MurphyA/hacker-news huggingface dataset:
by koakuma-chan | 2026-02-11 17:54:45+00:00
> The Suspects Peter Thiel

Has anyone tried garlic on him?

> Vampires don’t drink blood because young blood contains an elixir. They drink blood because their own blood accumulates factors that accelerate aging, and they need to periodically dilute it.

I don't think this makes sense. Our bodies do not use the same blood forever.
by scotty79 | 2026-02-11 17:54:47+00:00
I never heard of the institution that distributes opportunities based on the result of IQ test. I only heard about IQ test for police and for military.

I'm not sure if that's what you mean by "one sided", but while you can find high IQ people in all walks of life it's very easy to find them in high achievers. And it goes way beyond lack of low IQ people. Even average IQ people are rare there.
by kakacik | 2026-02-11 17:55:00+00:00
Which evil system do they live in? Veggies are the cheapest stuff I can find in supermarkets anywhere. I agree their reward systems are fried, but thats a result of decades of over-eating on the worst junk mankind ever produced, while this whole 'evil system' screams on them from all sides how stupid and suicidal this is, how sugar is same as cocaine and so on.

Its all a mental problem (and here in Switzerland this is general consensus among doctors and I have one for wife), and an attempt to solve it anywhere else down the decision line apart from the head is just (temporarily, in case of glp) fixing the consequences.
by woeirua | 2026-02-11 17:55:03+00:00
Sorry, but that's an exceptionally unimpressive article. The crux of his thesis is:

>The main flaw is that this idea treats intelligence as purely abstract and not grounded in physical reality. To improve any system, you need resources. And even if a superintelligence uses these resources more effectively than humans to improve itself, it is still bound by the scaling of improvements I mentioned before — linear improvements need exponential resources. Diminishing returns can be avoided by switching to more independent problems – like adding one-off features to GPUs – but these quickly hit their own diminishing returns.

Literally everyone already knows the problems with scaling compute and data. This is not a deep insight. His assertion that we can't keep scaling GPUs is apparently not being taken seriously by _anyone_ else.
Show HN: TagLib-WASM – Read/write audio metadata with all JavaScript runtimes
by CharlesW | 2026-02-11 17:55:12+00:00
TagLib-Wasm wraps a WebAssembly version of the C++ TagLib library in a TypeScript/JavaScript API so you can read and write metadata for MP3, FLAC, M4A, OGG, WAV, and other audio file formats using Deno, Node.js, Bun, Electron, Cloudflare Workers, or browsers.

import { readTags, updateTags } from "taglib-wasm/simple";

const tags = await readTags("song.flac");
console.log(tags.title, tags.artist, tags.album);

await updateTags("song.flac", { title: "New Title", artist: "New Artist" });

I built TagLib-Wasm because the JS ecosystem had no complete, cross-format music metadata library. Existing options either only supported MP3, required native binaries, or couldn't write tags. TagLib itself is battle-tested (it powers VLC, Kodi, Strawberry, and others), but had no Wasm build.

On server runtimes (Deno, Node.js, Bun), it auto-selects a WASI backend that does fast and efficient seek-based I/O. In browsers, it uses Emscripten with full-buffer I/O. No configuration is needed.

This is the first 1.0 beta. I'd appreciate any feedback on the API design/DX, missing formats/features, and use cases I haven't thought of.

https://charleswiltgen.github.io/taglib-wasm/
by abustamam | 2026-02-11 17:55:41+00:00
I see comments like this a lot. In fact, I've run into it in my own side projects that I work on by myself -- what is this slop and how do i fix it? I only have myself to blame.

I can't speak to open source orgs like curl, but at least at the office, the company should invest time in educating engineers on how to use AI in a way that doesn't waste everyone's time. It could be introducing domain-specific skills, rules that ensure TDD is followed, ADRs are generated, work logs, etc.

I found that when I started implementing workflows like this, slop was less and if anyone wanted to know "why did we do it like X" then we can point to the ADR and show what assumptions were made. If an assumption was fundamentally wrong, we can tell the agent to fix the assumption and fix the issue (and of course leave a paper trail).

