MurphyA/hacker-news huggingface dataset:
by chneu | 2025-06-03 22:10:07+00:00
You're grossly over estimating how willing people are to inconvenience themselves for anything that doesn't immediately benefit them.

Your examples don't prove anything. Infact, I'd say they do the opposite. Bag bans are always met with tons of opposition. Electric vehicles are 50 years too late. Idk what disabled parking has to do with anything, people ignore those all the time.

People will nearly always choose the easiest and most instantly gratifying option. This is usually selfish.
by colmmacc | 2025-06-03 22:10:09+00:00
I work with a lot of smart people, many smarter than myself, and a goal I've always set myself is to leave them knowing less. Smart people are almost always more efficient at knowing more all on their own; they tend to be autodidacts and information hungry. But knowing less is much harder.

We all build up mental frameworks and systems for how we think the world is organized, and that's how we come to "know" it. It's mostly assumptions and invariants we've collected here and there. With age and experience, they become instinctual and habitual too. "Change X and Y will happen".

But when someone comes along and pops one of those foundational assumptions, "You know 'Y' doesn't always have to be true, and here's how", it is an incredible gift. A smart person will suddenly see new landscapes of possibility, optimism, and exploration that were previously out of view. What they thought they knew they now see anew.
by kenjackson | 2025-06-03 22:10:18+00:00
"And for most deep learning papers I read, domain experts have not gone through the results with a fine-tooth comb inspecting the quality of the output. How many other seemingly-impressive papers would not stand up to scrutiny?"

Is this really not the case? I've read some of the AI papers in my field, and I know many other domain experts have as well. That said I do think that CS/software based work is generally easier to check than biology (or it may just be because I know very little bio).
by alexisread | 2025-06-03 22:11:55+00:00
That's a nice take. Implicitly though, that implies treating words not as functions but as coupled routines, possibly because forth is untyped.

If anything goes wrong during development you need that model of the stack in your head to debug- I think that's the main differentiator, and if you had a typed forth with local variables, it would enable greater readability ie. I can scan the individual words/ functions without needing that stack model.

Just my POV, not sure if that resonates?
by recursive | 2025-06-03 22:12:24+00:00
When Bob Ross scrapes his knife across a canvas to create a jagged rock field, he doesn't have a detailed plan for exactly which rocks will appear and where. But he knows that that it will create a a rough patchy area alternating between two colors that will look like shadows in the context where he's doing it.

When you use the pencil tool across the screen in photoshop, it works just as a pencil on paper.

The difference is not so clear as you imply.
by freedeng | 2025-06-03 22:13:01+00:00
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by andrewd18 | 2025-06-03 22:13:21+00:00
Agreed, and we use Markdown where we can. But inevitably some product manager comes along and demands tables inside tables or embedded reuse of content... and it's back to DITA.

OxygenXML makes the OT much more manageable. I haven't had to touch an OT XSL transform in a few years now. Worth every penny.
by davidst | 2025-06-03 22:13:27+00:00
[Disclaimer: Former Amazon employee and not involved with Go since 2016.]

I worked on the first iteration of Amazon Go in 2015/16 and can provide some context on the human oversight aspects.

The system incorporated human review in two primary capacities:

1. Low-confidence event resolution: A subset of customer interactions resulted in low-confidence classifications that were routed to human reviewers for verification. These events typically involved edge cases that were challenging for the automated systems to resolve definitively. The proportion of these events was expected to decrease over time as the models improved. This was my experience during my time with Go.

2. Training data generation: Human annotators played a significant role in labeling interactions for model training-- particularly when introducing new store fixtures or customer behaviors. For instance, when new equipment like coffee machines were added, the system would initially flag all related interactions for human annotation to build training datasets for those specific use cases. Of course, that results in a surge of humans needed for annotation while the data is collected.

Scaling from smaller grab-and-go formats to larger retail environments (Fresh, Whole Foods) would require expanded annotation efforts due to the increased complexity and variety of customer interactions in those settings.

This approach represents a fairly standard machine learning deployment pattern where human oversight serves both quality assurance and continuous improvement.

The news story is entertaining but it implies there was no working tech behind Amazon Go which just isn't true.
by nostrademons | 2025-06-03 22:13:54+00:00
I'm also fascinated by the political implications on state formation, state size, and form of government.

State formation tends to track the relative military effectiveness of large highly-trained standing armies vs. small distributed arms making. The Roman Empire collapsed when they ran out of money to pay their legions. The smaller tribes and kingdoms of the Early Middle Ages unified into the larger kingdoms of the High Middle Ages as the longbow and mounted knight gave the advantage again to large, highly trained standing armies. These collapsed into the city-states of the Rennaissance because the gunpowder musket rendered all the armor of the knights useless. Then the nation-state took over as mechanized arms and airplanes became military weapons, and needed the resources of a large territory to produce them.

