MurphyA/hacker-news huggingface dataset:
by rmunn | 2025-10-27 02:48:52+00:00
I've seen one blog where in order to comment, you have to answer the question "What color is a green orange?" I presume he gets spambots which all answer "orange" and get blocked from commenting, or more commonly which leave that input blank (since it's a non-standard input field) and also get blocked.

But it just occurred to me that you could ask "what color is a green eggplant?" for a similar result. Though you'd catch a lot of people who, like me before I looked up fruits that aren't green when unripe, assume that all unripe fruits are green. (They aren't, unripe eggplants are white and look like eggs, hence the name).
by AdieuToLogic | 2025-10-27 02:51:38+00:00
>> Without cloud, saving a file is as simple as "with open(...) as f: f.write(data)" + adding a record to DB.

> Save where? With what redundancy? With what access policies? With what backup strategy? With what network topology? With what storage equipment and file system and HVAC system and...

Most of these concerns can be addressed with ZFS[0] provided by FreeBSD systems hosted in triple-A data centers.

See also iSCSI[1].

0 - https://docs.freebsd.org/en/books/handbook/zfs/

1 - https://en.wikipedia.org/wiki/ISCSI
by jeromegv | 2025-10-27 02:52:16+00:00
His views on women:

In November, Argentina was the only country to vote against a UN general assembly resolution to prevent and eliminate violence against women and girls. Two months later, Milei’s administration went further, pledging to strike the aggravating factor of femicide, defined as when a woman dies at the hands of a man on the basis of her gender, from the penal code – a move that drew swift condemnation from human rights groups
by johnnyanmac | 2025-10-27 02:52:47+00:00
You'd be correct in an economy not tumbling towards recesssion due to said tarrifs being universal, and not just focusing on specific industries to make american ones more competitive.

As it is, American spending is way down and hurts everyone. A small stock crash (the thing propping the US up as of now) would truly hit with a 2nd depression at this point.
by jasonboyd | 2025-10-27 02:53:25+00:00
I agree they are deadly serious, but to the parent commenter’s point, why wander the streets grabbing random people when they could go straight to the employers? They would have far more success targeting farms, construction sites, restaurant kitchens, etc.

The answer is the business owners are their constituents. They cannot afford to piss them off. If they lose their support the wheels will fall off this farcical performance.

I grew up in Florida, and I remember the sugar plantation “raids” they used to stage. They were a complete dog and pony show. They would announce them in advance so the plantations could hide most of their undocumented workers. Then they would round up just enough people for the photo op to prove they were being “tough on immigration.”

This is the same thing but on a grander and more dangerous scale.
by sparky_z | 2025-10-27 02:53:26+00:00
Yeah, no shit. But, come on, don't play dumb. By measurable, I obviously meant "above normal background". Something that shouldn't have been possible if, as described in the xkcd post, the water should have had less radioactivity than normal background. Combined with the fact that the post was literally about a different kind of pool than the one involved in the accident, it was reasonable to question whether the post was actually relevant.

I agree this was not a serious incident, and I never really though it was. (I'm extremely pro-nuclear, for the record.) But at the time I posted, the comment section was about 8 people posting the xkcd link at once (with no additional commentary), and few others reading it and saying "oh, no problem then", with literally nobody pointing out the discrepancies, or explaining exactly what a "reactor cavity" means in this context.
by maurycyz | 2025-10-27 02:54:36+00:00
> The client can still send a flood of correctly-formed requests

This is possible with any server. It's a known exploit and very difficult to fully mitigate: https://en.wikipedia.org/wiki/Denial-of-service_attack Whatever you do, they can always overwhelm your network connection.

And yes, there is inherent risk with exposing any service to the internet. That goes for any program, written in any language (remember Log4Shell?) doing any task.
by theaniketgiri | 2025-10-27 02:54:41+00:00
To clarify the AI question once and for all:

What AI did: - Generated README templates (boilerplate markdown) - Suggested commit messages (I didn't always edit them) - Helped with documentation structure

What I wrote: - All Python training logic (train.py, trainer.py, callbacks) - All model architectures (gpt.py, tiny.py, small.py, etc.) - Tokenizer integration - Data pipeline - CLI scaffolding (
by _heimdall | 2025-10-27 02:55:07+00:00
What you describe sounds more like industrial farming than tricks played by third world farmers (whatever that means).

