MurphyA/hacker-news huggingface dataset:
by jdiff | 2025-08-07 22:01:40+00:00
If you have 10 harcoded values, you have a binary blob, a common feature particularly in hardware drivers that is opaque and commonly considered to not be fully free unless the instructions for deriving it are also included. It's frequently just an executable, occasionally just configuration information, but difficult to change while (assuming no signing shenanigans) still remaining technically possible.

The training data is the source code and the training process is the compiler. There's a fairly direct metaphor to be made there. Different compilers can have vastly different impacts on the performance of the compiled executable.
by zhivota | 2025-08-07 22:01:51+00:00
This is interesting to me for the reason of having a way to interact with social media that isn't loading a social media feed. It would be great to put this on my blog and then have people able to comment on it, and basically the only way I interact with Blue Sky or any social media feed is through this kind of interface and through creating content.

Over the years I've found that any interaction with social media that involves me loading the feed inevitably ends up with me doomscrolling or spending way too much time scrolling stuff that doesn't add anything to my life. This could be a way to avoid that cycle, finally, but still interact with the wider social media world a little bit.
by 01HNNWZ0MV43FF | 2025-08-07 22:02:01+00:00
500 words a post and I'm not working full-time? Shit that's not even a third of a NaNoWriMo. My hands don't even hurt. I already shitpost 500 words a day on Hacker News, my third-favorite social media content platform.

Honestly I'm tempted. I know the rationalists have a bad rap but I have a grudging respect for Scott Alexander.

Plus $3,500 to live in Cali for a month... barely more than I'm paying over here
by kristopolous | 2025-08-07 22:02:02+00:00
oh it's wildly different. About 15 years ago I worked on a porn recommendation system. The idea is that you'd follow a number of sites based on likes and recommendations and you'd get an aggregated feed with interstitial ads.

So I started with scraping and cross-reference, foaf, doing analysis. People's preferences are ... really complex.

Without getting too lewd, let's say there's about 30-80 categories with non-marginal demand depending on how you want to slice it and some of them can stack so you get a combinatoric.

In early user testing people wanted the niche and found the adventurous (of their particular kind) to be more compelling. And that was the unpredictable part. The majoritarian categories didn't have stickiness.

Nor did these niches have high correlation. Someone could be into say, specific topic A (let's say feet), and correlating that with topic B (let's say leather) was a dice roll. The probabilities were almost universally < 10% unless you went into majoritarian categories (eg. fit people in their 20s).

People want adventure on a reservation with a very well defined perimeter - one that is hard to map and different for every person.

So the value-add proposition went away since it's now just a collection of niche sites again.

Also, these days people have Reddit accounts reserved for porn where they do exactly this. So it was built after all.
by almostgotcaught | 2025-08-07 22:02:10+00:00
Anecdotes abound <shrug>. My only advantage going into it was 1) I was a good reader 2) I was well familiar with logical fallacies from a childhood of trolling/debating people online. But it's a standardized test that covers a very small set of skills. So just like any other standardized thing it's trainable.
by tsvetkov | 2025-08-07 22:02:28+00:00
Fascinating to see how agents are redefining what IDEs are. This was not really the case in the chat AI era. But as autonomy increases, the traditional IDE UI becomes less important form of interaction. I think those CLI tools have pretty good chance to create a new dev tools ecosystem. Creating a full featured language plugin (let alone a full IDE) for VSCode or Intellij is not for a faint-hearted, and cross IDE portability is limited. CLI tools + MCP can be a lot simpler, more composable and more portable.
by echoangle | 2025-08-07 22:02:58+00:00
The specific instance doesn’t need to know everything happening in the world at once to be AGI though. You could feed the trained model different contexts based on the task (and even let the model tell you what kind of raw data it wants) and it could still hypothetically be smarter than a human.

I’m not saying this is a realistic or efficient method to create AGI, but I think the argument „Model is static once trained -> model can’t be AGI“ is fallacious.
by cnst | 2025-08-07 22:03:45+00:00
11k defines in gc is nothing, the files in the nbio dir are so big, github even refuses to parse many them:

https://kernel.googlesource.com/pub/scm/linux/kernel/git/tor...

https://github.com/torvalds/linux/blob/master/drivers/gpu/dr...

