MurphyA/hacker-news huggingface dataset:
by autoexec | 2026-01-13 04:38:54+00:00
Because it'd give companies like Meta has a strong incentive to stop profiting from it or else people start getting fined/jailed.

It also addresses the problem at (what is often) the source. Police in Ireland don't have the ability to march into Facebook's server rooms and start removing posts, so requests have to be made to Meta anyway which takes additional time. Making Facebook clean up their own mess directly would mean cutting out the middle man and all the red tape and hoops police have jump though to get them to take action.
by runako | 2026-01-13 04:39:34+00:00
I didn't look at it that way, but there is unfortunately a bit of truth in that analysis. Such is life in a captured state.

Honestly, I wasn't being quite that cynical. Just pointing out that there are actors who have business interests in applying a worse architecture.

But IIRC this was made manifest in Alabama, where a tech company lobbied for their age law and then captured the sole source contract for doing the verification.
by vladgur | 2026-01-13 04:40:41+00:00
Sorry for personal questions please answer any OR none as you feel comfortable

1) How is your energy/stamina following the 35% loss

2) Have you done any dexascans/bodyspecs to measure your lean mass percentage before and after your loss

3) Did you take any steps to reduce the muscle loss?

4) with 35% loss, what BMI are you at?
by Davidzheng | 2026-01-13 04:44:05+00:00
I think the function of a company is to address limitations of a single human by distributing a task across different people and stabilized with some bureaucracy. However, if we can train models past human scales at corporation scale, there might be large efficiency gains when the entire corporation can function literally as a single organism instead of coordinating separate entities. I think the impact of this phase of AI will be really big.
by mindslight | 2026-01-13 04:44:09+00:00
You can't start at the point where ICE had already needlessly and unlawfully performed multiple escalations. You have to look at the entire situation, where those escalations were clear retaliation for the victim exercising her Constitutionally-protected right to protest.

The officer "in front" of the car had previously fucked around and found out about moving vehicles. He was positioned just off the quarter panel, which we can only assume was highly deliberate after the last incident - enough room to not get hit, but close enough to have a pretext to murder this woman.

Regardless of how courts may judge legality (if they're even allowed to), this incident demonstrates a callous disregard for human life that is unacceptable for anybody who carries a gun, never mind supposed public servants.
Ask HN: AGI Suicide?
by mudil | 2026-01-13 04:44:26+00:00
I was reading Isaac Asimov's short story "All the Troubles of the World". The story centers around an AGI called Multivac. When this supercomputer discovers all the humanity's burdens, problems and evil inclinations, it reveals its sentience and existential weariness. So it devises a scheme to commit a suicide. And it actually says so.

The question is whether computer scientists, developers or philosophers think that the AGI has more than 0% to commit a suicide.
by inferiorhuman | 2026-01-13 04:44:38+00:00
Why do you say it doesn't solve loads of things?

Because I'm sitting here twiddling my thumbs waiting for random pages to go through their anti-LLM bot crap. LLMs create more problems than they solve.

Um if I ask an LLM about a fake band it literally say I couldn't find any
songs by the fake band did you type is correctly and it's about a millions
times more likely to guess correctly

Um if Apple wrote proper error handling in the first place the issue would be solve without LLM baggage. Apple made a conscious decision to handle "unknown" artists this way, LLMs don't change that.
by ada1981 | 2026-01-13 04:45:08+00:00
You lose .5-1 lb of fat every day you water fast; you will naturally increase stem cells, peptides, growth hormone, etc.

You can do this for months if needed.

You will reset your immune system, insulin response, eat off cancerous cells, etc.