Industrial ag regularly treats product to modify the texture, color, and shelf life. Its extremely common to expose produce to various gases and chemicals to either delay or hasten ripening, for example. Other tricks are used while the plants are still in the ground or immediately after harvest, for example spraying grains with roundup to dry out more quickly.
by rmunn | 2025-10-27 02:55:21+00:00
The Turing test was never a test of thinking: Turing said that thinking was difficult to define and so he decided to "replace the question by another, which is closely related to it" (I disagree with him there) "and is expressed in relatively unambiguous words," i.e. the question of whether a chatbot can fool a text-only observer into thinking it's human.

Clearly, current LLMs have passed the Turing test, as witnessed by the difficulty many schools have in enforcing "do not use LLMs to do your homework" rules. But even Turing didn't say his test was a test of intelligence, just a test "closely related" to intelligence. And if he had seen today's LLMs, I think he would have revised that opinion, because today's LLMs generate text with no underlying fact model, no fundamental understanding of the truth behind the words they're saying. (No understanding, even, of the concepts of truth or falsehood). I think today's LLMs have demonstrated that being able to string words together in coherent sentences is not "closely related" to intelligence at all.
by theaniketgiri | 2025-10-27 02:57:05+00:00
Good question! I think you mean nanoGPT (Karpathy's minimal GPT implementation)?

Key differences:

nanoGPT: - Minimal reference implementation (~300 lines) - Educational code for understanding transformers - Requires manual setup and configuration - Great for learning the internals

create-llm: - Production-ready scaffolding tool (like create-next-app) - One command: npx create-llm → complete project ready - Multiple templates (nano/tiny/small/base) - Built-in validation (warns about overfitting, vocab mismatches) - Includes tokenizer training, evaluation, deployment tools - Auto-detects issues before you waste GPU time

Think of it as: nanoGPT is the reference, create-llm is the framework.

nanoGPT teaches you HOW it works. create-llm lets you BUILD with what you learned.

You can actually use nanoGPT's architecture in create-llm templates - they're complementary tools!
by pcfwik | 2025-10-27 02:57:26+00:00
I once considered Wren for a situation where I (to a first approximation) wanted to allow users to write 'plugins' that link against my internal C application symbols but using a language focusing more on ease of use (rather than C).

Unfortunately, neither Wren nor any of the other major 'embeddable scripting languages' (e.g., Lua) were really a good fit for this, because they commit fully to the 'all-numbers-are-floats' thing and generally don't seem to even try to provide a general equivalent to the C++ `extern "C" { ... }` thing.

Of course, I know this isn't really the target use case of Wren/Lua/etc., but if anyone knows of a good embeddable scripting language for this I'd love to hear about it. Eventually I went with CPython (which provides ctypes to solve my problem) but it's a huge pain to embed properly.
by johnnyanmac | 2025-10-27 02:58:09+00:00
That's how it works right now. Besides Trump, the US's last presidental impeachment was over a sex scandal. They "say" it was because he lied about it, but I think we know better at this point. It's just really hard to impeach because you need 66 or 67 of the Senate to agree on something, not the usual 51.

But yes, we'd need some truly neutral Ombudsmen to back up such a system. And they themselves would need to be accountable should they corrupt. I don't think it's impossible, but hard to do with the current power structures.
by m463 | 2025-10-27 02:58:35+00:00
I focus a lot on 4k, bluray and dvds. Shuffling physical media is nice.

Small used cd/dvd stores like rasputin are a delight.

If life gets busy, you pause without racking up subscription fees.

Also - there is something deliberate about choosing and watching a movie physically. You buy it deliberately, and later you play it more deliberately.

When I had netflix, I could spend the time to watch a movie doomscrolling through not-that-great stuff to not watch.
by Forgeties79 | 2025-10-27 02:59:46+00:00
> Not all content needs to be real. A huge portion of what humans appreciate is fiction.

