MurphyA/hacker-news huggingface dataset:
by kldg | 2026-03-11 06:45:20+00:00
I was a bit shocked by headline, given how poorly ARM and x86 compares to RISC-V in speed, cost, and efficiency ... in the MCU space where I near-exclusively live and where RISC-V has near-exclusively lived up until quite recently. RISC-V has been great for RTOS systems and Espressif in particular has pushed MCUs up to a new level where it's become viable to run a designed-from-scratch web server (you better believe we're using vector graphics) on a $5 board that sits on your thumb, but using RISC-V in SBCs and beyond as the primary CPU is a very different ballgame.
Ask HN: What is thick black row above top of header?
by guiambros | 2026-03-11 06:45:42+00:00
I just noticed HN now has a thick black row right above the header [1].

I don't mean any disrespect to dang or whoever designed it, but is this supposed to be a feature or a bug? :)

According to Internet Archive it was added earlier today; it wasn't there before [2]. Here's the html:

<td bgcolor="#000000">
<img src="s.gif" height="5" width="0">
</td>

Personally I prefer the clean look from before, but respect if this is a new permanent design. I use a custom HN dark theme extension, so I can just adjust it to remove the row (unless it serves some other purpose; maybe counting visitors?)

[1] 2026-03-11 01:07 https://web.archive.org/web/20260311010735/https://news.ycombinator.com/

[2] 2026-03-10 05:34 https://web.archive.org/web/20260310053447/https://news.ycombinator.com/
by dsl | 2026-03-11 06:45:48+00:00
This is a very common misconception. The issue is not IPv4 or CGNAT, it's stateful middleboxes... of which IPv6 has plenty.

The largest IPv6 deployments in the world are mobile carriers, which are full of stateful firewalls, DPI, and mid-path translation. The difference is that when connections drop it gets blamed on the wireless rather than the network infrastructure.

Also, fun fact: net.ipv4.tcp_keepalive_* applies to IPv6 too. The "ipv4" is just a naming artifact.
by backrun | 2026-03-11 06:46:04+00:00
Good question — that is exactly where tools like this either become useful or fall apart.

For DOM changes, I try not to couple the parser too tightly to fragile selectors. The extraction layer leans more on structural patterns in the rendered chat tree, and I keep the export pipeline separate from the Gemini-specific parsing so I can update that layer without rewriting the whole exporter.

For tricky formatting cases:

nested markdown is normalized into an intermediate representation first, then mapped to Word, PDF, Google Docs, or Notion

code blocks are preserved as their own block type so they do not get flattened into regular paragraph text

large tables are probably the weakest area right now, especially when Gemini renders them inconsistently or with wrapped cells

I am also building a small regression set from real chats, so when Gemini changes something in the UI I can catch breakage faster instead of fixing issues one by one.

Still early, so I would not claim every edge case is solved yet. The goal is to fail gracefully: preserve the content first, then keep as much structure as possible.

If you have a nasty sample with nested markdown, wide tables, or code-heavy output, I would genuinely love to test against it.
by the_black_hand | 2026-03-11 06:47:00+00:00
yes those are bottlenecks that world models don't solve. but the promise of world models is, unlike LLMs, they might be able to learn things about the world that humans haven't written. For example, we still don't fully know how insects fly. A world model could be trained on thousands of videos of insects and make a novel observation about insect trajectories. The premise is that despite being here for millenia, humans have only observed a tiny fraction of the world.

So I do buy his idea. But I disagree that you need world models to get to human level capabilities. IMO there's no fundamental reason why models can't develop human understanding based on the known human observations.
by weird-eye-issue | 2026-03-11 06:47:20+00:00
> but we can (and routinely do) also transcend that, question it, play with it. LLMs can’t.

Maybe not in a single inference, but you can have an LLM question itself by running another inference using its previous prompt as input. You can easily see this in a deep research agent loop where it might find some data and then it goes to find other data to back that up but then finds that it was actually incorrect and then it changes its mind
by the_duke | 2026-03-11 06:48:11+00:00
Rust has managed just fine to remain mostly backwards compatible since 1.0 , while still allowing for evolution of the language through editions.