Engineers who waste other engineers' time reviewing slop PRs should just be fired. AI is no excuse to start producing bad code. The engineer should still be responsible for the code they ship.
by moon2 | 2026-02-11 17:55:54+00:00
From the website:

If I ever find a good moving prop like a small fan, maybe I'll also re-shoot new previews to demonstrate how shutter speed affects moving objects.

Now, I'm just not sure how would one simulate a running fan with a picture. While for a static image you can have separated foreground and background and then apply effects for simulation (I know iPhone HEIC images have this property), for moving images you have to simulate the blur and the stillness, which is probably more difficult in terms of coding.
by IshKebab | 2026-02-11 17:55:55+00:00
Yeah this is one of those "cool demo" research results that is completely impractical in the real world that is sold (probably by university PR departments) as an actual viable technique that might have real-world implications.

We've seen it before with things like taking photos around corners.

And no, it isn't like the Wright flyer and a bit crap now but in 40 years we have jet planes. This will never get significantly better.
by somenameforme | 2026-02-11 17:56:58+00:00
Batteries don't scale well when you're speaking of extremely high energy needs, especially given their deterioration over time. There's more clever things like artificial hydroelectric, but even that runs into scaling issues. Deep space solar, once established, has nice scaling potential. The inverse square distance:luminosity relationship really opens the door to some truly sci-fi type scenarios.

SpaceX is not publicly traded. It's privately owned and operated, with Elon's motivation behind the company being consistently ideological in nature. The water prices were apples to apples comparisons - the cost of a 0.33 liter bottle of water in an average restaurant.
by munk-a | 2026-02-11 17:56:58+00:00
Oh, they can certainly do that (in part evidenced by companies doing that). It's a large cost to the company, you'll get attrition and lose a lot of employee good-will, and it'll only pay off if you're right. Going with an optional system by making such tools available and incentivizing their use will dodge both of those issues and let you pivot if the technology isn't as beneficial as you thought.
by jimmaswell | 2026-02-11 17:57:08+00:00
> Education is likely declining as adoption allows students to avoid critical thought or applying concepts.

I highly doubt this will be the case. This common viewpoint is almost certainly no more than another iteration of Plato decrying the invention of books.

> Explainable by engineering isn't a miracle.

https://www.merriam-webster.com/dictionary/miracle

2: an extremely outstanding or unusual event, thing, or accomplishment. "The bridge is a miracle of engineering."
by czhu12 | 2026-02-11 17:57:08+00:00
Yeah working through documentation still. The goal isn’t so much to replace coolify. Mostly born out of my last start up that ran a $20M business, 15 engineers, with about 300-1000qps at peak, with fairly complex query patterns.

I think the single VPS model is just too hard to get working right at that scale.

I think north flank / enterprise applications, would be a better comparison of what canine is trying to do, rather than coolify / indie hackers. The goal is not take away kubernetes, but to simplify it massively for 90% of use cases but still give full k8s api for any more advanced features
by firefoxd | 2026-02-11 17:57:16+00:00
I was hoping he would provide some insight about why they avoid the sun. From observation, thiel looks like he is getting too much sun, or at least his skin has been reengineered like Alucard. While Johnson is just cake [0].

Side note: for once, I'm enjoying a heavily AI assisted article.

[0]: you'll have to find that reference on your own.
by PaulHoule | 2026-02-11 17:57:19+00:00
Pro tip: we are feeling overwhelemed with slop posts about AI. "a book by Opus 4.6" is just waving a red flag in front of a bull. The problem, as I see it, isn't that you got Opus to write it, it's that there is nothing newsworthy that you did something with AI in Feb 2026.
by kergonath | 2026-02-11 17:57:59+00:00
The model does not need to be that smart to understand that a name it does not know that starts with a capital letter is a the name of a place or a person. It does not need to be aware of whom this refers to, it just needs to transcribe it.

