MurphyA/hacker-news huggingface dataset:
by fnordpiglet | 2025-12-08 01:35:49+00:00
Asking your favorite LLM actually helps a lot. They generally are well trained on LLM papers unsurprisingly. In this case though it’s important to realize the LLM is incapable of seeing or hearing or reading. Everything has to be transformed into a vector space. Images are generally cut into patches (like 16x16) which are themselves transformed by several neural networks to convert them into a semantic space represented by the models parameters.

But this isn’t hugely different than your vision. You don’t see the pixel grid either. You have to use tools to measure things. You have the ability over time to iteratively interact with the image by perhaps counting grid lines but the LLM does not - it’s a one shot inference against this highly transformed image. They’ve gotten better at complex visual tasks including types of counting, but it’s not able to examine the image in any analytical way or even in its original representation. It’s just not possible.

It can however make tools that can. It’s very good at working with PIL and other image processing libraries or even writing image processing code de novo, and then using those to ground itself. Likewise it can not do math, but it can write a calculator that can do highly complex mathematics on its behalf.
by lathiat | 2025-12-08 01:36:10+00:00
I still have one of the early green OLPC laptops kicking around that I got at linux.conf.au 2005, in part because they were (or were thinking of) making use of avahi as part of the mesh stuff. They are quite fun to look at.

The project was quite interesting and exciting, and I really miss the era of custom linux desktops, phones, tablets etc being viable projects, it's a shame the project never really directly worked out.
by doctor_radium | 2025-12-08 01:36:35+00:00
I would like to think incompetence as well, but when the problem is this widespread, IMHO it does point to a corporate issue...even if that's simply leaving too many incompetent managers in charge. IMHO if you're the manager and the part-time teenager didn't finish updating all the shelf pricing, then it's on you to finish before going home. But today too many people just don't give a damn.

My first job was in retail as well, going back to the days before scanners when every item item was ticketed individually. When something goes on sale you ticket it again, then tear off the sale price stub when the sale ends. Repeat as needed. Maybe that could be a suitable punishment, too? Force stores to abandon shelf pricing for a period of time until it hurts enough that they get their act in order?
by nephihaha | 2025-12-08 01:37:17+00:00
There are better explanations than the vanilla call card of "conspiracy theory". One of them is that it is easy to get disorientated around there due a combination of many similar small islands in some areas and remote open ocean in another section, so it would be difficult to navigate by sight.

There are also widespread reports of magnetic anomalies which would mess with compasses, and it is within the hurricane zone providing another possible cause.
by underlipton | 2025-12-08 01:39:05+00:00
It's different in different states. In Maryland, once a complaint is filed with the relevant authority, the store has a certain number of days to correct pricing. Most retailers will give you the misprice if it's clearly their fault in not changing the tags, as a matter of policy.

The confusion around this law is quite frustrating, though. Quite a few customers think they're entitled to not just prices on tags that haven't been updated, but prices for what are clearly entirely different products.
by puildupO | 2025-12-08 01:39:39+00:00
I opened a shared notebook where anyone can create their own playlist of songs. You can add any genre, any year, any mood. The idea is to see all the different playlists people build in the same space. Just open it, press the add playlist button, and paste your song's link.

I want to see how many unique playlists this community creates.
by CommenterPerson | 2025-12-08 01:41:40+00:00
I shop at Walmart and Costco. The customers at the Costco appear much better off, but they seem much more arrogant and inconsiderate. They leave carts in the middle of the aisle, talk on phones with their families blocking the way, and so forth. Same behavior in the parking lots. Maybe it's because Costco is always packed. The shoppers at the Walmart definitely look less well off. They are much more respectful and considerate of others. I like shopping at the Walmart more.
by d3Xt3r | 2025-12-08 01:42:32+00:00
I don't see why you would automatically be in "a world of hurt". Yes, you might be if you were to suddenly roll it out organisation wide without any testing, but no sane IT department would do that. This is why you have internal test groups and pilot groups. Once you identify the limitations, you scope out the missing features/issues, engage developers if need be, or look for alternate solutions. No one needs to get hurt.
by fnordpiglet | 2025-12-08 01:42:51+00:00
Because the way subscription revenue is accounted for is a present value of the expected duration of the subscription and ad revenue is cyclic and varies throughout the year across individuals, cohorts, and the population. They’re also generally different markets - people willing to endure ads are either unable to afford the subscription or cheap, in either case it’s not unreasonable to expect the impression value for ads is pretty low.
by CGMthrowaway | 2025-12-08 01:43:08+00:00
>research from Anthropic [1] suggests that structures corresponding to meaning exist inside those bundles of numbers and that there are signs of activity within those bundles of numbers that seem analogous to thought.

