MurphyA/hacker-news huggingface dataset:
by ok_computer | 2025-10-28 14:50:43+00:00
I think this says more about how much of our tasks and demonstrations of ability as developers revolve around boilerplate and design patterns than it does about the Cognitive abilities of modern LLMs.

I say this fully aware that a kitted out tech company will be using LLMs to write code more conformant to style and higher volume with greater test coverage than I am able to individually.
by IshKebab | 2025-10-28 14:51:03+00:00
That stat is basically meaningless on its own. It could mean anything from they've done an amazing job on engaging women, to they've bodged the numbers by unfairly discriminating against men, or anything in between.

Annoyingly they actually do have the data to answer which it is, because Pycon's review process has a first stage which is blind, and a second stage which isn't. So if they published how many talks get rejected at each stage, by year and vendor, then we could draw actual conclusions.

I couldn't find where they have published those numbers though so we can't draw any conclusions here.
by motorest | 2025-10-28 14:51:05+00:00
> Being liberal in what you accept comes at _huge_ costs to the entire ecosyste

Why do you believe that?

Being liberal in what you accept doesn't mean you can't do input validation or you're forced to pass through unsupported parameters.

It's pretty obvious you validate the input that is relevant to your own case, you do not throw errors if you stumble upon input parameters you don't support, and then you ignore the irrelevant fields.

The law is "be conservative in what you send, be liberal in what you accept". The first one is pretty obvious.

How do you add cost to the entire ecosystem by only using the fields you need to use?
by pshirshov | 2025-10-28 14:51:06+00:00
> If 65K keys is considered outrageously large

You can split it yourself. If you can't, replace Shorts with Ints in the implementation and it would just work, but I would be very happy to know your usecase.

Just bumping the pointer size to cover relatively rare usecases is wasteful. It can be partially mitigated with more tags and tricks, but it still would be wasteful. A tiny chunking layer is easy to implement and I don't see any downsides in that.
by fcholf | 2025-10-28 14:51:17+00:00
To efficiently encode XOR-constraint you will necessarily need extra variables (as you proposed) because we know that no bounded depth and polynomial size Boolean circuit can encode parity ("parity is not in AC0").

The problem with this kind of constraints is that they are not local and really disturb CDCL based SAT solvers because you cannot remove the constraint unless you have fixed all its variables. Now, cryptominisat has a specific focus on this kind of constraints and implements ad-hoc routines to exploit this routine. cryptominisat is hence focused toward applications where this kind of constraint naturally appears, be it circuit synthesis or cryptography.

Now, CDCL solver is another beast. Gaussian elimination / Grobner basis are not implemented in these solvers simply because it is "too costly". One way of understanding why is just to reframe what one call SAT solver. This is not really a tool to solve SAT (hell, they can't even deal with the pigeon hole principle without preprocessing), the purpose of a SAT solver is to quickly solve instances coming from natural encoding of constraint systems. In this framework, unit propagation and clause learning are basically extremely efficient because they uncover hidden structure in the way, us human, encode constraint problems. Hence (CDCL) SAT solvers are highly efficient in many applications. But it is easy to kill one with a few variables by simply going out of this framework. For example, they are killers in solving packages dependencies because the structure of these problems matches this approach, CDCL solvers are then just an extremely refined way of bruteforcing your way through the search space.

Now, if your application heavily contains XOR-constraints, then it is likely a (CDCL) SAT solver is not the right approach. For circuit synthesis, some people use BDD based approach (where parity can be efficiently encoded) but sometimes you will simply have to develop your dedicated solver or use other solvers for other NP-complete problem that will have a different area of specialization (as already observed in many comments).
by eclark | 2025-10-28 14:51:27+00:00
They would need to lie, which they can't currently do. To play at our current best, our approximation of optimal play involves ranges. Thinking about your hand as being any one of a number of cards. Then imagine that you have combinations of those hands, and decide what you would do. That process of exploration by imagination doesn't work with an eager LLM using huge encoded context.
by efsavage | 2025-10-28 14:51:32+00:00
> Make a ballpark, even lowball, estimate for that risk, and simply require the people inside the vehicle to compensate others for the risk being imposed on them.

