MurphyA/hacker-news huggingface dataset:
by sneak | 2025-07-09 11:56:19+00:00
The US wasn’t the dominant superpower due to cooperation or agreement or leadership, it was the result of pure technological force.

Oppenheimer, Teller, and countless nameless others at NASA and Lockheed and Boeing and DARPA.

The US built the best weapons, spy planes, launch vehicles, satellites, and communications systems, and was willing to take a no-holds-barred approach to geopolitical strategy. This led to a circumstance which it seems was unparalleled in history thus far.

Who else is able to commit such technological progress to being able to command the world order by edict?

China, perhaps, but I don’t see the next TSMC or SpaceX or OpenAI or Google starting there. Technology is the name of the game. (My own personal take is that mass scale reusable rockets is the key strategic piece to geopolitical dominance over the next 50-100 years, with perhaps the ability to effectively integrate AI as an alternate or close second.)

It may be that we never see a monolithic superpower of the same kind again for generations. The post ww2 world order was really very very kind to the USA.
by MSFT_Edging | 2025-07-09 11:56:22+00:00
When has the US actually overshot left though? There was a short period of social justice awareness, but that didn't translate to actual leftwing economic legislation. Even protests and movements with left wing goals were co-opted by the nominally center-right establishment and neutered.

This both-sides stuff gets me, man. Our history is by and large very right wing and every time there's a flutter of left leaning ideas, people chalk it up to some far-left political success and therefore the far right backlash is deserved, as if things ever actually went left in the first place.
by fatbobman | 2025-07-09 11:56:53+00:00
Text is heavily used in SwiftUI. Compared to its counterparts in UIKit/AppKit, Text requires no configuration and works out of the box, but this also means developers lose more control over it. In this article, I will demonstrate through a real-world case study how to accomplish seemingly “impossible” tasks with SwiftUI’s approach: finding the first view among a given set where text is not truncated, and using it as the required size.
Show HN: Discord-oidc-proxy: Convert Discord to an OIDC provider
by taiseiue | 2025-07-09 11:57:36+00:00
Ever wanted to use Discord authentication with your existing OIDC-compatible applications? discord-oidc-proxy is a serverless solution that converts Discord's OAuth2 into a standards-compliant OpenID Connect (OIDC) provider. Runs on Cloudflare Workers. (Should I make it work with Docker too? I'm waiting for your opinion.) I've implemented DI (Dependency Injection) in my programming project!

Features: - Use Discord authentication through standard OIDC flows

- Serverless design running on Cloudflare Workers

- Lightweight implementation built with Hono framework

- Full OIDC Discovery support (/.well-known/openid-configuration)
by pjc50 | 2025-07-09 11:57:44+00:00
I'm on team "Windows should just accept and change to write and read CR and '/'. beginning the decades long transition process for those". Most of the APIs accept '/', and most of the software accepts CR-only.

I think even Microsoft have noticed this, which is why WSL exists to provide an island of Linux-flavored open source tooling inside a Windows environment.
by Angostura | 2025-07-09 11:58:12+00:00
For many works, even the best photographs don't entirely capture the physical object - particularly those where texture, including brush strokes is important. Many pigments can't be duplicated via the standard printing gamut. This particular work is a woodblock print, so perhaps photography is adequate - I don't know.

I'm not clear that the original artist's materials, with respect to longevity is really relevant, assuming the artist didn't explicitly intend it to be ephemeral.
by baq | 2025-07-09 11:58:37+00:00
Foundation models are basically compressed databases of a big chunk (75%?) of human knowledge and the query language is English (...and many others) and you're saying it's a bubble to be ignored.

Meanwhile, model providers are serving millions if not billions of tokens daily.

Don't want to say this is a dropbox comment class blog post, but certainly it... ignores something.
by anonymars | 2025-07-09 11:58:52+00:00
I present to you this monstrosity: https://stackoverflow.com/q/39110233

Presumably they had an existing API, and then REST became all the rage, so they remapped the endpoints and simply converted the XML to JSON. What do you do with the <tag>value</tag> construct? Map it to the name `$`!

