MurphyA/hacker-news huggingface dataset:
by Retric | 2025-08-07 21:34:43+00:00
Stagnation, growth, and shrinking have been commonplace over the last 2,000 years. “Countries” have taken hundreds of years to regain economic peaks without being destroyed.

Overall population growth hides how minimal the per capita growth has actually been. If you assume ~1$/day as subsistence level 2,000 years ago then we’re talking something like 0.2% annual growth with the vast majority of that being very recent. But even that’s overstating things based on how the modern economy values hand crafted goods.
by elpocko | 2025-08-07 21:34:52+00:00
In Germany only 40+% of your income goes to taxes and social security. Plus another meager ~20% on most things you buy. Plus a small tax on many things that are supposedly bad for you, like ~70% on cigarettes. Death is taxed at a discount, only 15-40% depending on how rich you were.

"Free" healthcare though. It's a bargain!
by AbstractH24 | 2025-08-07 21:35:24+00:00
> It's cool and I'm glad it sounds like it's getting more reliable, but given the types of things people have been saying GPT-5 would be for the last two years you'd expect GPT-5 to be a world-shattering release rather than incremental and stable improvement.

Are you trying to say the curve is flattening? That advances are coming slower and slower?

As long as it doesn't suggest a dot com level recession I'm good.
by sugarpimpdorsey | 2025-08-07 21:35:27+00:00
> Bluesky's moderation service is all client side opt-in. It's force-enabled by the default client but any third party client allows you to opt-out

No matter how many times this pedantry gets repeated in this thread, this is literally not opt-in.

A light switch that is glued in place so you cannot turn it off is not opt-in.

Sure, some people with the know-how can get a pair of dikes and cut it out of the wall, the light will turn off and they will say "see, I opted out!"

But most people won't do this. At best it is misleading to say so.
by geerlingguy | 2025-08-07 21:35:37+00:00
I've been testing Exo (seems dead), llama.cpp RPC (has a lot of performance limitations) and distributed-llama (faster but has some Vulkan quirks and only works with a few models).

See my AI cluster automation setup here: https://github.com/geerlingguy/beowulf-ai-cluster

I was building that through the course of making this video, because it's insane how much manual labor people put into building home AI clusters :D
by throwawayReLU | 2025-08-07 21:35:39+00:00
It probably depends on the definition of "expert" here. Based on my definition, experts are people who write the LLM papers I read (some of them are my colleagues), people who implement them, people that push the field forward and PhD researchers blogs that go into depth and show understanding of how attention and transformers work, including underlying math and theory. Based on my own knowledge, experience (I'm working on LLMs in the field) and my discussions with people I consider experts in my day job I wouldn't add you to this category, at least not yet.

Based on my reading of some of your blogs and reading your discussions with others on this site, you still lack technical depth and understanding of the underlying mechanisms at what I would call an expert level. I hope this doesn't sound insulting, maybe you have a different definition of "expert". I also do not say you lack the capacity to become an expert someday. I just want to explain why, while you consider yourself an expert, some people could not see you as an expert. But as I said, maybe it's just different definitions. But your blogs still have value, a lot of people read them and find them valuable, so your work is definitely worthwhile. Keep up the good work!
by lukev | 2025-08-07 21:36:07+00:00
There's multiple kinds of novelty. Remixing arbitrary stuff is a strength of LLMs (has been ever since GPT-2, actually... "Write a shakespearean sonnet but talk like a pirate.")

Many (but not all) coding tasks fall into this category. "Connect to API A using language B and library C, while integrating with D on the backend." Which is really cool!

But there's other coding tasks that it just can't really do. E.g, I'm building a database with some novel approaches to query optimization and LLMs are totally lost in that part of the code.
by oiWecsio | 2025-08-07 21:36:23+00:00
> Imagine I make a library for loading a certain format of small, trusted configuration files.

> Some guy files a CVE against my library, saying it crashes if you feed it a large, untrusted file.

Not CVE-worthy, as the use case clearly falls outside of the documented / declared area of application.

