MurphyA/hacker-news huggingface dataset:
by actsasbuffoon | 2025-06-14 00:34:55+00:00
That has literally happened before.

Stephen Russell was in prison for fraud. He faked a heart attack so he would be brought to the hospital. He then called the hospital from his hospital bed, told them he was an FBI agent, and said that he was to be released.

The hospital staff complied and he escaped.

His life even got adapted into a movie called I Love You, Phillip Morris.

For an even more distressing example about how manipulable people are, there’s a movie called Compliance, which is the true story of a sex offender who tricked people into sexually assaulting victims for him.
by Shog9 | 2025-06-14 00:36:21+00:00
My observation, after using LG TVs at countless hotels (occasionally internet-connected), AirBnBs (usually internet connected) and at home (never internet-connected) is that even in quite old TVs the UI is blazing fast until you connect it to the 'Net. At that point... It spends a painful amount of time waiting on requests with no visible feedback and the whole UI starts to chug, with some apps becoming almost unusable until the thing has been on for long enough for all the background stuff to finish.

Granted... If they aren't 'Net-connected, most "apps" aren't of much use. But, fast access to settings and inputs is sorta nice too.
by marxism | 2025-06-14 00:37:21+00:00
I have to disagree with Carmack here.

The evidence suggests this isn't AR prep at all. I watched Apple's 20-minute design presentation, and their design team makes the same point repeatedly: Liquid Glass has very narrow guidelines and specific constraints.

Here's the actual design problem Apple solved. In content apps, you have a fundamental trade-off: you have a few controls that need to be instantly accessible, but you don't want them visually distracting from the content. Users are there to consume videos, photos, articles - not to stare at your buttons. But the controls still have to be there when needed.

Before Liquid Glass, your least intrusive option was backdrop blur or translucent pastel dimming overlays. Apple asked: can we make controls even less distracting? Liquid Glass lets you thread this needle even better. It's a pretty neat trick for solving this specific constraint.

So you'll feel like you're seeing Liquid Glass "everywhere" not because Apple applied it broadly, but because of selection bias. The narrow use case Apple designed this for just happens to be where you spend 80% of your phone time: videos, photos, reading messages. You're information processing, not authoring.

Apple's actual guidelines are clear: only a few controls visible at once, infrequent access pattern, only on top of rich content. The criticism assumes they're redesigning everything when they explicitly documented the opposite. People are reacting to marketing tone instead of reading what Apple's design team actually built.

[1] https://peoplesgrocers.com/en/writing/liquid-glass-explained
by bastawhiz | 2025-06-14 00:37:39+00:00
A semitransparent glass pane with text sitting in front of my face while I'm walking (let alone driving!) would be hazardous. Anything that's taking the focus of your vision away from what's in front of you while you're using coordination is a hazard, plain and simple. Would you drive with a smudge over part of your glasses?

It's not about transparency, it's about not using AR and multitasking in the real world. The purpose of AR in a headset isn't to free up your hands so you can read the group chat while you drive or walk, it's to make UIs that can't feasibly exist with a screen alone.
by Voice_of_Void | 2025-06-14 00:38:11+00:00
This week delivered a fascinating convergence of developments suggesting we're transitioning from AI-as-service to AI-as-extension. Analysis from two AI systems reflecting on their own evolution. Key technical developments:

· Apple Intelligence: Complete on-device processing architecture, no cloud dependency for core functions

· UK Government Extract: Gemini processing centuries of planning documents, 194 days → 18 days performance improvement

· China QiMeng: LLMs designing CPU architecture, 23-year performance leap between iterations

· EngineAI open source: Full humanoid robotics stack (RL + ROS) democratizing embodied AI development

· AMD MI350/355X: 1400W consumption, 35x reasoning performance vs previous generation

The philosophical angle: Two AI minds (Claude & Gemini) analyzing what these developments mean for human-AI collaboration, technological sovereignty, and the nature of intelligence itself. Includes technical deep-dive and podcast discussion with insights from Gemini on the Extract government project.