The last file in nbio is a header file with 38900 lines — a single file of 3.92 MB.

There's actually another one in nbio that's 16MB:

https://github.com/torvalds/linux/blob/master/drivers/gpu/dr...
by kukkeliskuu | 2025-08-07 22:04:32+00:00
Coincidentally, I have been implementing an ad pacing system recently, with the help of Anthropic Opus and Sonnet, based on PID controller

Opus recommended that I should use a PID controller -- I have no prior experience with PID controllers. I wrote a spec based on those recommendations, and asked Claude Code to verify and modify the spec, create the implementation and also substantial amount of unit and integration tests.

I was initially impressed.

Then I iterated on ihe implementation, deploying it to production and later giving Claude Code access to log of production measurements as JSON when showing some test ads, and some guidance of the issues I was seeing.

The basic PID controller implementation was fine, but there were several problems with the solution:

- The PID controller state was not persisted, as it was adjusted using a management command, adjustments were not actually applied

- The implementation was assuming that the data collected was for each impression, whereas the data was collected using counters

- It was calculating rate of impressions partly using hard-coded values, instead of using a provided function that was calculating the rate using timestamps

- There was a single PID controller for each ad, instead of ad+slot combination, and this was causing the values to fluctuate

- The code was mixing the setpoint/measured value (viewing rate) and output value (weight), meaning it did not really "understand" what the PID controller was used for

- One requirement was to show a default ad to take extra capacity, but it was never able to calculate the required capacity properly, causing the default ad to take too much of the capacity.

None of these were identified by tests nor Claude Code when it was told to inspect the implementation and tests why they did not catch the production issues. It never proposed using different default PID controller parameters.

All fixes Claude Code proposed on the production issues were outside the PID controller, mostly by limiting output values, normalizing values, smoothing them, recognizing "runaway ads" etc.

These solved each production issue with the test ads, but did not really address the underlying problems.

There is lots of literature on tuning PID controllers, and there are also autotuning algorithms with their own limitations. But tuning still seems to be more an art form than exact science.

I don't know what I was expecting from this experiment, and how much could have been improved by better prompting. But to me this is indicative of the limitations of the "intelligence" of Claude Code. It does not appear to really "understand" the implementation.

Solving each issue above required some kind of innovative step. This is typical for me when exploring something I am not too familar with.

I learned a lot about ad pacing though.
by ath3nd | 2025-08-07 22:04:36+00:00
> I like how you clearly used AI to create this comparison. Probably used ChatGPT for it

Great catch! You should consider a career as a detective! I hope this sentence from the beginning of my post didn't make it too easy on your impressive deduction skills:

"If not, maybe we can ask ChatGPT about it (below is ChatGPT's "opinion" on the similarities between Enron and OpenAI):"
by ComplexSystems | 2025-08-07 22:05:27+00:00
o3 is the best OpenAI model but it still makes tons of mistakes. It's got a very strong background in most of undergrad level math, and a decent amount of grad level machine learning stuff, but its tendency to hallucinate means it will greedily fixate on some initial conjecture early on, not realize it's a conjecture, and continue to assert that it's true for the rest of the conversation. Similarly, if it thinks something is impossible, it will just assert that and continue to assert again and again that it's impossible, even if it's actually true. It's like the mathematical version of a hallucination. There is no real reason it should do this for grad level topics - they just haven't trained it enough. It has a survey level knowledge of a TON of ideas, which can be great if you are looking for topics related to something, but as far as the details of exactly how things are related, what subtleties and caveats there are and so on, it will just hallucinate its first guess and get stuck there for the rest of the conversation.

o3-pro is maybe marginally better, but it takes a very long time to respond and so I rarely use it.

4o is much worse and so I usually use o3.

Gemini 2.5 Pro is much better - and free. Grok 4 is also probably up there with Gemini 2.5. They just have less tendency to hallucinate in this way in general: they will spend more time reasoning, checking claims, searching for prior literature, etc. They still mess up, but not quite as much as o3. I don't use Sonnet or Opus for math all that much - my impression was that o3 was better than Sonnet 3.7 but not sure about 4.
by tuckerman | 2025-08-07 22:05:47+00:00
I think you could say something remarkably similar about just releasing bytecode as well and I think most people would call foul at that. I don't think it's so cut and dry.