Can you give some concrete examples? The link you provided is kind of opaque

>Amanda Askell [2]. When she talks, she anthropomorphizes LLMs constantly.

She is a philosopher by trade and she describes her job (model alignment) as literally to ensure models "have good character traits." I imagine that explains a lot
by PrairieFire | 2025-12-08 01:43:19+00:00
I feel like their analogy could have worked if they had pushed a little further into it.

The RNN and LSTM architectures (and Word2Vec, n-grams, etc) yielded language models that never got mass adoption. Like reel to reel. Then the transformer+attention hit the scene and several paths kicked off pretty close to each other. Google was working on Bert/encoder only transformer, maybe you could call that betamax. Doesn’t perfectly fit as in the case of beta it was actually the better tech.

OpenAI ran with the generative pre trained transformer and ML had its VHS? moment. Widespread adoption. Universal awareness within the populace.

Now with Titans (+miras?) are we entering the dvd era? Maybe. Learning context on the fly (memorizing at test time) is so much more efficient, it would be natural to call it a generational shift, but there is so much in the works right now with the promise of taking us further, this all might end up looking like the blip that beta vs vhs was. If current gen OpenAI type approaches somehow own the next 5-10 years then Titans, etc as Betamax starts to really fit - the shittier tech got and kept mass adoption. I don’t think that’s going to happen, but who knows.

Taking the analogy to present - who in the vhs or even earlier dvd days could imagine ubiquitous 4k+ vod? Who could have stood in a blockbuster in 2006 and knew that in less than 20 years all these stores and all these dvds would be a distant memory, completely usurped and transformed? Innovation of home video had a fraction of the capital being thrown at it that AI/ML has being thrown at it today. I would expect transformative generational shifts the likes of reel to cassette to optical to happen in fractions of the time they happened to home video. And beta/vhs type wars to begin and end in near realtime.

The mass adoption and societal transformation at the hands of AI/ML is just beginning. There is so. much. more. to. come. In 2030 we will look back at the state of AI in December 2025 and think “how quaint”, much the same as how we think of a circa 2006 busy Blockbuster.
by martin-t | 2025-12-08 01:44:49+00:00
> if 1K people have done similar things ad the AI learns from that, well, I don't think credit is something that should apply.

I think it should.

Sure, if you make a small amount of money and divide it among the 1000 people who deserve credit due to their work being used to create ("train") the model, it might be too small to bother.

But if actual AGI is achieved, then it has nearly infinite value. If said AGI is built on top of the work of the 1000 people, then almost infinity divided by 1000 is still a lot of money.

Of course, the real numbers are way larger, LLMs were trained on the work of at least 100M but perhaps over a billion of people. But the value they provide over a long enough timespan is also claimed to be astronomical (evidenced by the valuations of those companies). It's not just their employees who deserve a cut but everyone whose work was used to train them.

> Some people might consider this the OSS dream

I see the opposite. Code that was public but protected by copyleft can now be reused in private/proprietary software. All you need to do it push it through enough matmuls and some nonlinearities.
by fy20 | 2025-12-08 01:47:40+00:00
I had a couple of netbooks, and they weren't very useful other than as basic devices to check email or SSH. The screen was too small, the aspect ratio and resolution was weird, they keyboard was too small, they were severely under powered - in that they would struggle to play a YouTube video.