This puts much more work on the compiler development side, but it's a great boon for the ecosystem.

To be fair, zig is pre 1.0, but Zig is also already 8 years old. Rust turned 1.0 at ~ 5 years, I think.
by rererereferred | 2026-03-11 06:48:11+00:00
The actual JS code is in the same ballpark as nodejs. They get fast by specializing to each platform's fastest APIs instead of using generic ones, reimplementing JS libraries in Zig (for example npm or jest) and using faster libraries (for example they use the oniguruma regex engine). Also you don't need an extra transpiling step when using TypeScript.
by sidkshatriya | 2026-03-11 06:49:31+00:00
I don't know why I was downvoted here. One day, I was experiencing weird compilation errors. Clearing the `ccache` C/C++ compiler cache helped get past the problem. Yes, I could have investigated in detail what was the issue and if ccache had a bug but sometimes you don't have the luxury of investigating everything your toolchain throws at you.
by NENCMediaGroup | 2026-03-11 06:51:14+00:00
Long before September 1930's national earthquake, the NSDAP had been quietly constructing institutional power in Bavaria's town halls, police stations, and regional newspapers. This feature traces how Bavarian municipal politics served as the proving ground in which the Nazi Party converted a movement of disruption into a credible bid for governance; and why the strategies rehearsed in Coburg and Nuremberg became the blueprint for Berlin. The argument is precise: Bavaria in 1930 was not the NSDAP's most reliable stronghold by accident; it was the laboratory where the party's hardest organizational problems were solved first.
by roxolotl | 2026-03-11 06:51:21+00:00
Grifting is about as American as apple pie honestly. Melville is of course know for Moby Dick where he delves into the psyche of the Great American Man but he also wrote The Confidence Man. Mark Twain’s work is full of con men and grifters. Ponzi laid the groundwork for more complex schemes in the 20s. Pyramid schemes were all the rage in the 40/50s, Tupperware parties as an example, and of course still are huge today.

It seems like whenever American society is changing very rapidly or has changed very rapidly con men become the powerful ones of the time. Maybe this is true everywhere but as an American I don’t know the history of cons in other countries.
by justsomehnguy | 2026-03-11 06:51:42+00:00
I still remember how Apple fans run around singing praises what their 8GB M1 absolutely kicked ass of Intel Macs with 16GB (and even more). Only to quietly replace them with a model with more RAM next year or some even way earlier than that.

I can open even 500 apps on any laptop. This is what swap for. But with only 8GB you are getting into the swap territory very fast because you need almost half of it for the OS and video memory.

Eg: https://news.ycombinator.com/item?id=47272996
by rhubarbtree | 2026-03-11 06:52:10+00:00
He’s still making money out of adverts on Web 2.0 platforms. A lot of money. Clearly Zuck is a brilliant businessman. That does not mean he is a brilliant technologist. He doesn’t have to be, so long as he can keep making money.

Eventually there may be a big misstep, perhaps, something big enough to bring down the company. But he’s never come close to date. He’s so good at making money from ads that he can afford to keep burning cash on fruitless projects, hiring people that don’t deliver, building infrastructure he might not need. That’s a testament to his performance as a money maker.

Meta is an advertising machine. Not something I’d want to be associated with, but you cannot deny that he has built an incredible ad machine, probably the greatest ad machine ever built - whereas Google had to deliver sophisticated and costly tech to maintain their machine (maps, google search, gmail) meta’s only technical breakthrough has been to hyperscale a php website.
by keyle | 2026-03-11 06:52:33+00:00
Note that 8GB of ram on a Mac plays out a lot more different than 8GB on a PC.

I work professionally on a Macbook Air 16GB now and I have quite a few docker images and services running bare metal, + browser, vscode etc. on top. Not a problem until I start loading up some LLMs.

The paging works wonderfully well; an advantage of everything being fused.

If anything, I'm much more bound by the CPU limitations and the eco-cores than the memory.

On a PC, I wouldn't think about less than 32GB for a dev pc.