I see your point but we're all imposing risks on each other all the time. I'm sitting on the 6th floor of a 10 floor building, presumably I'm at some non-zero risk of it collapsing, which would be lower if this building was shorter, but I don't feel entitled to compensation from the owner for the marginal risk because they wanted more floors.

I think we've actually done alot better in reducing the externalities of direct vehicle deaths (insurance, safety standards, vehicle inspections, etc.) than we have in other areas (energy costs, environmental impact, city/street design, parking, etc.)
by matheusmoreira | 2025-10-28 14:51:52+00:00
I claim (1) is the only possible response. We're already at war, and innocents are already dying.

I claim that the drug gangs have launched a stealthy secession. They have gotten sufficiently organized that they have laws, tribunals, taxes and territory. Is gang territory really brazilian territory? I don't think so. In such areas police is executed on sight, like enemy combatants. The brazilian government is not really there guaranteeing any of your so called rights. So are you really a brazilian citizen if you live in gang territory? Don't think so. These drug gangs have formed a government so barbarous they kill you if you don't pay your taxes.

When São Paulo tried to secede last century, war was declared and they were massacred. So why are these gangs tolerated? It's just a completely stupid status quo. This government needs to recognize the gravity of the situation and react accordingly. Instead the government and the gangs are merging into one.
by deaux | 2025-10-28 14:52:03+00:00
General data: hundreds of billions of tokens per week are running through Deepseek, Qwen, GLM models solely by those users going through OpenRouter. People aren't doing that for laughs, or "non-real-world use", that's all for work and/or prod. If you look at the market share graph, at the start of the year the big 3 OpenAI/Anthropic/Google had 72% market share on there. Now it's 45%. And this isn't just because of Grok, before that got big they'd already slowly fallen to 58%.

Anecdata: our product is using a number of these models in production.

[0] https://openrouter.ai/rankings
by ericmay | 2025-10-28 14:52:04+00:00
Auto fatalities are insane, and the US focus on build highways at all costs while out of the other side of their mouth parroting talking points about safety is one of the uniquely stupid things we do as a society. The safest car is the one parked in your garage. The safest driver is the one who isn't behind the wheel.

That being said, I think Waymo is spot-on here. The US at least will accept deaths due to these machines - look at how we accept car deaths now - but the problem Waymo faces is that when these machines do kill someone it's not like automobile insurance today but instead it's a lawsuit every single time until/unless we construct a new regulatory framework to divest corporations from having real responsibility for the deaths caused by these machines. We shouldn't fight the technology, IMO, because I think over the long term it will be safer to be in an autonomous car. We should instead ensure that if such deaths occur, businesses don't get to step away from their responsibility and have to pay rather large sums.

All that being said, all of the above is a complete waste of time and civilizational level resources. Most people should be walking, biking, and hopping on an automated rail line to get around. It's cheaper, healthier, and better in every way. And then when you want to take the car for that road trip or Sunday drive you still can.
by bobim | 2025-10-28 14:52:25+00:00
I was running it on an Odroid N2 for 2-3 years, and upgraded to a RK3588 Orange Pi something a couple of years ago. It's not fast but it's useable. At one point I succeded in making the collaborative editing working, but it stopped after updates. Maybe it needs more love than what I'm able to spare, but the feeling after years is that you have to accept some level of unreliability.
by etiennebausson | 2025-10-28 14:53:07+00:00
People give car fatalities in general a pass because it could be have been them driving.

If Waymo or a concurrent replace drivers, they don't get that free pass anymore, because the jury will not think it could have been them.