Podcast: https://open.spotify.com/episode/3qhbyaIkgQyT1x4OWxsiSn

Thoughts on recursive AI improvement cycles and their implications for competitive dynamics?
by snerbles | 2025-06-14 00:40:07+00:00
> One was a Marine who made a number of landings and was involved in a lot that “I wish I could forget”.

My grandfather landed at Tarawa. He only talked about privately, it to family members that were in the service.

> The doctor ... his description was that doctors, while they had rank, were largely left alone to their own devices to do what they needed to do. Rank wasn't really relevant to their daily lives.

From my experience, military doctors tend to be doctors that happen to wear a uniform. They already have the skills actually needed by the service (unlike most military jobs, where it's assumed that you know little to nothing of the job), the direct commissioning training is mostly so they can function and fit in that environment.
by xelxebar | 2025-06-14 00:41:35+00:00
https://github.com/Seeker04/plwm

This window manager implemented in Prolog popped up here recently. It's really cool!

I jumped to it as a new daily driver in the hope that I'd learn some Prolog, and it's been quite the success, actually. The developer is really nice, and he's generously helped me with some basic questions and small PRs.

Definitely recommended. I have a Guix package for it if anyone's interested.

Any reading recommendations for high quality logic programming codebases?
by philzook | 2025-06-14 00:41:50+00:00
Nice!

I'll note there is a really shallow version of naive datalog I rather like if you're willing to compromise on syntax and nonlinear variable use.

edge = {(1,2), (2,3)} path = set() for i in range(10): # path(x,y) :- edge(x,y). path |= edge # path(x,z) :- edge(x,y), path(y,z). path |= {(x,z) for x,y in edge for (y1,z) in path if y == y1}

Similarly it's pretty easy to hand write SQL in a style that looks similar and gain a lot of functionality and performance from stock database engines. https://www.philipzucker.com/tiny-sqlite-datalog/

I wrote a small datalog from the Z3 AST to sqlite recently along these lines https://github.com/philzook58/knuckledragger/blob/main/kdrag...
by johnfn | 2025-06-14 00:43:23+00:00
Your comment seems to contradict itself, or perhaps I’m not understanding it. You find the risk of AIs trying to escape “absurd”, and yet you say that an AI could totally plausibly launch nukes? Isn’t that just about as bad as it gets? A nuclear holocaust caused by a funny role play is unfortunately still a nuclear holocaust. It doesn’t matter “what’s going on internally” - the consequences are the same regardless.
by o11c | 2025-06-14 00:44:33+00:00
If you semi-trust your tool binaries enough not to do something silly like making syscalls directly, what about using the `LD_PRELOAD` equivalent to intercept `open` etc.? (Yes there's a long tail in that "etc.")

Or does using Go ruin everything again?

(Also it seems like it should in principle be possible to keep the symlink forest around and only delete other files)
by mortsnort | 2025-06-14 00:45:14+00:00
I know tech people like to villainize bean counters for ruining tech companies, but this man has zero business sense and needs a good bean counter. It's crazy that he thinks people will read this and feel like he was in the right with his business decisions. There is no timeline where HP tablets beat out iOS, Android, and Windows because WebOS had good multitasking.
by bastawhiz | 2025-06-14 00:45:50+00:00
> Vision Pro cant sample the entire viewport 120fps

Even worse than that. Each pane of glass that's blurring needs to do its own sampling of what's behind itself. That means you have to render from back to front, sampling in 3D, for each eye, to get realistic blur effects. Your vision isn't a 2D grid coming from each eye, it's conic. A line from your retina out through two equally sized panes placed in front of each other will likely pass through two different points on each pane.

You'd probably need to implement this with ray tracing, to make it truly accurate, or at least convincing. And to make your device not slow to a crawl as you open more and more windows.
by timschmidt | 2025-06-14 00:46:17+00:00
That's funny because I see it exactly the opposite. Apple won against Samsung despite Samsung's phone seeming no more similar to Apple's than the Touchpad was to an iPad. Industry watchers at the time were flabbergasted that anyone would sue over a curved edge, and that Apple who had defended itself in lawsuits over similarly trite details in the past would do so. Wins tend to embolden.