If I had a fulltime gig programming C, I'd even say I could work on this A14 8GB device. Why not? It's as powerful as a 10 year old powerful machine; probably. Or in that ballpark.
by theshrike79 | 2026-03-11 06:52:37+00:00
When you write tests with LLM-generated code you're not trying to prove correctness in a mathematically sound way.

I think of it more as "locking" the behavior to whatever it currently is.

Either you do the red-green-with-multiple-adversarial-sub-agents -thing or just do the feature, poke the feature manually and if it looks good then you have the LLM write tests that confirm it keeps doing what it's supposed to do.

The #1 reason TDD failed is because writing tests is BOORIIIING. It's a bunch of repetition with slight variations of input parameters, a ton of boilerplate or helper functions that cover 80% of the cases, but the last 20% is even harder because you need to get around said helpers. Eventually everyone starts copy-pasting crap and then you get more mistakes into the tests.

LLMs will write 20 test cases with zero complaints in two minutes. Of course they're not perfect, but human made bulk tests rarely are either.
by boisterousness | 2026-03-11 06:52:48+00:00
Another contender: Russ Cox's "fast unrounded scaling" [1].

Cox writes: "The main idea of this post is to implement fast unrounded scaling, which computes an approximation to x · 2^e · 10^p, often in a single 64-bit multiplication. On that foundation we can build nearly trivial printing and parsing algorithms that run very fast. In fact, the printing algorithms run faster than all other known algorithms, including Dragon4, Grisu3, Errol3, Ryū, Ryū Printf, Schubfach, and Dragonbox, and the parsing algorithm runs faster than the Eisel-Lemire
algorithm. This post presents both the algorithms and a concrete implementation in Go. I expect some form of this Go code to ship in Go 1.27 (scheduled for August 2026)."

[1] https://research.swtch.com/fp
by snackbroken | 2026-03-11 06:53:03+00:00
>Yeah I'm not seeing how this is supposed to work

You could verify the ID of an adult who vouches for the child they are a legal guardian of. That way, if it turns out that Brayden(M12) is actually Linda(F45) you know who to send law enforcement to to ask some very pointed questions.

That said, I don't think online ID verification is effective and even if it was, it wouldn't be worth the level of mass privacy invasion. If your goal is actually to help kids who are victims of abuse, your efforts are much better spent elsewhere. For example: making child abuse report hotlines/websites more easily accessible and widely known, fixing social services so that they actually provide better help when requested instead of making things worse, better education for children about what is and is not OK behavior even from "trusted" adults, and how to get help from someone who isn't a relative when you need it. "Stranger danger" hysteria catches all the outrage and public discussion, but is the least common source of abuse.
by munificent | 2026-03-11 06:53:56+00:00
When someone's communication is casual and informal, without any context, you really can't distinguish between:

* The author is being flippant and not taking the situation seriously enough.

* The author is presuming a high-trust audience that knows that they have done all the due diligence and don't have to restate all of that.

In this case, it's a devlog (i.e. not a "marketing post") for a language that isn't at 1.0 yet. A certain amount of "if you're here, you probably have some background" is probably reasonable.

The post does link directly to the PR and the PR has a lot more context that clearly conveys the author knows what they are doing.

It is weird reading about (minor) breaking language changes sort of mentioned in passing. We're used to languages being extremely stable. But Zig isn't 1.0 yet. Andrew and friends certainly take user stability seriously, but you signed up for a certain amount of breakage if you pick the language today.

As someone who maintains a post-1.0 language, there really is a lot of value in breaking changes like this. It's good to fix things while your userbase is small. It's maddening to have to live with obvious warts in the language simply because the userbase got too big for you to feasibly fix it, even when all the users wish you could fix it too. (Witness: The broken precedence of bitwise operators in C.)

It's better for all future users to get the language as clean and solid as you can while it's still malleable.
by phire | 2026-03-11 06:54:43+00:00
That's really interesting. Makes me immediately ask two questions:

1. Should we be training models like this from the start? It seems that a model trained with layer loops would be able to take advantage of it better than rearranging the layers of a naive model.

2. Should we even be using a fixed number of layers? If models are this tolerant to their inner layers being meddled with, then it doesn't make sense to run all the layers on every single token.