> refusing to load conspicuously large files [...] Is the new release a major, minor, or bugfix release?

It deserves a major release, because it breaks compatibility. A capability that used to work (i.e,. loading a large but trusted file) no longer works. It may not affect everyone, but when assessing impact, we go for the most conservative evaluation.
by threecheese | 2025-08-07 21:37:13+00:00
The inanity of this issue’s text aside; lack of task comprehensiveness in these models is obvious, and in my opinion isn’t something we should even expect in a nondeterministic system. I wouldn’t blindly trust anyone without some constraints checking, trust but verify.

I have some interest in this area, and wonder if a “not-LLM-as-judge” that can extract/infer constraints from a task description (or get them from an operator) could be used to judge task completion. Conceptually similar to structured outputs. Maybe there’s a paper already…
by stouset | 2025-08-07 21:37:48+00:00
Earth is a sphere with a fixed surface area. We have one way to shed heat energy off our planet: thermal radiation. There’s no convecting or conducting into space.

That makes it pretty easy to calculate the thermodynamic equilibrium temperature of earth, given the amount of energy we receive from the sun. Notably this is much less than our actual, observed temperature thanks to greenhouse gases.

Creating energy here adds to this equilibrium calculation. This applies to oil, coal, nuclear, fusion, and any mythical new energy source you want to come up with. If the energy is released here, it shows up as an increase in our equilibrium temperature.

Thankfully right now, the added energy doesn’t add up to much. But in surprisingly short order, using more and more energy will add up and produce a noticeable (and fatal) rise in Earth’s equilibrium temperature. Once we hit that point, our options are to stop using more energy or to boil the oceans. That’s thermodynamically unavoidable.

There’s no way around it either. Capture more solar and beam it here? That just directly contributes to our energy excess. Pump excess heat into objects and launch them into space? That’s literally worse than just not having produced the energy here in the first place.
by diggan | 2025-08-07 21:38:26+00:00
> All it takes is a simple reply of “you’re wrong.” to Claude/ChatGPT/etc. and it will start to crumble on itself and get into a loop that hallucinates over and over.

Yeah, it's seems to be a terrible approach to try to "correct" the context by adding clarifications or telling it what's wrong.

Instead, start from 0 with the same initial prompt you used, but improve it so the LLM gets it right in the first response. If it still gets it wrong, begin from 0 again. The context seems to be "poisoned" really quickly, if you're looking for accuracy in the responses. So better to begin from the beginning as soon as it veers off course.
by giantg2 | 2025-08-07 21:39:09+00:00
I was going to say, you can study 10 hours a day on topics that you like or find valuable and not cover all the material for the test. I took the SAT as a junior and didn't really study for it, so I hadn't covered some of the math types yet. I still did fine and got into all the colleges I applied to. It really only seems to matter if you want to go to a prestigious school.
by flockonus | 2025-08-07 21:39:09+00:00
If we're focusing on fast take-off scenario, this isn't a good trend to focus on.

SGI would be self-improving to some function with a shape close to linear based on the amount of time & resources. That's almost exclusively dependent on the software design, as currently transformers have shown to hit a wall at logarithmic progression x resources.

In other words, no, it has little to do with the commercial race.
by kristopolous | 2025-08-07 21:40:06+00:00
Porn is always the frontier.

It's a well-understood self-contained use-case without many externalities and simple business models.

What more, with porn, the medium is the product probably more than the content. Having it on home-media in the 80s was the selling point. Getting it over the 1-900 phone lines or accessing it over the internet ... these were arguably the actual product. It might have been a driver of early smart phone adoption as well. Adult content is about an 80% consumption on handheld devices while the internet writ large is about 60%.

Private tunable multi-media interaction on-demand is the product here.

Also it's a unique offer. Role playing prohibited sexual acts can be done arguably victim free.

There's a good fiction story there... "I thought I was talking to AI"
by OtherShrezzing | 2025-08-07 21:40:08+00:00
>"They claim impressive reductions in hallucinations. In my own usage I’ve not spotted a single hallucination yet, but that’s been true for me for Claude 4 and o3 recently as well—hallucination is so much less of a problem with this year’s models."