It's likely that the drone, being both cheap to produce, easy to use, and extremely lethal to existing weapon systems, will produce a similar political revolution. And it seems tailor-made for smaller political units: drones can lay waste to an invading army, but they suck at power projection because their range is only ~10-20 miles. Might we see a return to city-states as the primary form of political organization? Maybe all the arguments about whether Russia vs. the U.S. vs. China will come out on top are moot, because the very concept of a nation-state will disintegrate, and instead we'll have Beijing vs. Shanghai vs. Shenzhen vs. Moscow vs. Kiev vs. the Bay Area vs. NYC vs. Washington DC? Drones are also ideal for defending shipping lanes, so perhaps we'll see a loose confederation of economically-bound city-states, but each having their own culture and social laws.
by bound008 | 2025-06-03 22:14:05+00:00
Thank you so much for checking something off of my todo list!

Apple TV lets you share with two sets of apple headphones, which is awesome... but I wanted a way to:

* Share to more than two sets * Extend coverage past the (very generous) bluetooth range of AirPods. * Have lossless (albeit 44khz/16bit) wireless audio with audiophile headphones.

I was considering using an esp32, but so happy this exists now! Thanks!
by themadturk | 2025-06-03 22:14:18+00:00
A New Hope came out between my junior and senior years in college, and I was totally blown away (as I had been ten years earlier with 2001: A Space Odyssey). When my youngest son told me the prequel trilogy was his favorite Star Wars I couldn't believe it, but he pointed out that it was the Star Wars he was raised with, and saw for the first time in the theater; it was formative for him. My oldest son first really saw Star Wars when the Special Editions hit theaters, so he comes somewhere in between his younger brother and me.

I've never given up on Star Wars, though obviously there's little good to be said about the sequel trilogy and much of the Disney output. It took me a long time to even see Rogue 1, but I recognized it was something special, and Andor even moreso. (Though I will admit I like eps. 2 and 3 of the prequel trilogy more than I did at first.)
by bartread | 2025-06-03 22:14:56+00:00
> This is fake news. Builder.ai, like any other dev shop, had clients and was building apps using developers in India, pretty much like Infosys or any other Indian dev shop. Nothing wrong with that.

Yeeeah... that's a fairly disingenuous take.

The difference between every other offshore dev shop backed by developers in India and Builder.ai is that - and I say this as someone who thinks Infosys is a shit company - Infosys and all those other dev shops are at least up front about how their business works and where and who will be building your app. Whereas Builder.ai spent quite a long time pretending like they had AI doing the work when actually it was a lot of devs in India.

That is deliberately misleading and it is not OK. It's fraudulent. It's literally what Theranos did with their Edison machines that never worked so whereas they claimed they had this wondrous new blood testing technology they were actually running tests with Siemens machines, diluting blood samples, etc. The consequences of Theranos's actions were much more serious (misdiagnoses and, indeed missed diagnoses of thousands of patients), rather than just apps built by humans rather than AI, but lying and fraud is lying and fraud.
by toss1 | 2025-06-03 22:15:12+00:00
The best solution for me was to type with the left hand and switch from a mouse to a Logitech MX Ergo thumb-trackball — the key advantage is it can sit inside the sling and instantly give me full functionality.

My use case was shoulder surgery that kept my dominant right hand in a sling for two+ months, but I could use my fingers after a week or so, and much of my work is CAD.

It took only a few hours to completely get used to it, and I never went back to a mouse. While left-hand-only typing speed obviously went down, this was significantly mitigated by having a full function point-&-click device.

It turns out this setup is also really helpful when working in tight spaces where a mouse is near-impossible, such as airplanes or tight luncheon booths.

Even typing emails and multi-page documents left-handed was tolerable for 10 weeks, but if it had been longer, I probably would have looked into a chorded one-handed keyboard solution, as the learning cost would have been worth it.

I hope this helps, and good on you for helping your friend, and I hope they get well fast!
by Rochus | 2025-06-03 22:15:35+00:00
I'm using C89 and C99 very often, mostly for embedded system. Since you're a web developer, you're used to garbage collected languages. C is very bare-bone in comparison and you have to take care of details you never had to with your stack. So I think you should rather go for a language like Go, which is still pretty bare-bone compared to e.g. TypeScript with the usual tools and libraries, but still more familiar to what you are used to.
by xracy | 2025-06-03 22:15:59+00:00
Sorry, how is recycling not the scam if they were actually just pretending to recycle and not doing it?