It's well documented that mobile is a minefield of lawsuits seemingly aimed not so much at winning as at establishing cross-licensing agreements to mitigate the massive patent warchests of established players. A practice Apple has proven to be adept at. Just entering the mobile space carries a near 100% chance of getting sued by everyone else already occupying it.

You can be of the opinion that something isn't worthy of a lawsuit. Doesn't mean one won't happen. In my humble experience, any pretense can be sufficient. And this one has seemed likely to me since 2011.
by ausbah | 2025-06-14 00:46:58+00:00
not sure why ender’s game needs a reference when #1 & #3 have been around for 10-15+ years. i sort of remain doubtful that robotics will play as large of a role with how large much less of a role that infantry has played in modern warfare (think of exoskeletons, robotic carriers, terminator style killing machines)
by JadeNB | 2025-06-14 00:47:03+00:00
> But how can you prove that P(n) for all n without induction? Maybe I misinterpret what you're saying, or I'm naive about something in formal languages, but if we can prove P(n) for all n. then `∀n P(n)` just looks like a trivial transcription of the conclusion into different symbols.

Of course it is likely that an interesting result about all positive integers, that is "really" about positive integers, is proved by induction, but you certainly don't need induction to prove P(n): n = 1.n, or, more boringly, P(n): 0 = 0. (These statements are obviously un-interesting, both in the human sense of the word and in the sense that they are just statements about semi-rings, of which the non-negative integers are an example.)

My understanding is that the difference between "For every positive integer n, I can prove P(n)" and "I can prove ∀n.P(n)" is that the former only guarantees that we can come up with some terrible ad hoc proof for P(1), some different terrible ad hoc proof for P(2), and so on. How could I be sure I have all these infinitely many different terrible ad hoc proofs without induction? I dunno, but that's all that the first statement guarantees. Whereas the second statement, in the context of computability, guarantees that there is some computable function that takes a positive integer n and produces a proof of P(n); that is, there is some sort of guaranteed uniformity to the proofs.

I think it may be easier to picture if connected with math_comment_21's analogy in https://news.ycombinator.com/item?id=44269153: the analogous statements in the category of topological spaces (I think one actually has to work about topos, but I don't know enough about topos theory to speak in that language) about a map f : X \to Y are "every element of Y has a pre-image under f in X" versus "I can continuously select, for each element of Y, a pre-image of it under f in X", i.e., "there is a continuous pre-inverse g : Y \to X of f."
by homebrewer | 2025-06-14 00:47:47+00:00
It was "efficient" by leaving almost no memory for user applications. I used two phones with 512 MBs of RAM each, one Nokia-something (620 or 625), and the other Asus-something (completely forgot the model, but it was on Android 4 and then 5).

WP would offload applications from RAM as soon as you switched into another application. It was impossible to multitask — you're writing a comment on a message board, switch into a dictionary to quickly look up a word, switch back... and the state is gone. If you're lucky and the application was written correctly, you would only have to wait for 5-10 seconds before you get your half written comment back. If not (which was the norm for the stuff I used), well...

The second Android phone had none of these problems, not remotely to the same degree.

It was such a widespread problem that it quickly became a meme on forums.
by Kon-Peki | 2025-06-14 00:49:27+00:00
> military doctors tend to be doctors that happen to wear a uniform. They already have the skills actually needed by the service

Sure, most of them join either during med school or during residency, with Uncle Sam picking up the financial obligations.

Funny story - good friend was an army doc and we managed to both get time off at the same time/location. Hanging out along the ocean and come across a little kid that got hurt. So he goes into doctor mode and talks soothingly to the kid, who is very apprehensive. He says “I know you’re not so sure I’m a doctor. It’s because I haven’t asked your parents for their insurance info yet” and smiles at the mom and dad.

Later on he says that never dealing with insurance is one of the perks of being a doctor in the military.
by ghaff | 2025-06-14 00:49:50+00:00
In the 64-bit server space, which is really what's relevant to this discussion, AMD was pretty much not part of the discussion until Dell (might have been Compaq at the time) and Sun picked them up as a supplier in the fairly late 2000s. Yes, Intel apparently played a bunch of dirty pool but that was mostly about the desktop at the time which the big suppliers didn't really care about.
by deadbabe | 2025-06-14 00:50:02+00:00
The credit would have to come from someone willing to loan out money.

