MurphyA/hacker-news huggingface dataset:
by SchemaLoad | 2025-09-03 23:27:12+00:00
Could be that there is a huge difference in the products. Last few companies have given me Github Copilot which I find entirely useless, I found the automatic suggestions more distracting than useful, and the fix and explain functions never work. But maybe if you burn $1000/day on Claude Code it works a lot better. And then companies see the results from that and wonder why they aren't getting it spending a couple of dollars on Copilot.
by gleenn | 2025-09-03 23:27:21+00:00
I think your phrase choice is also quite funny. Obviously a fact isn't physically stolen, it has been surveilled and sold to the highest bidder. Every fair chance a competitor had to offer you something better was taken from you, it just wasn't done in front of your face. And that data is becoming more and more valuable as we speak as all this AI data race heats up.
by ankit219 | 2025-09-03 23:27:41+00:00
I like the thesis, (and probably not a fully informed opinion here), it's easier for openai like router to go the affiliate model than ads model. Router can determine how much a query is worth (eg: help plan a vacation is worth $50 vs say what is the capital of Australia as $0). This further informs how much compute to use, and this can lead to how much they get on affiliate fees if a link is clicked. Ads here are counter to the proposition in the sense that results are to be trusted. Then, despite everything, while contextual ads are good, personalized ads are still going to be more effective (gut feel). To get there, openai needs the kind of infra Facebook and Google has. They can get the same value (perhaps more) from affiliate links - especially in a world where they are kind of gateway to the discovery - and don't have to do as much work on the infra side. This also aligns incentives for all three - companies, consumers, and middlemen, in a way it only happened with Google before this.
by gamblor956 | 2025-09-03 23:27:58+00:00
Trains don't go everywhere because of a conscious, deliberate and top-down (centrally planned) choice to invest in car infrastructure.

Once again, this is false.

Trains don't go everywhere because America is large. Geographically, the "center" of America is larger than the entirety of continental Europe. You can fit the rich part of Europe in the American desert and still have room to spare. A U.S. train network as dense as what Europe has would cost hundreds of billions.

Trains of course used to go everywhere in North America, and were economically viable just fine, until cars were artificially made more economically viable.

This was never true. Trains have always been primarily about cargo in the U.S.

Cars were pushed because for several decades, cars were the cheapest and best option for a country as geographically large as the U.S.
by dr_dshiv | 2025-09-03 23:28:44+00:00
Let’s keep in mind that we don’t have most of the renaissance through the early modern period (1400-1800) because it was published in neolatin with older typefaces— and only about 10% is even digitized.

We probably don’t have most of the Arabic corpus either — and barely any Sanskrit. Classical Chinese is probably also lacking — only about 1% of it is translated to English.
by AIorNot | 2025-09-03 23:28:48+00:00
You guys are aware of Advaita and neo Advaita right? It basically has been the perrinal philosophy underlying all subjective spiritual experiences from Sufism to Gnostics to Buddhism and the Tao

Of course it could all be claptrap that humans want to believe in but I find it to be pretty powerful and I think it is true

(Warning: Gets into spiritual stuff)

https://youtu.be/R-IIzAblVlg?si=t9RqXgF_wwJPcv_g
by palata | 2025-09-03 23:29:07+00:00
What the hell are you talking about?

> First off, my money doesn't grant me power over anybody and it's still money.

Sure, but it doesn't invalidate the sentence you quoted. At all. You can't "educate" people if you don't understand basic sentences. Let me quote it again, so that maybe you can try to understand it properly:

> A world where being rich doesn't grant power over others is one where money isn't money.
by anp | 2025-09-03 23:30:22+00:00
FWIW this closely matches my experience. I’m pretty late to the AI hype train but my opinion changed specifically because of using combinations of models & tools that released right before the cut off date for the data here. My impression from friends is that it’s taken even longer for many companies to decide they’re OK with these tools being used at all, so I would expect a lot of hysteresis on outputs from that kind of adoption.