At scale if every (or even 90% of them) solar company were pretending to get solar energy, I would absolutely consider it a scam

Also, for the most part, my understanding of plastics recycling is that it doesn't really exist in practice. Glass Recycling, and Paper Recycling are actually able to reclaim most of the product, but plastic recycling is actually only downcycling where it can be used for a different purpose.
by godelski | 2025-06-03 22:16:02+00:00
> You're here using "ground truth" in some kind of grand epistemic sense

I used the word "ground truth" because you did!

>> in agent loops with access to ground truth about whether things compile and pass automatic acceptance.

Your critique about "my usage of ground truth" is the same critique I'm giving you about it! You really are doing a good job at making me feel like I'm going nuts...

> the information an LLM natively operates with,

And do you actually know what this is?

I am a ML researcher you know. And one of those ones that keeps saying "you should learn the math." There's a reason for this, because it is really connected to what you're talking about here. They are opaque, but they sure aren't black boxes.

And it really sounds like you're thinking the "thinking" tokens are remotely representative of the internal processing. You're a daily HN user, I'm pretty sure you saw this one[0].

I'm not saying anything OpenAI hasn't[1]. I just recognize that this applies to more than a very specific narrow case...

[0] https://news.ycombinator.com/item?id=44074111

[1] https://cdn.openai.com/pdf/34f2ada6-870f-4c26-9790-fd8def563...
by jeroenhd | 2025-06-03 22:16:13+00:00
I don't think my parents will be paying $30 for Windows 10, and neither will many non-IT friends. Plus, even if you decide to go legal after a year, you're still paying the cumulative price ($60 if you buy a year of support in November 2026). I think their pricing strategy is more "don't blame us for the lack of competition in the OS space, we offered you an alternative to replacing your hardware" than "make it cheap & easy to be legal".

If they wanted to make the offer look good, I think they would've put out special offers with OneDrive storage and a year of extra security support for $5 per month rather than $2.50 a month for just updates.
by perching_aix | 2025-06-03 22:16:19+00:00
I've recently been presented the idea that art goes beyond its creator and involves its consumer(s) too. So basically, the expression goes beyond the one expressing, and includes those appreciating that expression.

But if we accept that, there's no need for the creator to be a person - since if you yourself are a person observing the art, the idea will still hold.

While I'd find this notion agreeable, I really don't subscribe to personhood being a requirement on either side of art to begin with. But maybe it's something worthwhile for your consideration.
by sings | 2025-06-03 22:16:55+00:00
Another category, searchable interfaces, may fit into one of these or may be it’s own separate category. But tools like MacOS Spotlight or the command palette in some editors are very useful for power users. Having every command available through a minimal set of fuzzy keyboard strokes is a significant productivity boost, while also allowing some degree of discoverability.

As an aside, if anyone at Adobe is reading this, this sort of tool would be an excellent addition to Illustrator, Photoshop, etc. InDesign already has something like it, although that implementation leaves a little to be desired.
by nostrademons | 2025-06-03 22:17:21+00:00
> The fact that we haven't had more drone terror attacks says more about the technological slowness of terrorists than its infeasibility.

Also motivation and incentives. The reason we haven't seen many drone attacks on civilians is that it is far more lucrative to get civilians to buy your product than to kill them, and the companies that actually have the resources to mount a credible drone attack are making a lot more money doing the former.

Terrorism in general has always been far more overhyped than actually a problem - the median number of terrorist deaths per year in the U.S. from 1970-2020 is 4, making your odds of being killed in a terrorist attack significantly lower than being struck by lightning. And the reason is simply that it's deeply irrational. What do you have to gain from killing a random stranger?
by codingdave | 2025-06-03 22:18:41+00:00
> I set up an experiment that compares the original geometry with the simplified geometry by testing 1,000,000 random points within the US.

I'd be curious if the reliability is different if, instead of random locations, you limited it to locations with some level of population density. Because a lot of the USA is rural, so that random set is not going to correlate well to where people actually are. It probably matters more the farther east you go as well, as the population centers overlap borders more when you get to the eastern seaboard.
by bhartzer | 2025-06-03 22:18:57+00:00
Classic SERP sculpting in action. Bury the bad with a flood of the old — and watch Google prioritize what’s “fresh” by post date, not relevance. Neil Patel may be under fire from FTX for $55M in alleged marketing vaporware, but it looks like the real campaign was reputation laundering by content saturation. SEO rule #1: If you can’t clean it up, outrank it.
by normalaccess | 2025-06-03 22:19:03+00:00
What about the people that want to only have one boss and not be sucked into a collective blob that only cares about money?

I am in a union and I have less rights that I did before because I can't work with my boss to figure out the best way to work. I am BOUND by contact and there are 400+ other people that I would have to convince to even change my schedule.