Yes but that’s deliberately fiction and I know I am reading fiction. AI hallucinations are not comparable to deliberately created works of fiction. I don’t “appreciate” the fiction LLM’s serve me. They are explicitly sold as a utility, as a source of accurate information. They are literally being used to replaced google search.

Put another way: When someone claims something is true but speaks fiction it’s called a lie. If they think it’s true but are wrong it’s called a mistake. If I ask someone what is wrong with my car I don’t want 30% fiction. If I ask an LLM for a recipe I don’t want 70% accuracy.
by airstrike | 2025-10-27 03:00:30+00:00
> Not being able to easily conjure one was one of the biggest annoyances when I was forced to switch from macOS to windows.

I always install AutoHotkey if I have to use Windows for long periods of time. Interestingly, the bindings are so intuitive that I had actually come up with the _exact same_ bindings as macOS without knowing they existed. Imagine my surprise when I switched to a mac and found out they were there natively!
by photonthug | 2025-10-27 03:00:30+00:00
Hah, tools-or-no does make things interesting, since this opens up the robot tactic of "use this discord API to poll some humans about appropriate response". And yet if you're suspiciously good at cube roots, then you might out yourself as robot right away. Doing any math at all in fact is probably suspect. Outside of a classroom humans tend to answer questions like "multiply 34 x 91" with "go fuck yourself", and personally I usually start closing browser tabs when asked to identify motorcycles
by chrsw | 2025-10-27 03:01:03+00:00
I think a lot of this is all backwards. People think AGI is taking something dumb, like an LLM, and sticking on learning, like a software upgrade.

I think it's the other way around: you build a system that first and foremost _learns_ as part of its fundamental function, _then_ you train it in the domain you want expertise.

You're not going to get expertise in all domains all the time, just like with people. And you're not going to get a perfect slave either, just like with humans. You'll probably get something more like in between a human and machine. If that's what you really want, great.

To put this another way, if you neglect your kids, they're still going to learn things, just probably not things you want them to learn. If you neglect your language model it's just not going to do anything.
by Animats | 2025-10-27 03:02:53+00:00
> Well, all the cool kids were apparently doing "Deep space radar telemetry" :)

(Those guys were around. I worked at a location in Silicon Valley which had a 20 meter steerable dish in the parking lot, the prototype for others around the world.

The Colorado Springs guys were trying to migrate off the DEC PDP-11 to some kind of microprocessor. The PDP-11 (16 bit address space) was very popular with the USAF/intel crowd. Making add-ons and plugging them into the bus was a fully documented and supported procedure, not a hack. DEC sold all the parts needed for that. The usual setup was one or more PDP-11 machines connected via a custom interface to something exotic. In the early 1980s, it was time to go to a microprocessor. But what?

They picked the Zilog Z-8000 [1], because it was the closest thing to a PDP-11. That turned out to be a dead end, but the aerospace company was already building custom interface hardware that talked to it, so they were stuck for the duration of separate projects. Did not end well. At one point I did get TCP/IP onto a pair of Z-8000 based Oynx machines, which were for a brief period the lowest cost UNIX boxes.)
by cauliflower2718 | 2025-10-27 03:05:32+00:00
My example is asking for way less than what you're asking for.

Here is something I do not see with reasonable humans who are cooperative: Me: "hey friend with whom I have plans to get dinner, what are you thinking of eating?" Friend: "fried chicken?" Me: "I'm vegetarian" Friend: "steak?"

Note that this is in the context of four turns of a single conversation. I don't expect people to remember stuff across conversations or to change their habits or personalities.

Your goalpost is much further out there.
by qudat | 2025-10-27 03:05:33+00:00
> LLMs are a more complex and expensive trick

The more I think about this, the more I think the same is true for our own intelligence. Consciousness is a trick and AI development is lifting the veil of our vanity. I'm not claiming that LLMs are conscious or intelligent or whatever. I'm suggesting that next token prediction has scaled so well and cover so many use cases that the next couple breakthroughs will show us how simple intelligence is once you remove the complexity of biological systems from the equation.

https://bower.sh/who-will-understand-consciousness
by mindslight | 2025-10-27 03:06:49+00:00
Dear Leader has already been talking about instituting some kind of program to formally permit cheap imported labor in "critical" industries like farming, construction, and landscaping. And why would the regime ever want to fix any root causes? Pournelle's iron law of bureaucracy applies to autocracies as well. The Republican party has been drumming up support on this bogeyman for decades. Remember when there was a bipartisan immigration bill up for vote before the election and Tramp insisted that it be killed? That's the fundamental dynamic right there - their cultists crave human suffering, not effective policy.
by k310 | 2025-10-27 03:06:52+00:00
Where will we go when goatse.cx is down?