That said I’ve had similar misgivings about the METR study and I’m eager for there to be more aggregate study of the productivity outcomes.
by haleem123 | 2025-09-03 23:30:24+00:00
You note "the beaten path is saturated" - how do you reconcile that with two facts:

1. Fact 1: There is unusually high unemployment rate for new STEM graduates, including those with advanced degrees like MS and PhDs

2. Fact 2: Our politicians and business leaders are noting there is a "massive shortage of workers in STEM" and thus we need to import hundreds of thousands of foreign workers to meet the demand.

How can both be true and in line with your position?
by BizarroLand | 2025-09-03 23:30:34+00:00
That's among the worst takes I've ever seen.

"Oh, a company knows literally everything about me and clandestinely sells that information to the highest bidder in order to target every facet of my existence so that multinational conglomerations can extract every erg of value from every heartbeat of my existence, but that's cool because I also know that information"

Geez.
by godshatter | 2025-09-03 23:31:37+00:00
I'd throw brain plasticity in there. I'm worried about this given my age (getting close to 60) and I will sometimes bounce off of a song or a TV show or a movie or a book immediately and then force myself to go through it and see if it really is that bad or not. Sometimes it is, but often there's stuff to like if you're looking for it even in the worst of it's kind.
by marssaxman | 2025-09-03 23:31:46+00:00
A single-pass compiler is easier to implement in part because you're not going to do any of that optimization. You're writing a single-pass compiler either because you're banging out a quick sketch of an idea, and you don't care about production use, or because you've time-traveled back to the '70s or the '80s, where processors were so painfully slow and memory so eye-wateringly expensive that you might not even be able to read the entire source file into RAM at once, much less convert it all into some intermediate representation before starting to write out the machine code.
by vineyardmike | 2025-09-03 23:32:06+00:00
Definitely OpenAI. They’re not profitable and their core product is expensive to serve. They also have the disadvantage that their better models and features (eg agents, research, CoT, etc) are more expensive, but are better hooks to prove utility to new users - fundamentally they need a method to cheapen the cost of serving free users better features. Google can afford to see how it shakes out and the impact to OpenAI.

OpenAI already exploring and experimenting with different ad modalities privately. They’re also have a much better brand, so they might be able to avoid too much churn of customers.
by neilv | 2025-09-03 23:32:07+00:00
There's also the questionable copyright/IP angle.

As an analogy, can you imagine being a startup that hired a developer, and months later finding out the bulk of the new Web app they "coded" for you was actually copy&pasted open source code, loosely obfuscated, which they were passing it off as something they developed, and to which the company had IP rights?

You'd immediately convene the cofounders and a lawyer, about how to make this have never happened.

First you realize that you need to hand the lawyer the evidence (against the employee), and otherwise remove all traces of that code and activity from the company.

Simultaneously, you need to get real developers started rushing to rewrite everything without obvious IP taint.

Then one of you will delicately ask whether firing and legal action against the employee is sufficient, or whether the employee needs to sleep with the fishes to keep them quiet.

The lawyer will say this kind of situation isn't within the scope of their practice, but here's the number of a person they refer to only as 'the specialist'.

Soon, not only are you losing the startup, and the LLC is being pierced to go after your personal assets, but you're also personally going to prison. Because you were also too cheap to pay the professional fee for 'the specialist', and you asked ChatGPT to make the employee have a freak industrial shredder accident.

All this because you tried to cheap out, and spend $20 or $200 on getting some kind of code to appear in your repo, while pretending you didn't know where it came from.
by vidarh | 2025-09-03 23:32:09+00:00
The logic isn't self evident because it is irrelevant that their total demand doesn't add up this way, because the unit cost of the capacity is higher, and so the cost still ends up being far higher.

The unit cost is higher for many reasons, but the two basic ones are margins (exorbitant ones; this is not an efficient market) and that the providers also need to charge for the unused capacity to meet demand from customers behaving in ways they don't on fixed capacity systems, where spreading workloads over time wherever possible tends to become the norm.