Congratulations, we're REST now, the world is a better place for it. Off to the pub to celebrate, gents. Ugh.

I think people tend to forget these things are tools, not shackles
by sneak | 2025-07-09 11:59:11+00:00
> Some companies, like Meta, went even further. They didn’t just use web content—they also used pirated books to train their models. (The Unbelievable Scale of AI’s Pirated-Books Problem) If a regular person did this, they’d probably get into serious trouble. But when billion-dollar companies do it, they usually get away with it.

Someone should tell Anna’s Archive.

The US’s criminal enforcement is very much biased into the “rules for thee, but not for me” category, but invoking it here is a trope. Anyone can get away with piracy on the scale of Books3 or The Pile. The reason random people don’t make models is because the hardware and power costs are fucking astronomical, not because they can’t get away with downloading the training data.

These sort of hot takes are just as wrong as the breathless “AGI is right around the corner” ones.

AI is hugely transformative, and anyone who thinks it’s overhyped doesn’t know the SOTA. It will likely be the single biggest technological advancement of our lifetime.
by simonw | 2025-07-09 11:59:14+00:00
This is a great example of the kind of question I'd love to be able to ask these documentation bots but that I don't trust them to be able to get right (yet):

> What’s the syntax, in Liquid, to detect whether an order in an email notification contains items that will be fulfilled through Shopify Collective?

I suspect the best possible implementation of a documentation bot with respect to questions like this one would be an "agent" style bot that has the ability to spin up its own environment and actually test the code it's offering in the answer before confidently stating that it works.

That's really hard to do - Robin in this case could only test the result by placing and then refunding an order! - but the effort involved in providing a simulated environment for the bot to try things out in might make the difference in terms of producing more reliable results.
Agent simulations = unit testing for AI?
by draismaa | 2025-07-09 12:00:13+00:00
In traditional software, we write unit tests to catch regressions before they reach users. In AI systems—especially agentic ones that model breaks down. You can test inputs and outputs, use evals, but agents operate over time, across tools, mcps, apis, and unpredictable user input. The failure modes are non-obvious and often emerge only in edge cases. I'm seeing an emerging practice: agent simulations—structured, repeatable scenarios that test how an AI agent behaves in complex or long-tail situations.

Think: What if the upstream tool fails mid-execution? What if the user flips intent mid-dialogue? What if the agent’s assumptions were subtly wrong?

from self-driving cars to AI agents? The above aren’t one-off tests. They’re like AV simulations: controlled environments to explore failure boundaries. Autonomous vehicle teams learned long ago that real-world data isn't enough. The rarest events are the most important—and you need to generate and replay them systematically. That same long-tail distribution applies to LLM agents. We’ve started treating scenario testing as a core part of the dev loop—versioning simulations, running them in CI, and evolving them as our agent behavior changes. It’s not about perfect coverage,it’s about shifting from “test after” to “test through simulation” as part of iterative agent development. Curious if others here are doing something similar. How are you testing your agents beyond a few prompts and metrics? Would love to hear how the HN crowd is thinking about agent reliability and safety—not just in research, but in real-world deployments.
by Barrin92 | 2025-07-09 12:00:18+00:00
>SusSE was one of my favourite distros

it's honestly a crime that they don't get more traction. Tooling they've put out like the Open Build Service (which is distro agnostic), is fantastic. I've been using Tumbleweed on dev machines for a long time, and the fact that they ship fully tested images is imo just a vastly better way to do a rolling release.
by bshepard | 2025-07-09 12:00:21+00:00
On a more conceptual angle, Landrebe and Smith's "Why Machine's Will Never Rule the World" clarifies the limits of computation w/r/t complex dynamic systems.

Here is the core argument: "an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: 1. Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. 2. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer.
by _heimdall | 2025-07-09 12:00:44+00:00
What's often missed when this topic comes up is the question of who the back end API is intended for.