Could you give an estimate of how many "dumb errors" you've encountered, as opposed to hallucinations? I think many of your readers might read "hallucination" and assume you mean "hallucinations and dumb errors".
by hn_throwaway_99 | 2025-08-07 21:40:18+00:00
Completely agree. The other thing that was very encouraging about the study is that it actually reversed memory decline - it's not like you needed to take it for years/decades in advance to prevent that decline in the first place, so you can make the choice when the risk/reward tradeoff is much clearer.

Having seen a few family members succumb to dementia, it's not a path I want to take. Fuck up my kidneys and give me an early death, fine, but if I start showing the signs of that type of mental decline, I'm taking the lithium orotate.

My related biggest concern about this is that since it's a cheap supplement that can't be patented, it won't be a priority for the drug industry to study. Another reason to not necessarily trust the "Just slowly die by Alzheimers until we find the perfectly safe (patentable) antidote" crowd.
by stouset | 2025-08-07 21:41:17+00:00
We are not talking about an individual city or country having stagnation.

We are talking about the entire planet, as a whole, transitioning to a fully steady-state economy for the entirety of the planet’s future. If you that is anything like what any modern industrialized civilization has experienced or been built around, you are out of your mind.

This is not just idle musing. I encourage you to do some reading about the arguments being made before assuming they can just be hand-waved away.

https://dothemath.ucsd.edu/2012/04/economist-meets-physicist...
by andsoitis | 2025-08-07 21:41:46+00:00
> Some people think of Science, with a capital-“S”, as the official declaration of eternal truths. I prefer to think of science, with a lower-case “s”, as a messy scrabble toward half-truths that are often overturned with further research.

Yes!

It is a process: systematic study of the natural world through observation, experimentation, and evidence-based reasoning.

It is a world view: a way humans try to understand how things work.

It is not a set of immutable facts etched into a stone tablet somewhere in the cosmos waiting to be decoded.
by Perz1val | 2025-08-07 21:42:13+00:00
I don't know if you're sarcastic or just missing the problem; which is that people will be presented with lika a facebook login page, on a site with url like `facebook.quick-login.com` or `facebock.com` and they'll enter the passcode since as fair as they were concerned, they did everything correct. The disclaimer does shit preventing that, they »obviously« didn't share the code with any other website, they entered it on the facebooks as they were told!
by NitpickLawyer | 2025-08-07 21:42:34+00:00
> They're an artifact of a training process, not code that was written by someone.

If that were relevant to the licensing discussion, then you'd have to consider every "generated" parts (interfaces, dataclasses, etc) of every open source project artefacts. Historically, that was never the case. The license doesn't care if a hardcoded value was written by a person or "tuned" via a process. It's still source code if it's the preferred way of modifying said code. And it is. You can totally edit them by hand. It would not work as well (or at all), but you could do it.
by skydancer16 | 2025-08-07 21:43:08+00:00
Location: Los Angeles / Culver City, CA Remote: Yes, also willing to do hybrid or full in-office Willing to relocate: No Technologies: Java, Kotlin, MySql, MongoDB, C#, Spring Boot, Gradle, Jenkins, Github, JSON, React Resume: on LinkedIn profile Linkedin: https://www.linkedin.com/in/chloejosien/ GitHub: https://github.com/chloeJosien

Hi, I'm Chloe, and I'm looking for any role that involves backend or full-stack development. I have 4 years of experience, and in my most recent role, I was responsible for designing our databases and creating and maintaining all the REST API calls that communicated with our frontend team. I'm also available immediately Thanks!
by DoctorOetker | 2025-08-07 21:43:17+00:00
we could run some tests to first find out if comparative performance tests can be conjured:

one can intentionally use a recent and a much older model to figure out if the tests are reliable, and in which domains it is reliable.

one can compute a models joint probability for a sequence and compare how likely each model finds the same sequence.

we could ask both to start talking about a subject, but alternatingly each can emit a token. look again at how the dumber and smarter models judge the resulting sentence does the smart one tend to pull up the quality of the resulting text, or does it tend to get dragged down more towards the dumber participant?

given enough such tests to "identify the dummy vs smart one" and verifying them on common agreement (as an extreme word2vec vs transformer) to assess the quality of the test, regardless of domain.

on the assumption that such or similar tests allow us to indicate the smarter one, i.e. assuming we find plenty such tests, we can demand model makers publish open weights so that we can publically verify performance agreements.