Maybe we could make a model that changed the number of iterations through the compute layers based on how much computation it thought the problem needed. Send it through only once for easy problems (perhaps even zero times?) and two or more times for harder problems. This would allow easier prompts to complete faster, while allowing the model to potentially scale up to infinity hard problems.

If we are training or fine tuning the model, we can probably make the compute layers generate a confidence signals based that predicts how likely it is for an extra compute iteration to meaningfully change the result.
by ramblerman | 2026-03-11 06:55:53+00:00
> You have a right to perform your prescribed duty, but you are not entitled to the fruits of action. Never consider yourself the cause of the results of your activities, and never be attached to not doing your duty.

I have a hard time interpreting that as what geohotz is saying. If anything it seems to promote rent seekers by telling you - stick to your lane and don't complain. I.e. the caste system
by KingMachiavelli | 2026-03-11 06:56:34+00:00
IMO the consumer PC industry is near an existential crisis. The big players are just awful at marketing; too many SKUs and models - it takes a paragraph to figure out how 2 Dell laptops from the same release year differ. The exact same specs will be in two different chassis designs.

Additionally, you can’t count on the basic being correct. It takes a hour of research to know if the trackpad is not-awful, keyboard doesn’t suck, and display isn’t a 300nits POS unusable even in a bright room.

You want the same performance as a MacBook Air without one of these fatal flaws? You’ll hand to spend $1500+ anyway so you save nothing. Then the OS is full of ads and pre-installed garbage “gaming-optimization-tool” or driver tools taking up 99% of a single core while being riddled with security holes.
Show HN: CLI and TUI for Elasticsearch and OpenSearch
by jillesvangurp | 2026-03-11 06:57:02+00:00
I built a CLI for Elasticsearch and OpenSearch called ktsearch

You can run searches from the command line, manage indices, ILM, and data streams, inspect cat APIs like shards and indices, dump and restore indices, and monitor cluster status via a TUI (ktsearch top). Also includes bash/zsh completion.

Supports local/self-hosted clusters, Elastic Cloud, and experimental AWS OpenSearch support.

Install native binaries on Mac/Linux:

brew tap jillesvangurp/tap && brew install --cask kt-search

Or download the binaries from the release here:
https://github.com/jillesvangurp/kt-search/releases/tag/2.8....

The CLI is part of a bigger client library project that may be of interest if you work with Kotlin based backends. It's a multiplatform project, which enabled me to create a native cli for this.

Disclaimer: I've put a lot of manual work in this client over the last years but the CLI is indeed AI generated.
by ramon156 | 2026-03-11 06:57:25+00:00
I care less about receiving the money and more about the implications people have regarding money.

For example, when I'd joined a company I did not get any travel expenses. They expected me to pay the 200 euros a month myself. I'd suggested it and they shrugged it off. The company is now firing people and others are leaving.

The current company just has a default rate of money you get per km. They don't need to, but they know people want this and will ask about it.

Its a small example but it gives you a view of how a company operates
by retsibsi | 2026-03-11 06:57:51+00:00
Quoting the Wikipedia article's formulation of the task for clarity:

> You are shown a set of four cards placed on a table, each of which has a number on one side and a color on the other. The visible faces of the cards show 3, 8, blue and red. Which card(s) must you turn over in order to test that if a card shows an even number on one face, then its opposite face is blue?

Confusion over the meaning of 'if' can only explain why people select the Blue card; it can't explain why people fail to select the Red card. If 'if' meant 'if and only if', then it would still be necessary to check that the Red card didn't have an even number. But according to Wason[0], "only a minority" of participants select (the study's equivalent of) the Red card.