> Configuring goatse relaunch 2025...

> @goatsedotcx

> $goatse

> 4f9Nc1vPWvcbGP9Zfi6TWD9tApyMgBrqmXexNZnR4Wmo

Is this the answer?
by rpdillon | 2025-10-27 03:07:18+00:00
Generally, I don't advocate for code getting thrown over the fence, regardless of the dynamics associated with the particular exchange. So the ideal approach here would be for the CTO to partner with a trusted engineer with some leadership capacity (tech lead, staff, etc.) and work through the architecture design and technical specifications for the project and get it off the ground and then hand that off to the tech lead that they partnered with so that they could carry it over the line, possibly with a team. Understanding the vision behind the project and why the CTO thought it was valuable is a critical aspect here. It turns what would otherwise be a low leverage project, mostly involving architecture and coding, into a much higher leverage project that's focused on educating and empowering other leaders in the organization. It also allows the CTO to stay close to the technical foundations and code so they don't lose touch with the organization that they're leading.
by lotsoweiners | 2025-10-27 03:07:47+00:00
Youtube premium is like $15/mo. I believe it was more for the family plan I used to have. I canceled it like a year ago and don’t feel I miss it at all. I just don’t think Google is a company I should ever give money to directly. If some 3rd party service blocked YouTube for $15/mo I’d be more inclined to pay them vs Google.
by famouswaffles | 2025-10-27 03:08:01+00:00
>I could walk into a club in Vegas, throw down $10,000 cash for a VIP table, and start throwing around $100 bills.

If you can withdraw $10,000 cash at all to dispose as you please (including for this 'trick' game) then my friend you are wealthy from the perspective of the vast majority of humans living on the planet.

And if you balk at doing this, maybe because you cannot actually withdraw that much, or maybe because it is badly needed for something else, then you are not actually capable of performing the test now, are you ?
by bobbylarrybobby | 2025-10-27 03:08:42+00:00
Could this really invalidate research? Managing to produce a model that works (assuming you check all of the myriad modeling correctness checkboxes) is sufficient on its own. The fact that the modeling process itself was broken in some way — but not the assumptions made of the model inputs, or data leakage assumptions, or anything that fundamentally undermines any model produced — has no bearing on the outcome, which is the fact that you got a model that evidently did make accurate predictions.
by spot | 2025-10-27 03:09:08+00:00
> Last, we deliberately focus on core cognitive capabilities rather than physical abilities such as motor skills or tactile sensing, as we seek to measure the capabilities of the mind rather than the quality of its actuators or sensors.

seems pretty unfair to exclude motor skills, especially given 1) how central they are to human economic activity, and 2) how moravec's paradox tells us they are the hard part.
by jonway | 2025-10-27 03:09:10+00:00
There are plenty of very, very good EV out there, have been for years but those other automakers are already servicing shareholders with pretty reliable profits.

As a result they just treat ev and hybrids like any other model for the most part wrt marketing and so forth. It’s understandable that you wouldn’t want to cannibalize regular sales and service. Financially, they don’t need to. It does help their CAFE fleet standards.

It doesn’t make as much sense for Toyota since they have some of the segment (economical or environmental buyers) covered by Camry and Prius, which they’ve been making for like 30 years.

As for “why should cars change every 3 years”, well, they don’t.

Other automakers typically develop a platform and use it as a base for many models over several to many years.

Mercedes-Benz platforms have lasted over a decade, encompassing many badges. GM make Escalades and Yukons, they are the same platform with different options.

There is a sure benefit of Tesla: competition in the EV space, since they had no product to match GM.

