwiw) while the parents both get charged with involuntary manslaughter when their child got killed directly by a different adult.

And I'm happy to consider cases where the child was killed by an adult through other means than a car. Suicide has always been treated entirely differently by pretty much every justice system in existence, the analogy doesn't work.
by manquer | 2025-08-24 03:48:54+00:00
Maximize economic output not necessarily profit outside of that I agree with your comment, nobody is questioning whether we should have other goals.

The problem is however first can we all define the goals consistently and agree on the definition.

Next can we measure the value/benefits of the goal. This is typically subjective so everybody paints the picture best suited to their preconceived ideas.

Finally perception drives the political will for a social program. UBI style programs or just giving money in welfare instead of in-kind benefits for food or healthcare etc or rehabilitation over punishment are more efficient and while shown to work, will rarely get political support because of how they are perceived.

Given that we all have different understanding of the goals, measure them differently and have different moralities on what should be done as society (for welfare, crime etc) and have varying degrees of influence over policy what can we do to approach a problem better
by crazylogger | 2025-08-24 03:49:58+00:00
I think the OP's point is that all those requirements are to be implemented outside the LLM layer, i.e. we don't need to conceive of any new model architecture. Even if LLMs don't progress any further beyond GPT-5 & Claude 4, we'll still get there.

Take memory for example: give LLM a persistent computer and ask it to jot down its long-term memory as hierarchical directories of markdown documents. Recalling a piece of memory means a bunch of `tree` and `grep` commands. It's very, very rudimentary, but it kinda works, today. We just have to think of incrementally smarter ways to query & maintain this type of memory repo, which is a pure engineering problem.
by refulgentis | 2025-08-24 03:50:02+00:00
Right - I'd suggest the idea that 128 GB of GPU RAM gives you an 8K context shows us it may be worth revising priors such as "it has strong advantages for inference as well as training"

As Mr. Hildebrand used to say, when you assume, you make...

(also note the article specifically frames this speccing out as about training :) not just me suggesting it)