Also, there are generalist models that have enough of a grasp of a dozen or so languages that fit comfortably in 7B parameters. Like the older Mistral, which had the best multi-lingual support at the time, but newer models around that size are probably good candidates. I am not surprised that a multilingual specialised model can fit in 8B or so.
by dlisboa | 2026-02-11 17:58:03+00:00
Obviously not a macroeconomic analysis but if you watch YouTube channels like Caleb Hammer it seems people are literally spending their life away. No planning, no asset building, just hedonistic stuff. The kind of people you see there have the mentality of: "I'll never pay this debt down anyway so I'll max out my loans to do what I want before I die". Not very optimistic, even if it inflates the consumer market.
by testuser_xyz | 2026-02-11 17:58:07+00:00
The evolution from GLM-4.7 to GLM-5 represents an interesting inflection point in the open-source LLM landscape. While the parameter scaling (355B to 744B) and DeepSeek Sparse Attention integration are impressive engineering feats, what really caught my attention is their focus on "agentic engineering" and long-horizon tasks.

The Vending Bench 2 benchmark ($4,432 vs Claude Opus 4.5's $4,967) is particularly fascinating because it tests sustained multi-step reasoning over a year-long simulation, not just pattern matching or short-context tasks. This feels like a more honest evaluation of real-world utility.

However, I wonder if the gap between benchmark scores and actual performance will persist. The "slime" asynchronous RL infrastructure sounds promising for training efficiency, but as others have noted, RLHF quality and the human feedback loop remain challenging at scale. The fact that they're releasing under MIT license while supporting non-NVIDIA chips (Huawei Ascend, Moore Threads, etc.) suggests they're serious about accessibility.

Has anyone tried the document generation features? The ability to produce .docx/.xlsx directly seems like it could be genuinely useful for business workflows, assuming the formatting quality matches the benchmarks.
by dent9 | 2026-02-11 17:58:16+00:00
> I am extremely out of touch with anti-LLM arguments

Wow I know that feel.

I'm here using LLM for daily work and even hobbies in very conservative manners and didn't think much of it.

Now when I have casual discussions with other folks, especially non-tech people, the visceral hatred I get for even mentioning AI and the fact that I use it is insane. There's like an entire sub group of people who are so out of touch with these tools they think they're the devil like the anti-GMO crazies and the PETA psychos.
by renewiltord | 2026-02-11 17:58:25+00:00
People have always resisted change especially one that modifies the way they work. They’d rather work on the same thing for life. To get them to adopt new tools you need to do this stuff.

And yes, people did resist IDEs (“I’m best with my eMacs” - no you weren’t), people resisted the “sufficiently smart compiler”, and so on. What happened was that they were replaced by the sheer growth in the industry providing new people who didn’t have these constraints.
by jkuli | 2026-02-11 17:58:30+00:00
A simple solution is to use a system of linear equations.
Each row of a matrix is a linear equation, Ax = b
Each row contains kernel weightings A across the image X, B is the blurred pixel color.
The full matrix would be a terabyte, so take advantage of the zeros and use an efficient solve for X instead of inversion.

Enhance really refers to combining multiple images. (stacking)
Each pixel in a low res image was a kernel over the same high res image.
So undoing a 100 pixel blur is equivalent to combining 10,000 images for 100x super resolution.
by switz | 2026-02-11 17:58:48+00:00
If we get to the point that AI can run a complete business unencumbered then the world looks very different. At this time, I have very little confidence that AI today can operate my business untouched while OOO. Nor would I want it to.

But it certainly has helped me gain velocity working alone. My business is very hands off after ten years of automating most things and cleaning up the hot paths. Things break, but usually due to external factors that have nothing to do with me. A few support emails and hands-off monitoring is hardly a deal-breaker for me on vacation.

AI is really just a tool and there's a lot of incremental room between "helpful" and "totally autonomous".
by btown | 2026-02-11 17:58:54+00:00
Unless the Chrome web store integrates with this, it puts the onus on users to continuously scan extension updates for hash mismatches with the public extension builds, which isn’t standardized. And even then this would be after an update is unpacked, which may not run in time to prevent initial execution. Nor does it prevent a supply chain attack on the code running in the GitHub Action for the build, especially if dependencies aren’t pinned. There’s no free lunch here.
by moon2 | 2026-02-11 17:59:11+00:00
This is honestly the best and most simple way to learn photography, at least something basic that is still very hard to grasp sometimes. I know photography is not just about the photometer, and about depth of field, but this simple simulator helps to learn about these relationships between aperture size, shutter speed and ISO which always bugged me (sometimes my shots were bad and sometimes great).
by TimorousBestie | 2026-02-11 17:59:17+00:00
On the other hand, it’s not clear if any of it is sustainably profitable. Zitron has done a lot of reporting in this area, but since he’s “controversial” let’s stick with Forbes and the case of Sora (2025):

https://www.forbes.com/sites/phoebeliu/2025/11/10/openai-spe...