The demand curves when you're charged for total demand over time rather than peak demand are fundamentally different, and so while you're right the peaks rarely add up in the worst possible way, empirically the peaks end up high enough that cloud compute is expensive even before the exorbitant margins the large cloud providers charge.
by kbenson | 2025-09-03 23:32:14+00:00
I interpreted it as a roundabout way of increasing quality. Take any given subreddit. You have posts and comments, and scores, but what if the data quality isn't very good overall? What if instead of using it as is, you instead had an AI evaluate and reason about all the posts, and classify them itself based on how useful the posts and comments are, how well they work out in practice (if easily simulated), etc? Essentially you're using the AI to provide a moderated and carefully curated set of information about the information that was already present. If you then ingest this information, does that increase the quality of the data? Probably(?), since you're throwing compute and AI reasoning at the problem ahead of time reducing compute and lowering the low quality data by adding additional high quality data.
by scotty79 | 2025-09-03 23:32:25+00:00
How widely is AI adopted in the wider IT industry anyways? I imagine $200 per month subscription isn't that popular with people refusing to pay for their IDEs and going with free alternatives instead. And month worth of free tier of AI agent can be spent in two intense evenings.

So who pays for AIs for developers? Mostly corpos. And the speed of individual developer was never a limiting factor in corpos. Average corporate development was always 10 times slower than indie. So even doubling it won't make any impression.

I don't know if I'm faster with AI at a specific task, but I know that I'm doing things I wouldn't touch because I hate the tedium. And I'm doing them while cooking and eating dinner and thinking about wider context and next things to come. So for me it feels worth it.

I think it might be something like with cars and safety. Any car safety improvements are going to be offset by the drivers driving faster and more recklessly. So maybe any speed improvements that AI might make for the project is nullified by developers doing things they would just skip without it.
by mattmanser | 2025-09-03 23:32:44+00:00
I actually just looked, if anything the PH data supports his theory, assuming the website I found is scraping this data accurately.

In fact it looks like there were less products launched last month on PH than the same period a year ago.

https://hunted.space/monthly-overview

It's a bit hard as they're not summing by months but it looks like less to me quickly scanning it.

And as Claude Code has only really been out 3/4 months you'd be expecting launches to be shooting up week-by-week right about now as all the vibe products get finished.

They're not, see the 8 week graph:

https://hunted.space/stats
by Quarrelsome | 2025-09-03 23:33:06+00:00
I really enjoyed reading this article as I found its content extremely insightful, but I fear I must whine for far too long about something entirely minor.

As someone that didn't go to expensive maths club, the way people who did, talk about maths is disgraceful imho. Consider the equasion in this article:

(C ~ 6 N⋅D)

I can look up the symbol for "roughly equals", that was super cool and is a great part of curiousity. But this _implied_ multiplication between the 6 and the N combined with using a fucking diamond symbol (that I already despise given how long it took me to figure the first time I encountered it) is just gross. I figured it was likely that but then I was like: "but why not just 6ND? Maybe there's a reason why N⋅D but 6 N? Does that mean there's a difference between those operations"?

Thankfully I can use gippity these days to get by, but before gippity I had to look up an entire list of maths symbols to find the diamond symbol to work out what it meant. Its why I love code because there's considerably less implicit behaviour once you slap down the formula into code and you can play with the input/output.

I don't think mathsy people realise how exclusionary their communication is, but its so frustrating when I end up fumbling around in slow-mo when the maths kicks in, because "oh the /2 when discussing logarithms in comp sci is _obvious_, so we just don't put it in the equasion" just kills me. Idiot me, staring at the equasion thinking it actually makes sense without knowing the special maths knowledge of implication means that it actually doesn't solve as it reads on the page. Unless of course you went to expensive maths club where they tell you all this.