REST and HATEOAS are beneficial when the consumer is meant to be a third party that doesn't directly own the back end. The usual example is a plain old HTML page, the end user of that API is the person using a browser. MCP is a more recent example, that protocol is only needed because they want agents talking to APIs they don't own and need a solution for discoverability and interpretability in a sea of JSON RPC APIs.

When the API consumer is a frontend app written specifically for that backend, the benefits of REST often just don't outweigh the costs. It takes effort to design a more generic, better documented and specified API. While I don't like using tools like tRPC in production, its hugely useful for me when prototyping for much the same reason, I'm building both ends of the app and its faster to ignore separation of concerns.

edit: typo
by layer8 | 2025-07-09 12:00:52+00:00
Take this quote: “A REST API should be entered with no prior knowledge beyond the initial URI (bookmark) and set of standardized media types that are appropriate for the intended audience (i.e., expected to be understood by any client that might use the API). From that point on, all application state transitions must be driven by client selection of server-provided choices that are present in the received representations or implied by the user’s manipulation of those representations.”

If the client application only understands media types and isn’t supposed to know anything about the interrelationships of the data or possible actions on it, and there is no user that could select from the choices provided by the server, then it’s not clear how the client can do anything purposeful.

Surely, an automated client, or rather its developer, needs a model (a schema) of what is possible to do with the API. Roy Fieldings doesn’t address that aspect at all. At best, his REST API would provide a way for the client to map its model to the actual server calls to make, based on configuration information provided by the server as “hypertext”. But the point of such an indirection is unclear, because the configuration information itself would have to follow a schema known and understood by the client, so again wouldn’t be RESTful in Roy Fielding’s sense.

People are trying to fill in the blanks of what Roy Fielding might have meant, but in the end it just doesn’t make a lot of sense for what REST APIs are used in practice.
by pradn | 2025-07-09 12:01:18+00:00
In the simple (albeit niche) case, a UI could populate a list of buttons based on the URIs/verbs that the REST API returns. So the UI would be totally dynamic based on the backend - and so, work pretty generically across REST APIs.

But for a client, UI or otherwise, to make use of a dynamic set of URIs/verbs would require it to either look for a specific keyword (hard coding the intents it can satisfy) or be able to semantically understand the API (which is hard, requires a human).

Oddly, all this stuff is full circle with the AI stuff. The MCP protocol is designed to give AIs text-based descriptions of APIs, so they can reason about how to use them.
by edg5000 | 2025-07-09 12:02:19+00:00
Google has been crawling the web. I think it's about limiting to 1Hz per IP. This means a site with 100 000 pages will take 24 hours to crawl. The crawler could send requests as fast as possible, just distributed across IPs.

If I put a website up, everything goes as long as people don't DDoS me. A human crawls at ~1Hz, if a bot tries 1000Hz, this is a denial of service attack. It's hard to block since you can't rate limit IPs due to many people sharing the same IP. So you need heuristics, cookies, etc.

Putting paywalled content in the AI is not cool though (such as books), nobody was anticipating this, people got effed unexpectedly. This is piracy on hyperscale. Not fair.
by JKCalhoun | 2025-07-09 12:02:21+00:00
> Ever since ChatGPT came out, the tech world has jumped on a new hype train—just like it did before with crypto, NFTs, and the metaverse.

Personally, I eschewed all of those — except for LLMs. I'm convinced this one's for real. People though can use "hype" to mean a number of things.

AGI by the end of the year? Hype.

Decimation of white-collar jobs? Hype.

Fundamentally new paradigm and tech the world will have to adapt to? Not hype at all.

> Eventually, these companies tried something new: agents.

Yeah, that one's still on the hype shelf for me.

> This floods social media and websites with low-quality, copy-paste content.

No! Welp, there goes social media. ;-)

> ChatGPT has around 500 million weekly active users, but only around 20 million of them actually pay for a subscription. That means the vast majority of people think it’s not worth $20 a month.

You could say the same for YouTube (and likely wildly surpass that scenario).