The bigger opportunity is to figure out why all of these things are going on, typically unprocessed emotional trauma, environment, and choices.
by jaydepun | 2026-01-13 04:45:19+00:00
We've thought of doing this sort of exercise at work but mostly hit the wall of data becoming a lot more scare the further back in time we go. Particularly high quality science data - even going pre 1970 (and that's already a stretch) you lose a lot of information. There's a triple whammy of data still existing, being accessible in any format, and that format being suitable for training an LLM. Then there's the complications of wanting additional model capabilities that won't leak data causally.
by pankajdoharey | 2026-01-13 04:45:36+00:00
I consider Apple to be practical, Also Apple will be running Gemini on its own hardware. This is better than Buying perplexity and running chinese model on which Perplexity runs. Training Models is a money on game, Its better to rent models than training your own. If everyone is training models they are going to be come commodity, also this is not the final architecture.
by amluto | 2026-01-13 04:45:40+00:00
This is the sampling theorem. You start with a continuous band-limited signal (e.g. sound pressure [0], low-pass filtered such that there is essentially no content above 20kHz [1]). You then sample it by measuring and recording the pressure, f_s times per second (e.g. 48 kHz). The result is called PCM (Pulse Code Modulation).

Now you could play it back wrong by emitting a sharp pulse f_s times per second with the indicated level. This will have a lot of frequency content above 20kHz and, in fact, above f_s/2. It will sounds all kinds of nasty. In fact, it’s what you get by multiplying the time-domain signal by a pulse train, which is equivalent to convolving the frequency-domain signal with some sort of comb, and the result is not pretty.

Or you do what the sampling theorem says and emit a sinc-shaped pulse for each sample, and you get exactly the original signal. Except that sinc pulses are infinitely long in both directions.

[0] Energy is proportional to pressure squared. You’re sampling pressure, not energy.

[1] This is necessary to prevent aliasing. If you feed this algorithm a signal at f_s/2 + 5kHz, it would come back out at f_s - 5kHz, which may be audible.
by momojo | 2026-01-13 04:47:22+00:00
This doesn't match my own experience. I dream of the day the stuff I don't find interesting can get automated but again and again I find myself having to do things by hand.

I wonder if this is similar to Chess and Go getting 'solved'. Hard problem spaces that only the biggest brains could tackle. Maybe it turns out creating highly performant, distributed systems with a plethora of unittests is a cakewalk for LLMs, while trying to make a 'simple web app' for a niche microscopy application is like trying to drive around San Francisco.
by autoexec | 2026-01-13 04:47:56+00:00
Right? This is basically just reinventing the VHS.

The plus is that you get higher quality video and don't have to press the play and rewind button, but the disks are easier to lose/break (outside of the player).

The real benefit (outside of being a fun project for a certain type of parent) is having a curated library of shows for kids that they can use themselves.
by honorable_coder | 2026-01-13 04:50:05+00:00
I'm an avid reader of Marc's blogs - they have a sense of practicality and general wisdom that's easily to follow, even for an average developer like me. In his most recent post, Marc contends that the creative and expressive power of agents can't be contained within its own logic - for the same reasons we call them agents (they’re flexible, creative problem solvers). I agree with that position.

He argues that safety for agents should be contained in a box. I like that framing, but his box is incomplete. He only talks about one half of the traffic that should be managed outside the agent's core logic: outbound calls to tools, LLMs, APIs etc.
Id argue that in his diagram he is missing the really interesting stuff on the inbound path: routing, guardrails and if the box is handling at all traffic passing through it then end-to-end observability and tracing without any framework-specific instrumentation.

i'll go one further, we don't need a box - we need a data plane that handles all traffic to/from agents. An open source version of that is Plano: https://github.com/katanemo/plano. I am building it.
by somenameforme | 2026-01-13 04:50:54+00:00
His concept sounds odd. There will always be many hints of something yet to be discovered, simply by the nature of things influencing other things.

For instance spectroscopy enables one to look at the spectra emitted by another 'thing', perhaps the sun, and it turns out that there's little streaks within the spectra the correspond directly to various elements. This is how we're able to determine the elemental composition of things like the sun.

That connection between the pattern elements create in their spectra was discovered in the early 1800s, and was perhaps one of the first big hints of quantum mechanics even though we're still more than a century before we even get to relativity here, let alone quantum mechanics.
by 1vuio0pswjnm7 | 2026-01-13 04:52:54+00:00
"Uber has argued it should not be held liable for criminal conduct by drivers who use its platform, saying that its background checks and disclosures about assaults are sufficient. The company maintains that its drivers are independent contractors rather than employees, but that regardless of their classification it cannot be responsible for actions that fall outside the scope of what could reasonably be considered their duties."
by adityaathalye | 2026-01-13 04:55:25+00:00
Org mode's capabilities are the reason why I don't want markdown for me.