That would actually be a better situation to today's "free pass for everyone as long as no drug involved" that rules nowaday.
by JohnMakin | 2025-10-28 14:53:34+00:00
It’s part of the centi billionaire class power grab playbook. each one of them for the most part has some major media interests. if you can control and dictate the narrative, for a while no one can protest you, and maybe they won’t notice for a while that their futures are being robbed to enrich a handful of extremely vain white men. by the time they do, it’s likely too late.
by AndrewKemendo | 2025-10-28 14:53:37+00:00
This is called “managing the narrative”

It’s a classic hallmark technique of advanced psychopaths wherein you agree with reality but don’t change it because as long as you acknowledge it, most people assume you’ll “do your best.”

So all you have to do is acknowledge it, and as long as there’s nobody who can force you to do anything then there’s no obvious way to address it without escalation - that escalation being the reason then for claiming you’re attacked and then you have carte blanche to “simply defend yourself”

Do that long enough and people get tired and move on and you just cemented your place further
by LargoLasskhyfv | 2025-10-28 14:53:46+00:00
Depends on what you search for in which language and region. For technical stuff in english DDG mostly suffices, otherwise WP. For businesses, restaurants, clubs, general venues Apple Maps or Google Maps as fallback, depending on region. For pure maps, bicycle routes, pedestrian shortcuts OSM, depending on region again. There is no universally usable map.
by ps3544 | 2025-10-28 14:53:47+00:00
This is the central challenge of moving agents from single-player demos to multi-player production systems. My team has been tackling this, and we've landed on a few patterns that work well.

1. For policies (what agents can/can't do): We've had a lot of success with an in-process, "pre-execution hook" model. Instead of having the agent's core logic be full of if/else permission checks, we use a lightweight policy engine. Before any critical action (like a tool call), the agent's intent is passed to the engine, which evaluates a set of simple, deterministic Python functions (our policies) against the current context (user role, budget, etc.). If any policy returns BLOCK, an exception is raised and the action is never executed. It's like a sub-millisecond, framework-agnostic version of OPA that doesn't require a sidecar.

2. For managing shared data & mixing frameworks: The key insight for us was to treat this as a classic observability problem. The only way to debug race conditions or interoperability failures between a LangGraph agent and a CrewAI agent is to have a unified, high-fidelity trace of the entire system.

We built a simple tracing system with a @trace decorator that we can apply to functions in any framework. All traces are written to a single, local SQLite database. This gives us a "global view" of the system. When data gets corrupted, we can run a SQL query like SELECT * FROM spans WHERE attributes->>'data_id' = 'xyz' ORDER BY start_time_ns to see the exact sequence of reads and writes from all agents that touched that data.

(For anyone interested, we've open-sourced this entire approach as a single toolkit called Clearstone. The repo is in my profile. It's in an early beta, but it has the policy engine and the local SQLite tracer we're using.)
by 91bananas | 2025-10-28 14:53:51+00:00
Yeah this is not the case at all lol. I actually find Azure to be far more intuitive after suffering through AWS and a little GCP. It certainly seems more stable in US regions than AWS.

One thing I will say is the Azure documentation is some of the most cumbersome to navigate I've ever experienced, there is a dearth of information in there, you just have to know how to find it.
by wat10000 | 2025-10-28 14:54:50+00:00
Maybe you shouldn't shut down OpenAI over this. But each instance of a particular ChatGPT model is the same as all the others. This is like a company that has a magical superhuman therapist that can see a million patients a day. If they're found to be encouraging suicide, then they need to be stopped from providing therapy. The fact that this is the company's only source of revenue might mean that the company has to shut down over this, but that's just a consequence of putting all your eggs in one basket.
by embedding-shape | 2025-10-28 14:55:37+00:00
> It is kind of nuts that less than half of society accepts that

I'm not seeing any evidence of the other half of the US society not accepting school shootings.

If people truly cared about it, you'd go out on the street and protest, and waging a general strike in school and related areas until something is being done about it.

Instead 99% of the population seems complacent, and do mostly nothing about it, everyone (mostly) is still sending their kids to schools, teachers are still going to work and everything is business as usual.
by spankalee | 2025-10-28 14:55:37+00:00
We already accept 40,000 vehicle deaths a year, 7,500 pedestrian deaths a year, 1,100 by police, 260 by train, and almost 50,000 deaths from falls.