When you offer a free version, don't be surprised if most users (meekly raises hand) save their pocket money for something else. These are early days and people are sussing out what the thing can do for them.

> To me, Apple stands out. They aren’t trying to build a chatbot that knows everything. Instead, they’re focused on using AI as a tool to help people interact with their apps and data in smarter ways.

That feels like Apple in gap-filling mode: trying to show the world they're doing something while smart people are trying to figure out what Apple really ought to be doing.

They have their own chip dies — could perhaps do a dedicated LLM client architecture that allows it to run on-device? It makes you wonder what Jony Ives (and investors) could possibly be thinking when Apple could easily pivot and own the aiPhone market.

Waiting for my own aiPhone someday — with encrypted history saved to my cloud account. Wondering what it will be like for future generations who will have had a personal confidant for decades — since they were teenagers…
by linuxscooter | 2025-07-09 12:02:42+00:00
I’ve been writing oversized shell scripts for ages, often just for the moment in Bash.

Then if I need something similar for a Dockerfile, I’d write that also. The duplication is a sad feeling.

So I described what I wanted, /bin/sh with posix, detailed what both scripts do, and it merged both scripts without ever seeing their full codebases! (Both for work and my own code, I never share code unless it’s already in a public repository)

I fired up ShellCheck linter and zero issues. At work I Replaced both tech-debt laden scripts with a repo and people said they’d use it too, NICE cleanup, and how long did it take? :-)
by JCM9 | 2025-07-09 12:04:04+00:00
The “we don’t need as many workers because AI” line from CEOs isn’t sticking. It might work for a quarter or two but sooner or later these companies must answer hard questions on why they’re not getting measurable returns from massive investments in AI. That day is coming and it’s going to be really ugly.

Same for many of these “AI companies” that are burning through cash in a race to the bottom towards a commodity with no real prospects for a sustainable business model. The tech is cool, and can be useful, but the business aspects of all this is a forrest full of dry timber waiting for one strike of lightning to burn the whole thing to the ground.
by rijoja | 2025-07-09 12:04:53+00:00
Right I'm not trying to be argumentative here, I see where you are coming from right.

My point being that it's quite easy to demonstrate that it can't scale, by running an experiment.

Meaning that you could quite easily BS your way through that by just agreeing with whatever the status quo is.

Whereas in social science you can't do an empirical experiment, so you're epistemologically on much much more shakier ground

> This happens in maths, biology, in all science fields Right but I wrote social science and not maths or biology.

For instance if someone where to say that due to Hegelian Dialeticts and gender critical theory, in the future women are destined to rule the world, this is a good thing, and this will lead to the abolishment of racial inequality and exploitation through capitalism

how do you prove that?

in comparison if the problem is that your software isn't efficient when there are over 100 instance, you can prove that by spinning up 100 instances?

You can't clone earth and force all the inhabitants to enact ideologically pure race critical theory, and then ask the inhabitants in the control group to try out nazism, wait for a while and then use that to prove that one or the other is the best way can you?
by DaSHacka | 2025-07-09 12:05:06+00:00
> It may be that we never see a monolithic superpower of the same kind again for generations. The post ww2 world order was really very very kind to the USA.

And why do you think it couldn't remain that way? Considering SpaceX, OpenAI, and Google were made far, far closer to today than to WWII, why would the assumption be that the output suddenly stops?
by Toutouxc | 2025-07-09 12:05:10+00:00
> If you have a bunch of Zigbee devices, but at some point want to add some of the new ones, you need to start thinking about replacing all the perfectly working Zigbee devices or have a fragmented network.