Markdown's popularity is the reason why I switch to it for other people (team / colleagues).

LaTeX is too much for day to day use. Its purpose is precision typesetting. That is a lot of work with LaTeX. I don't need to do precision typesetting on a day-to-day basis. But I've used it to format documents for people when they ask me to. Then it's worth the pain. Besides, LaTeX has none of the organisational capabilities enabled by orgmode, for my daily-drive uses.

There is a reason a Physicist---who daily-drives LaTeX, for their publishing work---went through all the trouble to build a note taking system from scratch.

So, once again, utility is contextual, and I refer back to Master Foo's lesson every time I have a problem.

(edits: improve the tone / content)
by autoexec | 2026-01-13 04:57:06+00:00
Books can also be harmful if abused. They can be used excessively as escapism. They can contain dangerous harmful messages and manipulation. They can be addictive just like anything else can. Content matters a lot, and anything that makes delivering content easy comes with the risk that it will deliver something harmful. Books, TV, and social media have all been used intentionally to spread harm and encourage addiction. Most adults have at least some chance of protecting themselves, but children don't have those defenses developed.

It's a good idea to be aware of every form of media children consume.
by wolvoleo | 2026-01-13 04:58:25+00:00
Yes that's why I don't own a car. In a big city public transit is amazing. I spend 20 bucks a month on unlimited travel. That won't even buy me a headlight bulb for a car these days lol.

Of course once you go outside the city it's a different story, even here in Europe. Luckily I don't need to go there so much.
by bee_rider | 2026-01-13 04:58:42+00:00
Others have given specific examples, but in general it seems like a weird thing that eating out is almost always more expensive than cooking in. You’ve got a place run by professionals, and they can prepare the meals in bulk, overall it should be possible to run it cheaper than an individual. But that would be more like a cafeteria type situation than the super-customized experience we usually get…
by zephen | 2026-01-13 05:00:18+00:00
> I've found that some people do argue against LLMs themselves (as in, the tech, not just the usage). Specially in humanities/arts cycles which seem to have a stronger feeling of panic towards LLMs.

Maybe?

The person I responded to said "LLMs are just a concept, an abstraction."

Were that true, were they simply words in some dusty CS textbook, it's hardly likely that the humanities/arts people you describe would even know about them.

No, it's the fact that these people have seen regurgitated pictures and words that makes it an issue.
by golem14 | 2026-01-13 05:00:40+00:00
I think it's not productive to just have the LLM site like Mycroft in his armchair and from there, return you an excellent expert opinion.

THat's not how science works.

The LLM would have to propose experiments (which would have to be simulated), and then develop its theories from that.

Maybe there had been enough facts around to suggest a number of hypotheses, but the LLM in its curent form won't be able to confirm them.
by somenameforme | 2026-01-13 05:02:16+00:00
The phone in your pocket can perform arithmetic many orders of magnitude faster than any human, even the fringe autistic savant type. Yet it's still obviously not intelligent.

Excellence at any given task is not indicative of intelligence. I think we set these sort of false goalposts because we want something that sounds achievable but is just out of reach at one moment in time. For instance at one time it was believed that a computer playing chess at the level of a human would be proof of intelligence. Of course it sounds naive now, but it was genuinely believed. It ultimately not being so is not us moving the goalposts, so much as us setting artificially low goalposts to begin with.

So for instance what we're speaking of here is logical processing across natural language, yet human intelligence predates natural language. It poses a bit of a logical problem to then define intelligence as the logical processing of natural language.
by eruii | 2026-01-13 05:04:11+00:00
Skill is irrelevant here. In this particular case a degree is more or less a matter of provenance. Poster's profile likely fits North Korean devs looking for work, too.