Another idea is self-consistency tests: a single forward inference of context size say 2048 tokens (just an example) is effectively predicting the conditional 2-gram, 3-gram, 4-gram probabilities on the input tokens. so each output token distribution is predicted on the preceding inputs, so there are 2048 input tokens and 2048 output tokens, the position 1 output token is the predicted token vector (logit vector really) that is estimated to follow the given position 1 input vector, and the position 2 output vector is the prediction following the first 2 input vectors etc. and the last vector is the predicted next token following all the 2048 input tokens. p(t_(i+1) | t_1 =a, t_2=b, ..., t_i=z).

But that is just one way the next token can be predicted using the network: another approach would be to use RMAD gradient descent, but keeping model weights fixed, and only considering the last say 512 input vectors as variable, how well did the last 512 predicted forward prediction output vectors match the gradient descent best joint probability output vectors?

This could be added as a loss term during training as well, as a form of regularization, which turns it into a kind of Energy Based Model roughly.
by fnordpiglet | 2025-08-07 21:44:05+00:00
Altman et al have been discussing the many model interface in ChatGPT is confusing to users and they want to move to a unified system that exposes a model that routes based on the task rather than depending on users understanding how and when to do that. Presumably this is what they’ve been discussing for some time. I don’t know that was intended to mean they would be working toward some unified inference architecture and model, although I’m sure goal posts will be moved to ensure it’s insufficient.
by olieidel | 2025-08-07 21:44:14+00:00
Yes, that's true, but the implementation is.. not very elegant.

In theory, the exit tax should ensure that Germany gets the taxes of the sale of your company. So, if you ever sold your company once you're no longer in Germany, Germany wouldn't get those taxes, so it charges you immediately once you leave Germany in a sort-of "virtual" sale.

This, of course, sucks tremendously because you actually haven't sold your company, and "normal" people don't have this sort of cash on hand.

Other countries have "smarter" exit tax implementations and only charge you when you actually sell your company in the future. I think that's pretty fair. It also doesn't hinder people from leaving the country.
by ath3nd | 2025-08-07 21:44:37+00:00
Yeah if 'worlds apart in style' means 'kinda similar'.

There was this joke in this thread that there are the ChatGPT sommeliers that are discussing the subtle difference between the different models nowadays.

It's funny cause in the last year the models have kind of converged in almost every aspect, but the fanbase, kind of like pretentious sommeliers, is trying to convince us that the subtle 0.05% difference on some obscure benchmark is really significant and that they, the experts, can really feel the difference.

It's hilarious and sad at the same time.
by doormatt | 2025-08-07 21:45:02+00:00
You mention that Algphys can simulate any polynomial-time Turing algorithm with preserved complexity, but in your construction, the dynamics of Algphys are governed by physical properties: gradient norms, Hessian spectra, rigidity, etc. How do you guarantee that these geometric constraints don’t impose an exponential slowdown on some Turing algorithms that would otherwise run in polynomial time? Specifically, where do you prove that no such algorithm is mapped into a high-rigidity trajectory with exponential execution time?
by andsoitis | 2025-08-07 21:45:05+00:00
> 3. So, should we all be on GLP-1s?

> No. Certainly not now. While I’m excited about the future of these drugs’ development, the side effect profile isn’t worth the risk for otherwise healthy patients. The anti-inflammation and cognitive benefits of the drugs still come with weight-loss effects that many Americans shouldn’t accept.

Another way to fight inflammation is taking Metformin, popular in longevity circles.
by egypturnash | 2025-08-07 21:45:16+00:00
Man I wish I had $3.5k to do this. Actually I wish I had $3.5k to do this and try to go into total overdrive mode on my queer comics for a while, I could probably crank out a page a day if I just sat my ass in front of the computer all day instead of going out and doing errands and slacking around the park.