What drives me nuts is that every time I spend ages finally grokking something, I realise how obvious it is and how non-trivial it is to explain it simply. Comp sci isn't much better to be honest, where we use CQRS instead of "read here, write there". Which results in thousands of newbies trying to parse the unfathomable complexity of "Command Query Responsibility Segregation" and spending as much time staring at its opaqueness as I did the opening sentence of the wikipedia article on logarithms.

Idk what my point is, I just don't understand what's wrong with 6⋅N⋅D or 6*N*D. Do mathmeticians feel ugly if they write something down like that or smth?
by palata | 2025-09-03 23:33:15+00:00
> your reward is losing control if it?

That's not what I understand from the GP. What they say is taht if your business is extremely successful, it can keep being extremely successful and you can keep control over it.

You just cannot accumulate more money for yourself. Like if the highest amount of money in a video game was 1 billion. Once you reach it, you don't go back to 0, you just can't go higher.

Makes sense to me.
by mvdtnz | 2025-09-03 23:33:53+00:00
> LLMs can be automated to do busy work and although they may take longer in terms of clock time than a human, the work is effectively done in the background.

What is this supposed busy work that can be done in the background unsupervised?

I think it's about time for the AI pushers to be absolutely clear about the actual specific tasks they are having success with. We're all getting a bit tired of the vagueness and hand waving.
by davmre | 2025-09-03 23:34:05+00:00
If there's a general standard of transparency applied to all companies, fine. There are costs to increasing transparency, but certainly you could argue for that policy.

The argument that we should cheer on the use of government power to target a specific company, to selectively expose their dirty laundry as punishment for a crime they have not been convicted of, is what I found noxious in the original post.
by conor- | 2025-09-03 23:34:34+00:00
That doesn't really mean it's heavyweight though; an extra layer, sure (but I don't even really agree that it's complex - you set it up once and then mostly just log the same way you would with any other).

You can still log to a text file if you want to run locally, but for something like next.js where you're intended to deploy production to some cloud somewhere (probably serverless) the option of _just_ writing to a text file doesn't really exist. So having OTEL as an ootb supported way to do o11y is much better than the alternative of getting sucked into some vendor-specific garbage like datadog or newrelic
by sporkxrocket | 2025-09-03 23:34:54+00:00
It's very unfortunate that this post is being filtered from the main page. Imagine if there wasn't dramatic global censorship of anything anti-Israel. Opposition would be orders of magnitude greater.

Edit: of course now this article if flagged and the comments downvoted. That's diabolical. This site doesn't even have the thinnest veneer of impartiality, it's literally a propaganda arm for Israel.
by brazzy | 2025-09-03 23:35:24+00:00
The point is that current methods are unable to get more than the current state-of-the-art models' degree of intelligence out of training on the totality of human knowledge. Previously, the amount of compute needed to process that much data was a limit, but not anymore.

So now, in order to progress further, we either have to improve the methods, or synthetically generate more training data, or both.
by fluoridation | 2025-09-03 23:35:58+00:00
I don't. It's based off my own testing, not by disabling SMT, but by running either <core_count> or <thread_count> parallel threads. It was my own code, so it's possible code that uses SIMD more heavily will see a less-significant speed-up. It's also possible I just measured wrong; running Cargo on a directory with -j16 and -j32 takes 58 and 48 seconds respectively.

>From a hardware perspective, I can't imagine how it could be physically possible to double performance by enabling SMT.

It depends on which parts of the processor your code uses. SMT works by duplicating some but not all the components of each core, so a single core can work on multiple independent uops simultaneously. I don't know the specifics, but I can imagine ALU-type code (jumps, calls, movs, etc.) benefits more from SMT than very math-heavy code. That would explain why rustc saw a greater speedup than Cinebench, as compiler code is very twisty with not a lot of math.
by kelseyfrog | 2025-09-03 23:37:10+00:00
Nethack was the one that really hooked me. Telnetting into nethack.org from the CSCI lab computers during university will always be a fond memory.