Just an aside, electric cars aren’t even close to new, Tesla was not first to market. They were pretty popular 120 years ago, but clearly things change.
by rmunn | 2025-10-27 03:09:20+00:00
I would argue that current LLMs are passing the Turing test because many observers have a hard time distinguishing them from humans: just look at the difficulty many schools have in enforcing rules like "Not allowed to use LLMs for your homework". The teachers often (not always) can't tell, looking at a piece of text, whether a human produced it or whether ChatGPT or some other LLM produced it.

And that "not always" is the crux of the matter, I think. You are arguing that we're not there yet, because there are lines of questioning you can apply that will trip up an LLM and demonstrate that it's not a human. And that's probably a more accurate definition of the test, because Turing predicted that by 2000 or so (he wrote "within 50 years" around 1950) chatbots would be good enough "that an average interrogator will not have more than 70% chance of making the right identification after five minutes of questioning". He was off by about two decades, but by now that's probably happened. The average interrogator probably wouldn't come up with your (good) strategy of using counterfactuals to trick the LLM, and I would argue two points: 1) that the average interrogator would indeed fail the Turing test (I've long argued that the Turing test isn't one that machines can pass, it's one that humans can fail) because they would likely stick to conventional topics on which the LLM has lots of data, and 2) that the situation where people are actually struggling to distinguish LLMs is one where they don't have an opportunity to interrogate the model: they're looking at one piece of multi-paragraph (usually multi-page) output presented to them, and having to guess whether it was produced by a human (who is therefore not cheating) or by an LLM (in which case the student is cheating because the school has a rule against it). That may not be Turing's actual test, but it's the practical "Turing test" that applies the most today.
by lysp | 2025-10-27 03:10:35+00:00
The ACCC is actually quite switched on to any misleading conduct.

They have gone after Airbnb / Airlines / Hotel Booking / Concert Tickets - for misleading conduct.

Especially business that use drip pricing (adding compulsory hidden fees later) or misleading prices like in the Microsoft case.

Anything sneaky - they're normally right on to it.
by dbigge | 2025-10-27 03:10:39+00:00
Hi all — long time lurker…first-time poster here.

I’ve been following the discussion around Bitcoin Core v0.30 and the increased OP_RETURN relay size (~80 bytes → ~100 KB), along with the growing interest in Bitcoin Knots’ more conservative policy stance.

At first the debate looked like a simple question of: • Should Bitcoin block space be “money-only,” or • Should it allow arbitrary data as long as fees are paid?

But after hearing from both sides, I’m wondering if this debate is actually about something deeper than either side is presenting.

Nick Szabo wrote in Money, Blockchains, and Social Scalability (2017):

Social scalability is the ability of a system to support widespread human cooperation while minimizing the need for trust, negotiation, and discretionary judgment.

Bitcoin’s original design deliberately limited expressiveness and also used a slow database with inefficient network protocols…all in order to maximize social scalability — i.e., fewer reasons to argue about over globally.

So here’s the question I’m wrestling with:

Does expanding OP_RETURN and encouraging more arbitrary data use widen Bitcoin’s “sphere of purpose” in a way that reduces its social scalability?

Put differently: There seem to be two interpretations of what expanding OP_RETURN implies, and both have tradeoffs: • One interpretation is that a fee-based, permissionless market for block space keeps Bitcoin maximally neutral. If someone is willing to pay, that is the filtering mechanism (along with node policies).

This preserves the principle that Bitcoin does not distinguish “good” vs. “bad” data or actors. • The other interpretation is that broadening acceptable on-chain content expands the legal and social attack surface.

Since block space is permissionless, anyone — including adversarial or politically motivated actors — can embed material intended to provoke regulatory pressure or create social fracture.

I’m not taking a side — I’m trying to figure out what the right frame of analysis is.

Questions for the community: 1. Is purpose drift a real threat to Bitcoin’s social scalability as Nick’s blog suggests? 2. Can fee-market neutrality alone preserve coherence of purpose? 3. Has any decentralized system successfully stayed socially scalable while expanding its expressive surface area? BCH forked to BSV and ETC forked to ETH.

I’d appreciate high-signal perspectives — especially from those who’ve worked in: • distributed systems/security, • protocol governance, • or followed previous “purpose shift” debates in open networks.

Thanks for reading.