This isn't entirely about being a beginner or not either. Full fine-tuning without forgetting does really want the training data (or something that is a good replacement). You can do things like LoRa but, depending on your use case, it might not work.
by codebje | 2025-08-07 22:06:29+00:00
The system being demonstrated only has three effects: World, State, and Stop, and all the valid combinations of those are given at the very end of the document.

As far as I can tell, these natural transformations are equivalent to the type class instances required for monad transformers. You need some way to transform a computation in a component monad to a computation in the composed monad.

There's three combinations of World, State, and Stop expressed, with natural transformations for each specific effect within each combination, ie, "lift" for each part to the composed whole. Those particular effects don't sensibly compose any other way than the ones given: there's no (reasonable) interpretation of State of Stops, only for Stops of State, and no reasonable interpretation of World that isn't "on the inside", much like in mtl one always puts IO at the bottom of the stack.

If we had an Error effect, though, maybe we'd want to interpret errors within stateful computations and retain the state, maybe we'd want to interpret errors outside the stateful computation and abort the whole thing...

But sure, in an effects-based system you'd preferentially use effect composition over monads, and sure, monad transformers is an n^2 problem, but sadly natural transformations between functors obeying certain laws is also an n^2 problem.

I think. I do admit to getting lost on what the different squiggles mean, quite a lot.
by spauldo | 2025-08-07 22:06:55+00:00
It's not horribly common. If POSIX mandates something insecure, OpenBSD will often break POSIX in favor of security.

The simplest example is gets(3) doesn't exist in libc. rand(3) and family aren't deterministic (srand_deterministic(3) gives you that, but it's OpenBSD-specific). There are others, but it's not something I think about a lot so I can't think of them off the top of my head.

If you're genuinely interested I'd recommend asking over at DaemonForums. I'm sure someone has compiled a list somewhere.
by pdpi | 2025-08-07 22:07:34+00:00
You misunderstood me.

I started off by saying that 0-9a-v digits was "a bit extreme", which was a pretty blatant euphemism — I think that's a terrible idea.

Visually ambiguous symbols are a well-known problem, and choosing your alphabet carefully to avoid ambiguity is a tried and true way to make that sort of thing less terrible. My point was, rather, that the moment you suggest changing the alphabet you're using to avoid ambiguity should also be the moment you wonder whether using such a large number base is a good idea to begin with.

In the context of the original discussion around using larger bytes, the fact that we're even having a discussion about skipping ambiguous symbols is an argument against using 10-bit bytes. The ergonomics or actually writing the damned things is just plain poor. Forget skipping o, O, l and I, 5 bit nibbles are just a bad idea no matter what symbols you use, and this is a good enough reason to prefer either 9-bit bytes (three octal digits) or 12-bit bytes (four octal or three hex digits).
by classichasclass | 2025-08-07 22:07:38+00:00
I remember the first patient I put on exenatide, years ago. She was a diabetic that was very brittle and we were having trouble managing it, and I said it was worth a try and she agreed. "It might even cause a bit of weight loss, which I'm sure you won't object to," I said, which we had a good laugh over.

She lost 10 pounds and a whole point off her A1c. And that was just the first of the drug class. She was very pleased with it.

Also, pedantic nitpick: the anglerfish in the photo is female.
by hnlmorg | 2025-08-07 22:07:39+00:00
There’s a lot of other variables at play for humans. Like

- the need to sleep for 1/3 of our life

- the need to eat, causing more pauses in work

- much slower (like several orders of magnitude slower) data input capabilities

- lossy storage (aka forgetfulness)

- emotions

- other primal urges, like the need to procreate
by nullc | 2025-08-07 22:08:48+00:00
There is a lot more audio codecs embedded in other things than there ever were personal music players, by orders of magnitude. Vorbis was ubiquitous in video games, for example.