These days I facilitate roguelike development each year with a group code-along (for lack of a better term). Each year a group of participants follow along together and produce their own roguelike. The tutorial is in Python but folks participate using a bunch of other languages. This year we had people who made it to the end with Rust, C++, C#, and Odin, to name a few. Completion posts are still rolling in so I'm excited to see what this year's batch cooked up. :)
by tech_ken | 2025-09-03 23:37:30+00:00
> How do you know that?

Well you don't, and my reading of the article was that Nagle also recognized that it was basically an assumption which he granted to bats specifically so as to have a concrete example (one which was suitably unobjectionable, seems like he thought bats 'obviously' had some level of consciousness). The actual utility of this definition is not, as far as my understanding goes, to demarcate between what is and what is not conscious. It seems more like he's using it to establish a sort of "proof-by-contradiction" against the proposal that consciousness admits a totally materialistic description. Something like:

(1) If you say that A is conscious, then you also must say that A has subjective self-experience (which is my understanding of the point of the whole "what it is to be like" thing)

(2) Any complete description/account of the consciousness of A must contain a description of the subjective self-experience of A because of (1)

(3) Subjective self-experience cannot be explained in purely materialistic/universal terms, because it's subjective (so basically by definition)

=> Consciousness cannot be fully described in a materialistic framework, because of the contradiction between (2) and (3)

> Just that all models, however useful are still models

Totally agree with this, I think you're just misunderstanding the specific utility of this model (which is this specific argument about what can be described using human language). My example with the rock was kind of a specific response to OP illustrate how I understood the whole "what it is to be like" thing to be equivalent to (1). If I'd had a bit more forethought I probably would have made those arrows in the line you've quoted bidirectional.
by conor- | 2025-09-03 23:37:36+00:00
I don't really know anything about self-hosting Next apps - but if you're deploying to k8s, it's not really that difficult or far-fetched to run an otel collector sidecar for your applications. It's already common to run some kind of prometheus scraper or other service to collect logs/metrics from your services but instead of having to have different collection methods for APM vs logs vs traces you can have it all aggregated in one place using OTLP format
by larve | 2025-09-03 23:38:20+00:00
I don't think so, although I think at that point experience heavily comes into play. With GPT-5 especially, I can basically point cursor/codex at a repo and say "refactor this to this pattern" and come back 25 minutes later to a pretty much impeccable result. In fact that's become my favourite past time lately.

I linked some examples higher up, but I've been maintaining a lot of packages that I started slightly before chatgpt and then refactored and worked on as I progressively moved to the "entirely AI generated" workflow I have today.

I don't think it's an easy skill (not saying that to make myself look good, I spent an ungodly amount of time exploring programming with LLMs and still do), akin to thinking at a strategic level vs at a "code" level.

Certain design patterns also make it much easier to deal with LLM code: state reducers (redux/zustand for example), event-driven architectures, component-based design systems, building many CLI tools that the agent can invoke to iterate and correct things, as do certain "tools" like sqlite/tmux (by that I mean just telling the LLM "btw you can use tmux/sqlite", you allow it to pass hurdles that would otherwise just make it spiral into slop-ratatouille).

I also think that a language like go was a really good coincidence, because it is so amenable to LLM-ification.
by dgl | 2025-09-03 23:38:27+00:00
It's not; the git format defines it as a positive integer, see git help commit:

DATE FORMATS The GIT_AUTHOR_DATE and GIT_COMMITTER_DATE environment variables support the following date formats: Git internal format It is <unix-timestamp> <time-zone-offset>, where <unix-timestamp> is the number of seconds since the UNIX epoch.

Changing a commit's timestamp is as simple as:

$ git commit --amend --date='1970-01-01T00:00:00' --reset-author [main 6e1d001] test Date: Thu Jan 1 00:00:00 1970 +0000 1 file changed, 1 insertion(+)

But dates before 1970 really don't work (in some cases it gives "fatal: invalid date format"):

TZ=UTC git commit --amend --date='1969-12-31T23:59:59Z' --reset-author [main 47e54f0] test Date: Mon Dec 31 23:59:59 2012 +0000 1 file changed, 1 insertion(+)