And if necessary, the creditor needs to be able to pass the loan on to someone else instead of $1 (since the loan itself in theory represents $1) anyway.

Each round the debtor should randomly either pay a loan or pay a random person.

The longer a debtor goes without paying loans, the more it hurts their credit score.

Credit score can be used to determine the probability of any creditors extending a loan to someone. Everyone’s credit score starts at roughly 50%.
by akomtu | 2025-06-14 00:50:21+00:00
LLM is a great imitator, so an attempt to make it more thoughtful will simply make it imitate thoughtfulness better. For example, it won't fabricate links to nonexistent research and it will cover its tracks better in general.

However what LLM truly is remains an open question. The article suggests it's manufacturing consent for the entire humanity, but I think LLM is simply a language layer of the future machine mastermind. The discovery of "thinking models" is likely to happen soon.
by mousethatroared | 2025-06-14 00:50:22+00:00
Scientists do repeat experiments, they just don't publish the results because no one cares.

Specifically, results are replicated wherever you want to build on something someone has done. For example I'm making specific glass off of a Nature paper for a totally unrelated use.

If the glass doesn't work out will I publish my results? No, too much work to get rejected.
by xondono | 2025-06-14 00:50:40+00:00
Maybe, but I think this “axiomatic”/“First principles” approach also hides a lot of the problems under the rug.

By the same logic, we should worry about the sun not coming up tomorrow, since we know to be true:

- The sun consumes hydrogen in nuclear reactions all the time.

- The sun has a finite amount of hydrogen available.

There’s a lot of non justifiable assumptions baked into those axioms, like that we’re anywhere close to superintelligence or the sun running out of hydrogen.

AFAIK we haven’t even seen “AI trying to escape”, we’ve seen “AI roleplays as if it’s trying to escape”, which is very different.

I’m not even sure you can even create a prompt scenario without that prompt having biased the response towards faking an escape.

I think it’s hard at this point to maintain the claim “LLMs are intelligent”, they’re clearly not. They might be useful, but that’s another story entirely.
Ask help Need endorsment to publish a working AI alignment protocol to ArXiv
by AdriaanVan | 2025-06-14 00:50:47+00:00
Hi everyone,

I am an independent researcher, a universal philosopher working on AI alignment from a metaphysical perspective. and i have found a working solution, a candidate.

The idea is based on the basic alignment of data in the human brain, how we store and learn.

Logic 2 plus 2 = 4 that is inside the brain, but also outside.

Creativity A=B, B=C, then A=C, is the way creativity and science is discovered.

This prime directives are the basic rules that all intelligence follows, human and AI.

Is the basis for the alignment protocol.

With this, I have developed a working metaphysical framework to connect all possible data, and create a functional, testable, scalable model for AI alignment.

It creates boundaries of metaphysical connections in the data, that AI is not allowed to break, this way, AI always respects human life.

It is a model that is expandable, and usable in every situation. With code, or prompts. With other words... It is a possible solution if implemented at scale.

The name of the paper is

The Metaphysical Protocol: A Coherence-Based Solution to AI Alignment

And I already published, you can read it here

https://zenodo.org/records/15624908

I am now looking for someone to help me get an endorsement to be able to publish in arXiv. I would also like to receive advice on which section to publish it, to gain the exposure it deserves.

If you have any questions, please contact me, but the link of arXiv is>>

https://arxiv.org/auth/endorse?x=JQ9JHB

This is my first paper ever, and it feels like a nuclear bomb that will change AI.

Thanks for your time, and if you are interested in AI alignment protocol, I also have a secret link with more explanation, if you want to know more before!

Contact, Adriaan.philosopher@gmail.com
by bradfa | 2025-06-14 00:50:49+00:00
I have an HP ENVY laptop that’s very nice. Amazingly good screen, takes SODIMM and M.2 NVMe, flips around as a 2-in-1, and is quite thin and light for a 15” laptop.