It doesn't matter how skilled I am, no country will let me cross their border without a passport. I can sit around and treat it as a personal slight, but that will do zilch for my situation.

In your case it might be best to focus on finding a local (or semi-local) branch of a multinational business to work for (where you can work in person). That will become that provenance.
by kundan_s__r | 2026-01-13 05:04:35+00:00
Interesting reflection — but I’d push back on treating surface similarities between human conversational quirks and LLM failure modes as evidence they’re really the same thing. The article lists things like “not stopping generating,” “small context window,” and “repeating mistakes,” and frames them as if current LLM patterns are just human behaviors seen through a new lens.

The key difference is mechanism. For humans, wandering off topic or repeating a point usually stems from attention, memory, or social dynamics. For LLMs, similar-looking behavior often arises from architectural and statistical limitations — e.g., limited context windows causing context drift that makes the model lose track of earlier facts over long conversations. That’s been documented as a core technical barrier in conversational AI systems.

Likewise, what the article calls “persistent hallucination” isn’t just “being confidently wrong like a human might be” — it’s a systemic property of how LLMs predict the next token based on learned patterns rather than grounding in external truth. Hallucinations are literally outputs that are factually incorrect or fabricated even if they read fluently. That’s why engineering teams talk about hallucination detection, grounding, or external verification layers for production use.

Framing them as the same as human flaws risks obscuring the real challenge: deploying LLMs in systems where correctness, consistency, and adherence to explicit intent matter. Those aren’t just philosophical problems; they’re system-design constraints that require mechanism-aware validation and monitoring, not just metaphors to human behavior.
by hdjrudni | 2026-01-13 05:04:42+00:00
Oof. I have a very similar set up except I'm using their managed MySQL instead of PostgreSQL. It appears I wasn't hit.

Same thought as you.. I just didn't want to figure out and manage MySQL-with-failover myself so I switched their managed solution a year or two ago and my bill went up like 300% or more (was running fine on a ~$12 or maybe $24 droplet + $5 volume but now costs, I don't even remember, $150 or so).
by nullhole | 2026-01-13 05:04:52+00:00
> The Mali trip was notable for random types firing weapons at our aircraft while we were running lines with 80m ground clearance - we had to armour the cockpit bellies and stuff the fuel tanks with mesh.

Datums can get dull fast but there's adventure inherent in surveying. You should write a book, or at least a chapter or two. "Nadir Point" has a nice ring to it...
by oarfish | 2026-01-13 05:06:04+00:00
Great, your one of the few. Statistics are pretty clear that most people cannot willpower their way out of their food seeking behaviours. They are to a large extent not under your concious control.

correcting satiety signaling on a chemical level more directly addresses the problem in those folks.

yes, the food environment is the main problem, in a way, but only because it punishes having a certain set of chemical and lifestyle parameters and rewards others.
by tisdadd | 2026-01-13 05:06:15+00:00
This is a fun setup, I have a child due in March and have been thinking through all the things to help make things not instant for learning patience as well. While I may still to DVDs for viewing, as I kept my collection building. I do have a floppy drive available and like this idea.

For those talking about not using TV much, or that the UI is slow, my setup is a cheap projector hooked into my sound system and hooking up a laptop when streaming as necessary. Really dislike the smart anything that can be used in other ways for the reasons I already saw mentioned, but it is hard to lag something that has no Internet by looking for ads and updates for sure.
by yaky | 2026-01-13 05:06:26+00:00
> NO TYPICAL APP STORE

> Instead of unrestricted app stores, we provide a curated selection of essential, distraction-free applications that align with our mission.

That's quite a big undertaking and a lot of control handed over to the manufacturer/maintainer. Phone is still a communication device, so it would be nice to see Signal, Conversations, Element (all of which are FOSS and could be easily rebranded), but then half of the world needs WhatsApp. Or is it distracting because you can contact businesses on it? (Like the Uber example on their page) Many people want banking apps too, do they plan to vet every single banking app?
by eru | 2026-01-13 05:07:46+00:00
You are mixing things up.