Oh well, guess I'll stay in New Orleans and draw queer comics at a less punishing pace instead.

(actually sheesh if we use the standard conversion rate of "a picture is worth a thousand words" then my usual peak of two pages a week is probably more work per week than the stated minimum of 500 words per post.)
by magicalhippo | 2025-08-07 21:45:29+00:00
Sadly no. I'd like to keep it untainted, but also because the tables involved are straight from my work, which is very much not OSS.

I can however try to paraphrase it so you get the gist of it.

The question asks to provide a SQL statement to update rows in table A based on related tables B and C, where table B is mentioned explicitly and C is implicit through the foreign keys provided in the context.

The key point all previous models I've tested has missed, is that the rows in A are many-to-one with B, and so the update should take this into account. This is implicit from the foreign key context and not mentioned directly in the question.

Think distributing pizza slices between a group of friends. All previous models has completely missed this part and just given each friend the whole pizza.

GPT-OSS correctly identified this issue and flagged it in the response, but also included a sensible assumption of evenly dividing the pizza.

I should note some of the previous models also missed the implicit connection to table C, and thus completely failed to do something sensible. But at least several of them figured this out. Of course I forgot to write that part down so can't say offhand which did what.

As for the code, for example I've coded a Y combinator in Delphi, using intentionally terse non-descriptive names, and asked the models to explain how the code works and what it does. Most ~7B models and larger of the past year or so have managed to explain it fairly well. However GPT-OSS was much more thorough and provider a much better explanation, showing a significantly better "understanding" of the code. It was also the first model smaller than LLama 3 70B that I've tried that correctly identified it as a Y combinator.
by dismalaf | 2025-08-07 21:46:14+00:00
OSS isn't a business model. The most successful projects I've seen is when someone has a business, releases a tool they use, then others iterate on said tool that the business uses. Then everyone gets a better tool.

Think Linux, Rails, most programming languages, etc...

OSS as a business model usually means a rug-pull, and I've never seen it going that well...
by mpyne | 2025-08-07 21:46:20+00:00
> which is wholly predicated upon unbounded exponential growth

The economy does not require and is not predicated upon unbounded exponential growth.

Do not confuse economic activity growing where growth is easy, as a mandate for growth to work at all.

Companies that can no longer grow but can keep profits by keeping prices above costs can continue indefinitely. But ultimately the economic represents the activity of human workers aided by technology.

If everyone is working and there's no technological help to be had then the economy can no longer expand... but in this model of the world everyone is gainfully employed and doing something, and that can resolve in many different ways of setting cost (of labor and technology) and price (of goods and services).
by godelski | 2025-08-07 21:47:01+00:00
> It does sort of give me the vibe that the pure scaling maximalism really is dying off though

I think the big question is if/when investors will start giving money to those who have been predicting this (with evidence) and trying other avenues.

Really though, why put all your eggs in one basket? That's what I've been confused about for awhile. Why fund yet another LLMs to AGI startup. Space is saturated with big players and has been for years. Even if LLMs could get there that doesn't mean something else won't get there faster and for less. It also seems you'd want a backup in order to avoid popping the bubble. Technology S-Curves and all that still apply to AI

Though I'm similarly biased, but so is everyone I know with a strong math and/or science background (I even mentioned it in my thesis more than a few times lol). Scaling is all you need just doesn't check out
by olieidel | 2025-08-07 21:47:20+00:00
Agreed. As mentioned in another comment, I think it'd be fair to levy the exit tax when you actually sell your company in the future. Like, if I ever sell my business, I'd be happy to pay my fair share of German taxes on said business, even if I'd no longer be a tax resident of Germany.

The current implementation which essentially simulates a "virtual" sale of your business once you leave the country is pretty terrible, as most normal humans don't have that sort of cash on hand because, well, they actually didn't sell their business at that point in time.

Interesting pointer on Canada - thanks!