I had a couple in the late 00s to avoid having to lug around my 15" MacBook Pro when on-call. For that they worked great, but other than that I avoided it.

Later I got the 11" MacBook Air, and that had many of the same issues (especially weird screen size). It also wasn't that small, by today's standards, as it had a massive bezzle.

Nowadays I have to check if my 13" MacBook Pro is in my bag, as it's small and light enough not to notice. However I'd love a MacBook Air that is same aspect ratio as the 13" just smaller width and depth (No Apple, it doesn't need to be thinner), maybe with a 60% keyboard so typing isn't weird.
by grouchy | 2025-12-08 01:47:47+00:00
I understand the anxiety, but isn't this already the reality with most complex software?

Photoshop has thousands of possible panel arrangements, yet users develop their own workflows.

The question isn't whether permutations exist—it's whether the system helps you find your optimal permutation faster. Do you think the problem is unpredictability itself, or the lack of a predictable meta-pattern for how changes occur?
by kogasa240p | 2025-12-08 01:47:55+00:00
Since we're talking about stirling engines, I've always wondered how using geothermal heat for a larger stirling engine would work.

https://youtu.be/duuk_r--lqU?t=99

Even though the video uses the sun to heat the oil, I would think it would be feasible to use geothermal heat instead.
by nephihaha | 2025-12-08 01:48:11+00:00
I'm amazed it is a company. I wonder how far it can run with its original idea, and what the next stages would be? Tours perhaps? There are plenty of interesting places out there but once they are publicised they become everyone's property. I have bought the Atlas Obscura book and watched their channel umpteen times. Like the Rare Earth they seem to have played themselves out.
by jandrewrogers | 2025-12-08 01:49:17+00:00
What comparable alternative is available today? None of the European companies has a production 5th generation aircraft nor the integrated sensing capabilities. This is what is driving the incredible demand despite misgivings. You can't survive in a near peer combat environment without it.

Countries are buying it because it is the only game in town for certain high-value capabilities, not because they necessarily like the implications of there being a single seller of those capabilities. For better or worse, the US has been flying these for 30 years and has 6th generation aircraft in production. Everyone else is still figuring out their first 5th generation offering.

Closing that gap is a tall order. Either way, European countries need these modern capabilities to have a capable deterrent.
by ryan_lane | 2025-12-08 01:49:56+00:00
You're applying that razor incorrectly. These dollar stores are run with a skeleton crew, where it's impossible for the workers to keep the store in order, or to update the prices on the shelves. The prices of items at the register is managed centrally. They ensure resources exist to increase prices at the register and not on the shelves, and that's misleading and fraudulent.

This isn't a pricing error. They should change their practices to require prices be updated on the shelves, and for that to be verified, prior to the prices at the register applying (and this should be required by law).

It's funny that it's criminal when someone shoplifts from a dollar store, but knowingly showing one price and charging a higher price isn't a crime. We need to start treating corporate theft as crimes, rather than as a cost of business.
by crossroadsguy | 2025-12-08 01:50:24+00:00
> but I've heard good things about NextDNS

I have used them both paid and free and they are not good. I will pick just one point - support. It's pathetic. Maybe because it's non existent. I stopped paying for it, started using free, then removed it altogether.

uBlock Origin really is that good as others are saying. I haven't really needed anything else. Ads in other apps? Well, that's a hit or miss but then a lot of my finance/investment related apps anyway don't work if I use any ad blocking on local network or device label, sadly. Tweaking around it is how I needed support with NextDNS and then realised I've been paying for something with essentially no support.
by ssl-3 | 2025-12-08 01:50:36+00:00
There's variations in dollar stores, and in packaging, and deals, and everything else.

Let's play with Tide, and with Kroger and Dollar General just because those are the two retailers that are near to me. We'll do biggest and smallest, and start with the smallest.

---

The smallest bottle of original Tide that the Dollar General near me has is 34 ounces for $6.00: $0.1765 per ounce.