[0] https://web.mit.edu/curhan/www/docs/Articles/biases/20_Quart...
by dzink | 2026-03-11 06:58:35+00:00
To refer back to the trite business book section - making something new is a Blue Ocean Strategy approach. Fighting for existing market share is a bloodied Red Ocean approach that Thiel called “competition is for losers”. So both benevolent and be greedy approaches recommend the same. Make a new puddle for everyone to swim in and you can focus on empathy instead of defense.
by franciscop | 2026-03-11 06:59:35+00:00
Do you think e.g. the AI/LLM boom is all rent seeking? Do you think there's no positive value for the world on the recently announced e.g. MacBook Neo and that it's purely a monopolistic activity? Those are 2 clear recent examples of big players making massive benefits for the world, and I'm okay if they get X% of that value as company valuation.
by josephg | 2026-03-11 07:00:07+00:00
Testing works because tests are (essentially) a second, crappy implementation of your software. Tests only pass if both implementations of your software behave the same way. Usually that will only happen if the test and the code are both correct. Imagine if your code (without tests) has a 5% defect rate. And the tests have a 5% defect rate (with 100% test coverage). Then ideally, you will have a 5%^2 defect rate after fixing all the bugs. Which is 0.25%.

The price you pay for tests is that they need to be written and maintained. Writing and maintaining code is much more expensive than people think.

Or at least it used to be. Writing code with claude code is essentially free. But the defect rate has gone up. This makes TDD a better value proposition than ever.

TDD is also great because claude can fix bugs autonomously when it has a clear failing test case. A few weeks ago I used claude code and experts to write a big 300+ conformance test suite for JMAP. (JMAP is a protocol for email). For fun, I asked claude to implement a simple JMAP-only mail server in rust. Then I ran the test suite against claude's output. Something like 100 of the tests failed. Then I asked claude to fix all the bugs found by the test suite. It took about 45 minutes, but now the conformance test suite fully passes. I didn't need to prompt claude at all during that time. This style of TDD is a very human-time efficient way to work with an LLM.
by rvz | 2026-03-11 07:01:31+00:00
Two things.

> If you don’t use this new stupid AI thing you will fall behind. If you don’t use this new stupid AI thing you will fall behind. If you haven’t totally updated your workflow you are worth 0.

That is a sign that a VC over-invested and is create emotions on social media to manipulate future customers to use their portfolio company. This is a tired tactic repeated and recycled tens of thousands of times over and over.

> That said, if you have a job where you create complexity for others, you will be found out. The days of rent seekers are coming to an end. But not because there will be no more rent seeking, it’s because rent seeking is a 0 sum game and you will lose at it to bigger players.

This is why many here are realizing the uncomfortable truth about why complexity over simplicity was celebrated. Job security.

It turns out that the low hanging fruit at those companies that added close to no value, LLMs were enough to achieve "AGI" internally; (meaning layoffs). The jobs will still be there but the big money just went into CapEx on data centers (and not overpaying knowledge workers).

The truth is in the middle.
by lazystar | 2026-03-11 07:01:56+00:00
jokes on them! my ex was a narcissist who gaslit me for 8 years, left me with ptsd after threatening to stab me when we were snowed in, and isolated me from all friends and family.

lost my train of thought (ptsd flashback, ugh) but my point is, 1/ AWS leadership's motives and strategies towards their employees are childs play in the grand scheme of things, and 2/ there is a rhyme and a reason if you look hard enough. well, for most of the orgs; ironically aws support's time-to-shine is right now, but theyve been gutted since bezos left. years of mushroom treatment leads to irrecoverable brain drain.
by georgehotz | 2026-03-11 07:03:07+00:00
Building tools and services to reduce hassle and friction for others is great. However, what often happens is that you end up creating and building a moat around that hassle. Think about how companies like TurboTax lobby the government to not build electronic tax filing stuff.

Cory Doctorow explains the dynamics well in Enshittification. First they turn against their users, then their business partners, then their employees. The layoffs you are seeing are just stage 3 enshittification. If you work at a company like this, my advice is to quit ASAP. At least then you leave on your own terms.
by hulitu | 2026-03-11 07:03:15+00:00
> MacBook Neo Review: No Other Budget Laptop Can Compete

> PC Magazine came to the same conclusion:

> Similar to the Verge:

Apple pays well.
Budget laptop at 600 Euros ? And can't compete having a tablet processor, 8 MB RAM, 256 MB SSD. 2 USB ports (one i presume used for charging) ?
Yeah. It really can't compete with better options.