As far as I can tell, the math isn’t getting any better. The financial costs of running an AI service are enormous and it’s not clear where sufficient revenue is going to magically come from once the aggressive loss-leading ends.
by tombennet | 2026-02-11 18:00:12+00:00
Hello, author here. I built this to explain what Bitcoin miners are actually doing - not “solving complex equations” but repeatedly hashing block candidates in a lottery.

The main interactive component lets you simulate mining w/ adjustable difficulty, and shows how Bitcoin’s issuance schedule is enforced regardless of hash rate growth.

I built it with Astro. The mining simulator component runs client-side. Happy to answer any questions.
by PaulHoule | 2026-02-11 18:00:18+00:00
What do I care that it is vibe coded or not? If it is a good app, it's a good app. If you say "vibe coded" in the subject people aren't going to judge it in terms of its quality, it's just more slop posts about AI. Take a look at how the /new page is overwhelmed with low-quality posts about AI and how the front page shows people are desperate for anything else.
by asa400 | 2026-02-11 18:00:54+00:00
It's extremely human behavior. We all do it to some degree or another. The incentives work like this:

- If all your peers are doing it and you do it and it doesn't work, it's not your fault, because all your peers were doing it too. "Who could have known? Everyone was doing it."
- If all your peers _aren't_ doing it and you do it and it doesn't work, it's your fault alone, and your board and shareholders crucify you. "You idiot! What were you thinking? You should have just played it safe with our existing revenue streams."

And the one for what's happening with RTO, AI, etc.:

- If all your peers are doing it and you _don't do it_ and it _works_, your board crucifies you for missing a plainly obvious sea change to the upside. "You idiot! How did you miss this?"

Non-founder/mercenary C-suites are incentivized to be fundamentally conservative by shareholders and boards. This is not necessarily bad, but sometimes it leads to funny aggregate behavior, like we're seeing now, when a critical mass of participants and/or money passes some arbitrary threshold resulting in a social environment that makes it hard for the remaining participants to sit on the sidelines.

Imagine a CEO going to their board today and going, "we're going to sit out on potentially historic productivity gains because we think everyone else in the United States is full of shit and we know something they don't". The board responds with, "but everything I've seen on CNBC and Bloomberg says we're the only ones not doing this, you're fired".
by SkiFire13 | 2026-02-11 18:01:00+00:00
> If you use it to talk to friends, you'll presumably have your computer on when you want to use it yourself anyway.

I tried this in the past but it didn't work. Now if your friends want to play you need to start the server for them. What if you're not at home? You basically end up making your pc a 24/7 server. Or you need to coordinate so that someone else runs the server in those cases, but that ends up creating more confusion. And let's not start talking about port forwarding issues...

All these issues are solvable, but they add so much friction when all you want to do is play with some friends.
by munch117 | 2026-02-11 18:01:34+00:00
I'm slightly taken aback by the telnetd fix: The solution to the username "-f root" being interpreted as two arguments to /usr/bin/login is to add a "sanitize" function, really? I'm not seeing the sense in that. Surely in any case where the sanitize functions changes something, the login will fail. Better to error out early than to sanitize and try to hobble along.

What I'd like to know is how the arguments get interpreted like that in the first place. If I try giving that kind of argument /usr/bin/login directly, its argument parser chides me:

$ login '-f root'
login: illegal option --

What's telnetd doing differently? Is it invoking login via a shell?
Show HN: Gottp – A Postman/Insomnia-Like TUI API Client Built in Go
by sadopc | 2026-02-11 18:01:37+00:00
What it does: A Postman/Insomnia-like TUI for building, sending, and organizing HTTP/GraphQL/gRPC/WebSocket requests. Supports saved collections stored as YAML/JSON files, environment variables, auth presets, response diffing, and request history.