The Kroger near me has a similar, but lesser, bottle as their smallest offering: 32 ounce bottles for $5.99: $0.1872 per ounce.

Dollar General wins on smallest.

---

The biggest bottle of Tide at Dollar General is 115 ounces; regularly, $16.95 ($0.147 per ounce). On sale for $15.95 ($0.139 per ounce). With a $4-off digital coupon, $11.95 ($0.104 per ounce).

At Kroger: 132 ounces for $19.99 ($0.151 per ounce). (With a $5-off-of-$25 digital coupon if I feel like giving Proctor & Gamble even more of my money in one transaction.)

Dollar General also wins at biggest. They win at regular price, and today they also win at sale price.

shrug

---

Convenience also has a cost. For instance: I ran out of cat food on Christmas Day. Everything nearby was closed except for a Circle K, so I walked over there to see what they had. And they had cat food (of course they did). I bought the smallest container of Purina dry cat food I've ever seen for ~$9.

That was a lot of money for such a small amount of cat food, but I was happy to pay it. They had the right product in the right place at the right time. (And most importantly, the cat was happy.)
by tkgally | 2025-12-08 01:51:24+00:00
Here are three of the Anthropic research reports I had in mind:

https://www.anthropic.com/news/golden-gate-claude

Excerpt: “We found that there’s a specific combination of neurons in Claude’s neural network that activates when it encounters a mention (or a picture) of this most famous San Francisco landmark.”

https://www.anthropic.com/research/tracing-thoughts-language...

Excerpt: “Recent research on smaller models has shown hints of shared grammatical mechanisms across languages. We investigate this by asking Claude for the ‘opposite of small’ across different languages, and find that the same core features for the concepts of smallness and oppositeness activate, and trigger a concept of largeness, which gets translated out into the language of the question.”

https://www.anthropic.com/research/introspection

Excerpt: “Our new research provides evidence for some degree of introspective awareness in our current Claude models, as well as a degree of control over their own internal states.”
by phantasmish | 2025-12-08 01:52:26+00:00
As someone who has Apple-everything (just about) and has since 2013 or so, every time I see a headline about Apple being in serious trouble over their “AI failure” I can’t even understand what they’re talking about. Nothing I’ve seen yet is compelling enough I need it in my OS. People can reach Chatgpt on the iPhones just fine. Who cares? Who are these people like “idk might switch to Windows because of Apple’s failed AI strategy” making this an actual problem? I’ve never even understood what their supposed strategy was trying to do (at which it evidently failed? How did it fail? I also don’t follow that.)
by zozbot234 | 2025-12-08 01:53:32+00:00
Except that raw unadjusted IQ scores for even the "hardest" and supposedly most culturally unbiased test (Raven's Progressive Matrices) have consistently shown a secular gain of about one standard deviation over 30-to-40 years, due to the so-called Flynn Effect; with much of it concentrated at the low end. The whole notion that these tests simply measure some kind of purely "innate" ability is highly implausible to say the least; even more so when you compare across different cultural subgroups and even totally different countries.
by grouchy | 2025-12-08 01:53:41+00:00
I don't disagree that simple and repeatable wins—but isn't there a tension between "simple" and "capable"?

Excel is neither simple nor explicit, yet it's the most successful end-user programming tool ever made.

Could generative UI be a path to creating powerful tools feel simple by hiding complexity until needed, rather than dumbing down the tool itself?
by bitwize | 2025-12-08 01:53:54+00:00
I was trying to explain the concept of "token prediction" to my wife, whose eyes glaze over when discussing such technical topics. (I think she has the brainpower to understand them, but a horrible math teacher gave her a taste aversion to even attempting to that hasn't gone away. So she just buys Apple stuff and hopes Tim Apple hasn't shuffled around the UI bits AGAIN.)