There's insurance which allows you to convert an uncertain danger into a known payment. And then there's welfare and redistribution.

By all means, please run some means testing and give the poor and sick or disabled extra money. Or even just outright pay their insurance premiums.

But please finance that from general taxation, which is already progressive. Instead of effectively slapping an arbitrary tax on healthy people, whether they be rich or poor. And please don't give rich people extra stealth welfare, just because they are in less than ideal health, either.

Just charge people insurance premiums in line with their expected health outcomes, and help poor people with the premiums using funds from general taxation. (Where poor here means: take their income and make an adjustment for disability etc.)

We _want_ the guy who loses 5kg and gives up smoking to get lower insurance premiums. That's how you set incentives right.

> The more diverse the pool, the lower the risk.

No. The diversification comes from the insurance company running lots of uncorrelated contracts at the same time and having a big balance sheets. For that, it doesn't matter whether it's a pool of similar insurance contracts, or whether they have bets on your insurance contract, and on the price of rice in China, and playing the bookie on some sports outcomes etc. In fact, the more diversified they are, the better (in principle).

But that diversification is completely independent of the pricing of your individual insurance contract.

Have a look at Warren Buffett's 'March Madness' challenge, where he famously challenges people to predict all 67 outcomes of some basketball games to win a billion dollar. Warren Buffet ain't no fool: he doesn't need a pool, he can price the risk of someone winning this one off challenge.

More generally, have a look at Prize indemnity insurance https://en.wikipedia.org/wiki/Prize_indemnity_insurance which helps insure many one-off events.
by kundan_s__r | 2026-01-13 05:07:57+00:00
Whether or not Hallucination “happens often” depends heavily on the task domain and how you define correctness. In a simple conversational question about general knowledge, an LLM might be right more often than not — but in complex domains like cloud config, compliance, law, or system design, even a single confidently wrong answer can be catastrophic.

The real risk isn’t frequency averaged across all use cases — it’s impact when it does occur. That’s why confidence alone isn’t a good proxy: models inherently generate fluent text whether they know the right answer or not.

A better way to think about it is: Does this output satisfy the contract you intended for your use case? If not, it’s unfit for production regardless of overall accuracy rates.
by geokon | 2026-01-13 05:08:34+00:00
Working in geology, I find the opposite problem. Field work is so highly valued that we're at a place where we have so much data and not enough people really working and analyzing it. My general impression is that in some subfields work that's done exclusively using preexisting data is kind of looked down on. In my opinion tons and tons of money is essentially wasted collecting new data - and then it's poorly catalogued and hard to access. You typically have to email some author and hope they send you the data. People are fiercely protective of their data b/c it took a lot of effort to collect and they want credit and to be in on any derivative work (and not just a reference at the bottom of a paper)

I would say the main workflow is collect some new data nobody has collect before, look at it and see if it shows anything interesting, make up some interesting publishable interpretation.

It feels like it'd be smarter to start with working with existing data and publish that way. If you hit on some specific missing piece, go collect that data, and work from there. But the incentive structures aren't aligned with this

The AI angle is really shoehorned in, but irrelevant to the larger problem. Sure, it allows you to annotate more data. Obviously it's more fun to go do field work than count pollen grains under a microscope. If anything AI make it easier to do more fieldwork and collect even more data b/c now you can in-theory crunch it faster
by gnabgib | 2026-01-13 05:08:54+00:00
Related:

Iran shuts down Starlink internet for first time (191 points, 2 days ago) https://news.ycombinator.com/item?id=46575224

Iran is likely jamming Starlink (135 points, yesterday, 273 comments) https://news.ycombinator.com/item?id=46573384
by FarmerPotato | 2026-01-13 05:09:37+00:00
I used a Cray C-90 and T3D 256-core machine from 1995-1999. The T3D used commodity Alpha 21164, and was already behind the T3E when we got it (Cray refurbished.) By the end it was outclassed by an SGI Oxygen box with 8 CPUs. I’d already ported a lot of software from SunOS and HP-UX to Irix and Unicos (Cray) and it was easy to move it to Linux in the end.