Why it's needed: This is the single largest gap in the Go TUI ecosystem. The abandoned wuzz (10.5k stars) proved massive demand for terminal HTTP inspection, but it's been dead for years. Posting (Python, ~6k stars) and ATAC (Rust, ~2k stars) are thriving alternatives in other languages. The Go options — gostman and go-gurl — are learning projects with known limitations. Developers who work over SSH or prefer keyboard-driven workflows have no mature Go tool for API testing.

Existing alternatives: Posting (Python/Textual), ATAC (Rust/ratatui), wuzz (Go, abandoned), Bruno (GUI). A Go version wins via single-binary distribution, no Python runtime dependency, and Go's excellent HTTP/networking standard library.

Complexity: Hard. Multi-protocol support, collection management, and auth handling require significant engineering.

Libraries: Bubble Tea + Bubbles (tabs, text inputs, lists) + Lip Gloss + Glamour (for response rendering)
by mandevil | 2026-02-11 18:01:41+00:00
> There's a sentiment that the monthly numbers were purposely inflated for 2025.

Jobs data (which comes from a survey of employers) is always subject to revisions, and the revisions have gotten worse. But it's not necessarily political. Back when Trump unprecedentedly fired Erika McEntarfer (former head of the BLS) I looked into this and tried to understand where the data comes from, how it works.

Basically, the BLS surveys 50k out of the several million companies in the US. But response rates have dropped rather strongly since the Pandemic in particular. If you give them 3 months, it gets up to 90%, but after 1 month it is only 50%. This would be okay, except that the response rates turn out to be skewed: large companies almost always respond quickly, small companies respond more slowly. And small companies tend to be much more responsive to the state of the overall economy than large companies- for good and for bad. And even the response times of the small companies turn out to be sensitive to economic trends, for good and for bad: the companies that respond more slowly to surveys, it turns out, tend to be the most sensitive to the broader economy, the first to fire in a recession, but also the first to hire when the economy is getting better.

The final thing is that these companies can be highly correlated with each other and the broader economy. So there are always corrections, but in placid economic weather the corrections cancel out- some of the extrapolations are high, some are low, it ends up being close to 0. And the financial markets understand how to read these corrections. They understand that when the economy is shifting you will get all of the misses in the same direction- either high or low- and to pay attention these corrections data.

All of these misses low in 2025 are a very bad sign for the economy overall, not necessarily a sign of political pressure. That would probably show up in large, sustained differences to the ADP numbers or other privately reported numbers, rather than revisions announced by the BLS itself.

Both Trump I's appointee to head the BLS, William Beach (who served from 2019-2023) and Biden's appointee Erika McEntarfer (whom Trump fired in 2025) wanted to modernize the survey system, make it easier for companies to respond, and get better and faster data collection. But, because this system is so incredibly important to the markets, they wanted a larger budget to run the new system and the old system together for a significant portion of time (several years) so that everyone would be comfortable understanding the intricacies of the system, what revisions would mean, etc. And since they didn't get that budget (in fact it got cut) they decided to prioritize the old system rather than throw it away and experiment with something different.
by caseyohara | 2026-02-11 18:01:55+00:00
Shell was originally very literal though. They sold seashells.

> The "Shell" Transport and Trading Company (the quotation marks were part of the legal name) was a British company, founded in 1897 by Marcus Samuel, 1st Viscount Bearsted, and his brother Samuel Samuel. Their father had owned an antique company in Houndsditch, London, which expanded in 1833 to import and sell seashells, after which the company "Shell" took its name.

https://en.wikipedia.org/wiki/Shell_plc
by mlyle | 2026-02-11 18:02:05+00:00
Yah. He didn't write the Feynman Lectures on Physics. He just came up with the unique arguments in them and gave the lectures at Caltech; it fell to Leighton and Sands to do most of the work of knitting it into a cohesive, coherent book.

And his other books-- they're just his stories, trying to capture the characteristic style in which he talked, while editing it to be a cohesive written work.

This criticism is maybe valid for QED-- I am not sure what fraction of that he was really involved in-- but not the rest of his body of work.
Is this supposed to be bad?