I stumbled across a good-enough analogy based on something she loves: refrigerator magnet poetry, which if it's good consists of not just words but also word fragments like "s", "ed", and "ing" kinda like LLM tokens. I said that ChatGPT is like refrigerator magnet poetry in a magical bag of holding that somehow always gives the tile that's the most or nearly the most statistically plausible next token given the previous text. E.g., if the magnets already up read "easy come and easy ____", the bag would be likely to produce "go". That got into her head the idea that these things operate based on plausibility ratings from a statistical soup of words, not anything in the real world nor any internal cogitation about facts. Any knowledge or thought apparent in the LLM was conducted by the original human authors of the words in the soup.
by cobertos | 2025-12-08 01:54:16+00:00
I still don't quite get this reasoning. A statistical model for detecting a category (like is this written hiring material LLM generated or not, is this email spam or not, etc) is most metricized by its false positive and false negative rate. But it doesn't sound like anyone measures this, it just gets applied after a couple times of "huh, that worked" and we move on. There's a big difference between a model that performs successfully 70% of the time vs one that performs 99% but I'm not sure we can say which this is?

Maybe if LLMs were aligned for this specific task it'd make more sense? But they're not. Their alignment tunes them to provide statistically helpful responses for a wide variety of things. They prefer positive responses to negative ones and are not tuned directly as a detection tool for arbitrary categorization. And maybe they do work well, but maybe it's only a specific version of a specific model against other specific models hiring material outputs? There's too many confounding things here to not have to study this in a rigorous way to come to the conclusion that felt... not carefully considered.

Maybe you have considered this more than I know. It sounds like you work a lot with this data. But the off-handedness set off my skepticism.
by colechristensen | 2025-12-08 01:55:07+00:00
Well... they're not oracles and never will be. The things I'm creating are following recognizable development practices. It's not build-once and done, it's an elaborate design/build/test cycle that happens in many flavors because unless you've already done something and are copying it, that's how you create and language models aren't going to get away from that.
by underlipton | 2025-12-08 01:55:52+00:00
I believe there were many in Japan - including products like small laptop-shaped electronic dictionaries - but that's Japan. Their homegrown cell phones have recently picked up the moniker "Galapagos phones" because they tended to develop country-specific features and rarely leave to other markets. The same can be said for their micro/portable laptops of the early 2000s.

One could argue that OLPC made people outside of Japan aware that the form factor was possible and even optimal for some users.
by pcfwik | 2025-12-08 01:56:01+00:00
Since this is about C declarations: for anyone who (like me) had the misfortune of learning the so-called "spiral rule" in college rather than being taught how declarations in C work, below are some links that explain the "declaration follows use" idea that (AFAIK) is the true philosophy behind C declaration syntax (and significantly easier to remember/read/write).

TL;DR: you declare a variable in C _in exactly the same way you would use it:_ if you know how to use a variable, then you know how to read and write a declaration for it.

https://eigenstate.org/notes/c-decl https://news.ycombinator.com/item?id=12775966
by jacquesm | 2025-12-08 01:56:14+00:00
If a human did 2a or 2b we would think that a larger infraction than (1) because it shows intent to obfuscate the origins.

As for your free software is dead argument: I think it is worse than that: it takes away the one payment that free software authors get: recognition. If a commercial entity can take the code, obfuscate it and pass it off as their own copyrighted work to then embrace and extend it then that is the worst possible outcome.
by buu700 | 2025-12-08 01:57:17+00:00
I'd say the simple answer is that the buck always stops with the vendor. If Acme Co sells a jetpack that explodes and kills someone, the entity doesn't get to deflect liability by saying one of their engineers made a mistake; that may be an explanation, but not an excuse. Swapping out Acme Co and its employees with your grandma and her AI/robots doesn't change the fundamental principle.
by retrac | 2025-12-08 01:57:28+00:00
The Visi-On API provides a handle-based memory manager. Handles are a kind of managed pointer that allow memory blocks to be moved around even though the hardware does not have virtual memory. So long as the program always follows the rules on acquiring and releasing the handle before using the underlying pointer, it enables a kind of poor man's virtual memory. The first version of Mac OS and Windows 3.x worked in a similar way. I'm guessing that the designers of Visi-On thought of this, and the other abstractions the API provides, as a kind of virtualization.