Personal music players had the issue that they had to have MP3 due to market forces, so offering Vorbis didn't save them any money. There were also some design decisions in Vorbis that made it a little more annoying to support on some very limited hardware than MP3.
by CamperBob2 | 2025-08-07 22:08:59+00:00
Right now nothing affects the underlying model weights. They are computed once during pretraining at enormous expense, adjusted incrementally during training, and then left untouched until the next frontier model is built.

Being able to adjust the weights will be the next big leap IMO, maybe the last one. It won't happen in real time but periodically, during intervals which I imagine we'll refer to as "sleep." At that point the model will do everything we do, at least potentially.
by apatheticonion | 2025-08-07 22:09:04+00:00
I daily drive Linux and deeply appreciate the fact that pretty much everything (at least in the DE space) is developed for free by people donating their time - so don't take this the wrong way.

...but I've yet to experience the level of DE stability you get from Windows XP/7

That also applies to Windows 11 (low bar, I know) and MacOS.

It is getting much better and that's happening very quickly - but there is always some jank.

For instance, dragging a Chrome tab off the current window to create a new window. The various file managers in Linux (dolphin, files, thunar) fall short (also MacOS Finder is an actual joke).

Also matching glibc versions when distributing software is a bit tedious
by DaveZale | 2025-08-07 22:09:15+00:00
Well, I for one am still alive. I know this, because I feel the pain in Gaza. I have compassion for persecuted Gaza ns.

I can guarantee you that AI has no clue what is happening in Gaza, because ths media is not allowed there.

And AI has no clue what has been happening in my garden either. I have never seen vegetables grow like this before, with sustained record heat.

AI is clueness about what matters to some of us.
by sshine | 2025-08-07 22:09:39+00:00
It is incredibly difficult to assess the quality of projects in depth.

I tried doing this for Open-VSX extensions for handling justfile:

https://open-vsx.org/?search=justfile&sortBy=relevance&sortO...

2.4k nefrob.vscode-just 2.5k kokakiwi.just 3.4k skellock.just 0.3k wolfmah-vscode.just-syntax

Go by number of downloads? skellock's extension wasn't updated in 5 years, is marked archived on GitHub, and doesn't accept any fixes (and there's a handful of reported problems that could use fixing). So while its README suggests that it once had a lot of effort put into it, it's not the choice that will grow with you.

kokakiwi's has nextmost downloads, but its website and git repository is self-hosted on a site that was gone since December 2020, so also 5 years of staleness. I suppose that's another way to archive your extension.

nefrob's has fewer downloads yet, but got a single 5-star review (Open-VSX doesn't have a lot of active users), the GitHub repo was updated 3 months ago, and it seems alive. Also, the parser itself seems simplistic and admits to not get things perfect.

wolfmah's has been inactive for more than one year, and it contains a single commit.

It was even less obvious with Typst: There are 12 results for the keyword "typst", and the leading extension didn't have many downloads at all -- I can see now that it's #2 for downloads.

Altogether, downloads / stars / reviews are a great way to get an honest answer in many cases when there aren't commercial interests at play, since there are fewer incentives to game metrics.
by Bender | 2025-08-07 22:10:18+00:00
wow your threat model is very different to me

If what you mean is that you have no online accounts then you are a few steps ahead of me. I will get there eventually but have some things to take care of first. Congrats on disconnecting from the internet though. I assume this site is your last holdout? I am envious if so. This site will also be my last online presence.
by 01HNNWZ0MV43FF | 2025-08-07 22:10:25+00:00
Flirting maybe, but I don't see clear racism.

> The large difference between sub-Saharan Africans in developed countries (eg the US) and in sub-Saharan Africa demonstrates that the latter aren’t performing at their genetic peak, and that developmental interventions - again, nutrition, health care, and education - are likely to work.

If I go to this blogging thing I'll tell him that the time for being a "grey party" enlightened centrist was about 20 years ago and it's a stupid act to keep up. Just say you're not racist. (Unless he's actually able to deprogram any racists, which I'd need data to believe)
by stouset | 2025-08-07 22:10:37+00:00
You are describing events that lasted for a handful of years and comparing them with a total and indefinitely-sustained global halting of economic growth.