Yes, if you're using the manufacturer's half-assed smartphone app, but if you're on Home Assistant, like basically anyone who's serious about their smart home, having multiple kinds of smart devices isn't really a problem. It's just one more radio to configure. Some people run both Zigbee and Zwave, some people run Zigbee + Wi-Fi or even Zigbee + Zwave + Wi-Fi + cloud integrations, Home Assistant doesn't care.
by sdrapkin | 2025-07-09 12:05:22+00:00
No, Guid/uuids are defined as 128-bit labels used to uniquely identify objects in computer systems. This 128-bit/16-byte definition predates any RFCs that one may or may not choose to implement. I'm obviously aware of RFC 9562, and nowhere in the Guid library do I claim implementation of it. RFC 9562 is a choice, and one that should not be made blindly, or for you. It all starts with 16 random bytes. Google's uuid starts that way, and virtually every other Guid/uuid implementation. Then, on top of that building block, one may tweak additional non-random bits if the usecase truly requires it. If it does - you can do it quickly and cheaply on top of 16 random bytes. If the usecase does not require it (99% of cases), you're better off with the foundational 16 random bytes. The perspective of "your 16 random bytes do not implement RFC 9562 - BAD, BAD!" is very myopic. But if wasting bits on versions and variants is something that helps someone sleep better - they can easily and cheaply achieve that with a couple of bit ops. RFC 9562 robs developers of that choice.
by Tuna-Fish | 2025-07-09 12:05:31+00:00
A symlink is just a special file that contains a string of text, it's not tightly bound to the target like a hard link. You can write anything into that string of text, including, say, "~/.bashrc". Then you can ship that symlink onto another system, and it suddenly points to your .bashrc.

Git just moves symlinks across systems as is, so yes, you can use git to deploy the exploit.
by brookst | 2025-07-09 12:07:05+00:00
This is a terrible article, apparently one of those that starts with a title and then goes in search of every possible argument to support the conclusion.

The whole thing is bad and disingenuous (somehow the very real impact of excessive crawling by AI companies in an indictment of the value of the output).

And it just gets worse. For instance:

> If you’re looking something up [on a search engine], you usually type a few keywords and get a list of links. But with a chatbot, you have to write full sentences, and how fast you can type limits how fast you can interact. Then, instead of getting quick, scannable links, you get a big block of text. You read it—but you’re always aware it might be wrong. On a regular search engine, you can judge a source just by looking at the domain of the website, the design of the page or even reading the “About” page.

Got that? Chatbots make you type whole sentences, and instead of a short list of links the reader can easily scan, click through, analyze quality of graphic designs, and read the obviously-totally-trustworthy About pages to determine accuracy… you get answers in one place that could be wrong.

The fact that all chatbots include citations that you can click to do the same rigorous design-based fact checking is omitted, presumably because it would weaken the argument.

There are legit reasons to dislike the ethics of AI companies, and there are legit reasons believe this is a dot bomb style bubble, and there are legit reasons to be skeptical that the tech has enough headroom to reach AGI.

But this article just puts little bits of each in a blender and hopes for the best. It’s funny because while decrying “hype”, it uses all the same cheap and lazy rhetorical techniques as the worst AI hypesters. Further illustrating the “you become what you hate” principle, I suppose.
by edg5000 | 2025-07-09 12:07:30+00:00
No, I think the book pirating thing is different than an individual pirating. It's like comparing genocide to murder. A few murders, not great. A few genocides? Really not cool.

This book thing at Meta is something we should never forget. It revealed how utterly broken the US is in this regard, hope they get it sorted. Without the rule of law you'll get a shit country.
by matsemann | 2025-07-09 12:07:47+00:00
I don't have anything particular against using AI tools in my workday in the future. I just don't want to spend my time experimenting with it now, and have no need to be on the bleeding edge. If in a year things are stable and useful, I can just learn whatever is vogue then. You won't miss out by not jumping on the train now. Most tools I use were made long before I started my career as a software engineer, and still I got up to speed. There is no big moat that experienced developers won't be able to quickly get over.
by nijave | 2025-07-09 12:08:35+00:00
I have use cases for linking Terraform lock files to keep various deployments/modules on consistent versions. I could see there being a use case for symlinking Chart.lock files although usually that's limited to an internal implementation and not something a general purpose chart would probably ship

i.e. you have 3 different charts that all depends on `cache`, `load balancer` and `database` charts and you want to only ever have 1 version deployed of those subcharts so you want the parent chart locks linked