Nothing is completely safe, and it's just factually correct to say that there will be a fatal crash at some point that's the fault of an autonomous car (there actually have been already), but that Waymo's at least are already far safer than human drivers, and if that remains true, then society will "accept" it.

Also, the question was literally "Will society accept a death potentially caused by a robot?" which is not great, IMO. What does it mean for "society" to "accept" a death? There will be lawsuits, regulations, etc. Is the question whether self-driving cars will be banned everywhere after one fatality?
by aelaguiz | 2025-10-28 14:55:50+00:00
This is my area of expertise. I love the experiment.

In general games of imperfect information such as Poker, Diplomacy, etc are much much harder than perfect information games such as Chess.

Multiplayer (3+) poker in particular is interesting because you cannot achieve a nash equilibrium (e.g. it is not zero sum).

That is part of the reason they are a fantastic venue for exploration of the capabilities of LLMs. They also mirror the decision making process of real life. Bezos framed it as "making decisions with about 70% of the information you wish you had."

As it currently stands having built many poker AIs, including what I believe to be the current best in the world, I don't think LLMs are remotely close to being able to do what specialized algorithms can do in this domain.

All of the best poker AI's right now are fundamentally based on counter factual regret minimization. Typically with a layer of real time search on top.

Noam Brown (currently director of research at OpenAI) took the existing CFR strategies which were fundamentally just trying to scale at train time and added on a version of search, allowing it to compute better policies at TEST TIME (e.g. when making decisions). This ultimately beat the pros (Pluribus beat the pros at 6 max in 2018 I believe). It stands as the state of the art, although I believe that some of the deep approaches may eventually topple it.

Not long after Noam joined OpenAI they released the o1-preview "thinking" models, and I can't help but think that he took some of his ideas for test time compute and applied them on top of the base LLM.

It's amazing how much poker AI research is actually influencing the SOTA AI we see today.

I would be surprised if any general purpose model can achieve true human level or super human level results, as the purpose built SOTA poker algorithms at this point play substantially perfect poker.

Background:

- I built my first poker AI when I was in college, made half a million bucks on party poker. It was a pseudo expert system. - Created PokerTableRatings.com and caught cheaters at scale using machine learning on a database of all poker hands in real time - Sold my poker AI company to Zynga in 2011 and was Zynga Poker CTO for 2 years pre/post IPO - Most recently built a tournament version of Pluribus (https://www.science.org/doi/10.1126/science.aay2400). Launching as duolingo for poker at pokerskill.com
by Tostino | 2025-10-28 14:56:03+00:00
Why wouldn't something like an RL environment allow them to specialize in poker playing, gaining those skills as necessary to increase score in that environment?

E.g. given a small code execution environment, it could use some secure random generator to pick between options, it could use a calculator for whatever math it decides it can't do 'mentally', and they are very capable of deception already, even more so when the RL training target encourages it.

I'm not sure why you couldn't train an LLM to play poker quite well with a relatively simple training harness.
by brrrrrm | 2025-10-28 14:56:28+00:00
> None of which are they currently capable

what makes you say this? modern LLMs (the top players in this leaderboard) are typically equipped with the ability to execute arbitrary Python and regularly do math + random generations.

I agree it's not an efficient mechanism by any means, but I think a fine-tuned LLM could play near GTO for almost all hands in a small ring setting
by abetusk | 2025-10-28 14:57:18+00:00
Not even close [0]:

https://en.wikipedia.org/wiki/Moore%27s_law#/media/File:Moor...

https://en.wikipedia.org/wiki/Moore%27s_law#/media/File:The_...

[0] https://en.wikipedia.org/wiki/Moore%27s_law
by eclark | 2025-10-28 14:57:20+00:00
Text trained LLM's are likely not a good solution for optimal play, just as in chess the position changes too much, there's too much exploration, and too much accuracy needed.