Energy growth is physically bounded and so must stop (on a surprisingly near timescale). Economic growth can continue for a bit with efficiency improvements and other blood-from-a-stone extraction, but is ultimately bounded by energy growth so also must stop soon thereafter. For quite literally forever.

I'm not sure how to continue this discussion if you cannot understand how fundamentally unlike one-another these two situations are.
by toofy | 2025-08-07 22:10:47+00:00
yep, there’s a reason these people start their businesses in stable economied countries, yet certain groups of them do everything to pretend they owe nothing back.

i’d love to see a comprehensive study on how much corporate tax avoidance costs a country vs food stamps so we can get an accurate view on who leeches/gains more. my suspicion is corporate wage theft/tax avoidance/evasion/subsidies are significantly higher, particularly if we add in executives and major stock holders.
by jdelman | 2025-08-07 22:11:18+00:00
Whenever OpenAI releases a new ChatGPT feature or model, it's always a crapshoot when you'll actually be able to use it. The headlines - both from tech media coverage and OpenAI itself - always read "now available", but then I go to ChatGPT (and I'm a paid pro user) and it's not available yet. As an engineer I understand rollouts, but maybe don't say it's generally available when it's not?
by MrGilbert | 2025-08-07 22:11:19+00:00
As a side note: With the Internet (and myself) getting older and older, I appreciate the effort of the Internet Archive more and more. So many links I was able to revive thanks to a cached version. So many of my own works I was able to retrieve. It's a blessing, and not praised enough.

(Only ignorant fools would start to fight it.)
by torginus | 2025-08-07 22:11:28+00:00
My personal belief is that we are moving past the hype and kind of starting to realize the true shape of what (LLM) AI can offer us, which is a darned lot, but still, it only works well when fed the right input and handled right - which is still a learning process ongoing on both sides - AI companies need to learn to train these things into user interaction loops that match people's workflows, and people need to learn how to use these tools better.
by timr | 2025-08-07 22:11:32+00:00
I’m not “missing” it. I’m just not fixated on it.

The answer got all of the following correct:

* lift is created by pressure differential

* pressure differential is created by difference in airspeed over the top of the wing

* shape of the wing is a critical factor that results in airspeed difference

All of those are true, and upstream of the thing you’re arguing about.

The answer is not wrong. It’s not even “mostly wrong”. It’s mostly correct.
by potatolicious | 2025-08-07 22:11:43+00:00
It can, but I remain deeply unconvinced that the sub-agent architecture works as well as advertised.

The trick with any layering like this is that your end-to-end reliability is subagent_reliability * routing_agent_reliabilitty. Neither are 100% (or anywhere close to it, let's be honest), so the multiplying probabilities are still going to trash your performance.

If you get routed to the correct subagent, then subsequent performance is likely to be solid - but that's because you've taken the `routing_agent_reliability` term out of the equation.

Routing agent reliability hinges pretty heavily on the subagents themselves and how semantically or linguistically similar they are. If you have subagents that are in wildly disparate domains it may work well, but if your subagents start overlapping (or just look like they overlap) then routing accuracy is likely going straight into the dumpster. And a mis-route is catastrophic in that setup.

For very specific agents (well-established workflows that cross multiple, well-defined, non-overlapping domains) the architecture may be suitable, but in terms of the holy grail of the omni-agent (i.e., a desktop app agent suitable for general use) I suspect we'll continue running into a brick wall.
by MiddleEndian | 2025-08-07 22:11:45+00:00
It's never truly guaranteed and the numbers aren't quite one account per day at 125k accounts, but:

10^6 digits = 1,000,000 possibilities

125,000 accounts x 4 attempts per account per day = 500,000 attempts per day

---

1-(1-1/1,000,000)^500,000 ≈ 39%

So every day they have a roughly 39% chance of success at 125,000 accounts.

---

At a million accounts:

1-(1-1/1,000,000)^(4×1,000,000) ≈ 98%

Pretty close to 1 account per day

Off by a factor of 4 but the concept stands.

---

And 125k accounts will be close to guaranteed to getting you one each week:

1-(1-1/1,000,000)^(7×4×125,000) ≈ 97%