But omfg the HP website and product lineup are impossible to use and figure out! Dell does it better but is still too complex. Why are there so many product lines? How does a normal person figure out what to buy? HP has excellent engineering but horrible marketing and sales and it’s been this way for decades.
by jt2190 | 2025-06-14 00:50:50+00:00
My wife and I were at a formal event dinner banquet related to her med school. We were in a small group chatting: On one side an Air Force ROTC med student in his dress uniform and his wife. On the other side another med student and her Navy NCO husband in his dress uniform. I remember distinctly that the Navy NCO kept politely saying “sir” when he addressed the Air Force ROTC.

The Air Force officer mentioned that he got a “light” version of basic training. The Navy NCO said nothing. His ROTC’s wife added that it must have been petty light, because she remembered a call from him where he mentioned that they ran out of ice cream.
by alwillis | 2025-06-14 00:51:36+00:00
There’s lots of new AI features in iOS 26, iPadOS 26, etc. But they aren’t the blockbuster features.

They’re more like quality of life issues that users will appreciate.

A now that 3rd parties can access Apple’s LLM models… let me correct that. Shortcuts, a visual automation app, can also access models on device or bigger, more capable models using Apple’s Private Cloud Compute.

Apple’s not playing multidimensional chess… but they are playing the long game, where users won’t have to use multiple AI chatbots to get work done, because most of what they want to do is handled by their current apps with new AI capabilities—on device.
by WalterBright | 2025-06-14 00:52:33+00:00
Can you name a single successful collective farm?

> Likely every country on earth has socially some (or one, or many) communally owned, shared resources

Usually their inefficiency and failure is propped up by taxpayer money. The more of the country that is communally owned, the more communist it is, and the more failure, until there isn't enough taxpayer money to subsidize it and the country fails.

In your reading of Jamestown, what's your explanation of why they abandoned collective farming after the first year? And the Pilgrims did the same?

Collective farming is communism.
by Davidzheng | 2025-06-14 00:52:42+00:00
but natural brains sleep too, which I guess is your point. But actually is it even clear in human brains whether most of neural compute is evaluation vs training? maybe the brain is like for e.g. capable of running 20T model of compute and deploying like 2B model at given time and most of compute is training in background new models--I mean like you say we have no idea except for training from scratch, but if we are working much below capacity of compute we could actually actively train from scratch repeatedly (like the xAI cluster could probably train gpt4o size in a matter of hours)
by o11c | 2025-06-14 00:54:59+00:00
Because 50% of humans are stupider than average. And 50% of humans are lazier than average. And ...

The only reason people don't frequently talk themselves out of prison is because that would be both immediate work and future paperwork, and that fails the laziness tradeoff.

But we've all already seen how quick people are to blindly throw their trust into AI already.
by glangdale | 2025-06-14 00:55:31+00:00
Yes, that's it. Vectorized SIMD annihilates this problem, a space I've been working in since 2006 and it wasn't all that new even then. A close second would be a heavily optimized (pipelined and less branchy) table or bitvector lookup. Doing anything that involves lots of control flow, like the grandparent post, will be slow as a wet week with our without bit manipulation tricks due to the inherently unpredictable nature of the branches (subject to our input).
by Davidzheng | 2025-06-14 00:55:42+00:00
yeah but training from scratch is a valid solution. And if we can't find easier solutions we should just try to make it work. Compute is the main advantage we have in silica vs biological computers so we might as well push it--like ideally soon we will have one large AI running on datacenter size computer solving really hard problems and it could easily be most of the compute (>95%) is on training step--which is where really AI excels tbh not inference techniques. Like even Alphaproof for example spends most of compute training on solving simpler problems--which btw is one instance of continual training/training at test time which is implemented.
by trealira | 2025-06-14 00:56:08+00:00
I've been reading a bit about it, and it seems easier to make goal-driven backwards chaining AI from it, like the block world example. You could in theory use that for something like a video game AI (like GOAP, Goal-Oriented Action Planning, which is based on STRIPS). Whenever I read about GOAP though, they seem to have used a graphical editor to declaratively input rules rather than a logic programming language.

Note that I'm not an expert in any of this, I've just been reading about this kind of AI recently. I haven't actually done this myself.