CFR is still the best, however, like chess, we need a network that can help evaluate the position. Unlike chess, the hard part isn't knowing a value; it's knowing what the current game position is. For that, we need something unique.

I'm pretty convinced that this is solvable. I've been working on rs-poker for quite a while. Right now we have a whole multi-handed arena implemented, and a multi-threaded counterfactual framework (multi-threaded, with no memory fragmentation, and good cache coherency)

With BERT and some clever sequence encoding we can create a powerful agent. If anyone is interested, my email is: elliott.neil.clark@gmail.com
by floor2 | 2025-10-28 14:57:34+00:00
> just send the cops after you

> > that's clearly a good thing

You might want to read up on how interactions between police and various groups in the US tend to go. Sending the cops after someone is always going to be dangerous and often harmful.

If the suicidal person is female, white and sitting in a nice house in the suburbs, they'll likely survive with just a slightly traumatizing experience.

If the suicidal person is male, black or has any appearance of being lower class, the police are likely to treat them as a threat, and they're more likely to be assaulted, arrested, harassed or killed than they are to receive helpful medical treatment.

If I'm ever in a near-suicidal state, I hope no one calls the cops on me, that's a worst nightmare situation.
by ventedmouse | 2025-10-28 14:58:02+00:00
Your comment made wonder if there is an social / economic phenomenon tied to your characterization. I'd be really curious if there is any academic work done on further elucidating it.

Edit: Did some research with ChatGPT and found the following papers if anyone else is interested in the above concepts.

https://pmc.ncbi.nlm.nih.gov/articles/PMC9537742/

https://www.researchgate.net/publication/235279297_The_survi...

https://backend.production.deepblue-documents.lib.umich.edu/...

https://pmc.ncbi.nlm.nih.gov/articles/PMC10025906/

https://strategy.sjsu.edu/www.stable/pdf/Staw%2C%20B%2C%20L%...

https://journals.sagepub.com/doi/10.1177/0312896220970609
by IlikeKitties | 2025-10-28 14:58:17+00:00
> They're about as smart as a person who's kind of decent at every field. If you're a pro, it's pretty clear when it's BSing. But if you're not, the answers are often close enough.

No they are not smart at all. Not even a little. They cannot reason about anything except that their training data overwhelmingly agrees or disagrees with their output nor can they learn and adept. They are just text compression and rearrangement machines. Brilliant and extremely useful tooling but if you use them enough it becomes painfully obvious.
by tom1337 | 2025-10-28 14:58:25+00:00
Same - living in a region where it gets below 0°C in the winter and also snows, you really see that those cars were designed for sunny california. It happened multiple times now that the trunk or door handles were frozen so hard, that I couldn't use the car in the morning. Also when opening the frunk while its partly covered in snow just made it slide into the frunk...
by pshirshov | 2025-10-28 14:58:36+00:00
Yep, can be done but they aren't free because of variable size. With constant pointers I can access const-sized elements directly, with varints I would have to do some rituals.

I have another binary encoding for different purposes (https://github.com/7mind/baboon) which relies on varints, in case of SICK I decided to go with pointers of constant size to save some pennies on access efficiency.
by Larrikin | 2025-10-28 14:58:38+00:00
Useful if used well as a thought has gone from meaning a replace all developers machine to a fresh out of college junior with perfect memory bot to a will save a little typing if you type out all of your thoughts and baby sit it text box.

I get value from it everyday like a lawyer gets value from LexisNexis. I look forward to the vibe coded slop era like a real lawyer looks forward to a defendant with no actual legal training that obviously did it using LexisNexis.
by crymer11 | 2025-10-28 14:58:47+00:00
From your linked article:

> But personally, I don't use tell-dont-ask. I do look to co-locate data and behavior, which often leads to similar results. One thing I find troubling about tell-dont-ask is that I've seen it encourage people to become GetterEradicators, seeking to get rid of all query methods.