Unions restrict the cooperation AND YOU. Your voice becomes one in a sea and is lost in the noise.
by xnx | 2025-06-03 22:19:03+00:00
SSX was a semi-open world snowboarding game that was truly excellent, so it's very possible that Nintendo could pull it off. Mario Kart 8 Deluxe is a nearly perfect game. It lends itself to getting into a heightened flow state where you're working right at the edge of your reflexive and strategic abilities and having a ton of fun.
Show HN: Thriftled – DoorDash for local thrift stores (books and clothes first)
by michaelasiass | 2025-06-03 22:19:19+00:00
My cofounder and I noticed that thrift stores were still offline, and no one had tried to solve delivery for secondhand items the way DoorDash did for food.

We built Thriftled, which lists inventory from local thrift stores, lets users shop online, and handles delivery.

No warehouses, no massive ops overhead — stores ship directly, and we handle the UX, payments, and logistics.

We're testing with books and clothes from Value Village and a few independents. Would love your thoughts on the model, tech stack, and growth ideas.
by BizarroLand | 2025-06-03 22:19:28+00:00
No, this is smart, because then the journal could also be the thing that records all of the AI's made up on the spot sayings.

If you indexed that with the unique character descriptor then the LLM can be programed to re-read the relevant data other iterations of itself made and keep the characters somewhat consistent.

Maybe allow it other information like:

"How many in game days since last conversation" after a random number would cause the npc to forget the character "What major events have happened in the world, if any" "What events have happened in this area" "Generic gossip related to this character" "What other NPCs are doing at this time"

All of these combined into summary paragraphs would go a long way to influence what topics would be on the characters mind while also not requiring that every NPC has a perfect knowledge of all events or that the game designers have the script everything out.

Could also cause some interesting emergent gameplay, both naturally by the game world evolving over time as the characters play in it, moreso if it's a MMO.

Could also be fun to do things like advance the game clock 1,000 years and see what happens to the npcs.

What if the world is fully destructible? What if the NPCs can build new houses, expand cities, engage in trade? What if NPCs can die of natural causes, get married, have children that are genetic descendants of their parents? What if NPCs undertook quests and occasionally advanced the plot all on their own?

What if you were just one person among hundreds of thousands in the game world?

I'd love to play something like that.
by slt2021 | 2025-06-03 22:19:34+00:00
Fantastic article by Rachel Thomas!

This is basically another argument that deep learning works only as a [generative] information retrieval - i.e a stochastic parrot, due to the fact that the training data is a very lossy representation of the underlying domain.

Because the data/labels of genes do not always represent the underlying domain (biology) perfectly, the output can be false/invalid/nonsensical.

in cases where it works very well - there is data leakage, because by design LLMs are information retrieval tools. It comes form the information theory standpoint, a fundamental "unknown unknown" for any model.

my takeaway is that its not a fault of the algorithm, its more the fault of the training dataset.

We humans operate fluidly in the domain of natural language, and even a kid can read and evaluate whether text make sense or not - this explains the success of models trained on NLP.

but in domains where training data represents the fundamental domain with losses, it will be imperfect.
by callc | 2025-06-03 22:20:29+00:00
I find both the golang uppercase lowercase naming scheme and python underscores for private (and __ for *extra* private) to be terrible design choices.

They are hidden functionality, a set of rules which must be remembered. “Make sure to do <weird trick> because that mean <X> in <PL>”

Leave identifier names alone. Packing extra info inside is unnecessary mental burden
by dgs_sgd | 2025-06-03 22:21:01+00:00
> But if you're going to write about things that are important to know, you have to ask why your readers don't already know them. Is it because they're smart but inexperienced, or because they're obtuse?

What’s missing is the third and most obvious explanation.. that what you think is important isn’t necessarily what others think is important..

Perhaps PG things this falls under the “obtuse” category.
by rpruiz | 2025-06-03 22:21:30+00:00
AI answers are ephemeral, often user-specific, and influenced by changing models. Unlike traditional SEO. That makes measurement tricky and potentially brittle. Curious how you’re tackling that technically and whether there’s a sustainable data pipeline behind it.

If you’re aiming to be the “Ahrefs of AI,” think carefully about where defensibility can come from: data access, UX, integrations, or use case specificity (e.g., brand monitoring vs. keyword rank).
by godelski | 2025-06-03 22:21:35+00:00
Great, I used my program and everything seems to be working as expected.

Not great, somebody else used my program and they got root on my server...

> I have no idea how anyone could keep the callgraph of even a minimal gui application in their head

Practice.

Lots and lots of practice.

Write it down. Do things the hard way. Build the diagrams by hand and make sure you know what's going on. Trace programs. Pull out the debugger! Pull out the profiler!

If you do those things, you too will gain that skill. Obviously you can't do this for a giant program but it is all about the resolution of your call graph anyways.

If you are junior, this is the most important time to put in that work. You will get far more from it than you lose. If you're further along, well the second best time to plant a tree is today.