MurphyA/hacker-news huggingface dataset:
Show HN: TypeCrt – Zero-latency typing test in vanilla TS, no frameworks
by shadowline | 2026-03-05 09:18:50+00:00
Hey HN, I built TypeCrt because every typing test I tried had noticeable input lag at 150+ WPM. Monkeytype uses React. Keybr uses React. 10FastFingers feels like 2012. So I built one from scratch with vanilla TypeScript, vanilla CSS, and direct DOM manipulation — no React, no Vue, no Angular.

The result: zero perceptible input latency, even at 200+ WPM.

Some things I'm proud of:

- CRT terminal aesthetic with 50+ themes and a visual theme creator
- Adaptive practice mode ("KeyForge") that uses Markov chains to generate words targeting your weakest keys
- Per-word burst speed breakdown, keystroke heatmaps, consistency tracking
- Command palette (Ctrl+Shift+P), mechanical keyboard sounds, pace caret ghost
- Cloud sync via Firebase, tiered analytics dashboard

Tech stack: TypeScript (strict) + Vanilla CSS + Vite. ~15K lines. No dependencies beyond Chart.js and Firebase.

I'd genuinely love feedback from this community — especially on performance, UX, and what features would make you switch from your current typing tool.
by akinalpfdn | 2026-03-05 09:19:07+00:00
Hey HN, I built GridSnap because I was tired of digging through notes and docs to copy-paste things I use repeatedly — server addresses, SQL queries, config values, template messages.

It's a spreadsheet-like desktop app that lives in your system tray. Ctrl+Shift+Space pulls it up, you click a cell, it's copied. That's the whole UX.

Technical decisions:
- Tauri v2 over Electron: ~3MB bundle vs ~85MB, ~30MB RAM vs 200MB+
- Custom virtualized grid: 1000×26 cells, only visible cells rendered
- Rust backend: AES-256-GCM + Argon2id for encryption, all crypto/IO in Rust
- Sparse storage: empty cells don't allocate memory
- CSS custom properties theming, zero inline styles

Still early — the dev plan covers 7 phases and I'm working through them. Feedback on architecture decisions welcome.
by vanillameow | 2026-03-05 09:19:09+00:00
Regardless, I think if you are thinking purely from a ruthless business standpoint then standing up to the DoD was an incredibly ill-advised move. It's basically free financial and technological backing at the cost of ethics. Additionally, basically everyone with functioning eyeballs knows that the current US administration is incredibly vindicative, reckless and short-tempered. I would agree that in a more tame administration, you might do something like this as a publicity stunt. In the Trump administration, and while the AI arms race is still in full force, it feels like there has to be at least somewhat genuine sentiment behind it, otherwise it just doesn't really make sense. Like what do they accomplish from this? You'll get some users who will view you more favourably for it but it probably won't make up for the lost revenue, and no matter how many people like you, if you are first to AGI in this industry you win. The prior sentiment basically won't matter at that point. In the most critical interpretation I guess you could say if the bubble pops it might be more of a matter of sentiment. I don't know, in my mind the math just doesn't work for it to be a business move.
by akimbostrawman | 2026-03-05 09:19:30+00:00
>People get arrested for tweets like calling for the homes of asylum seekers to be set on fire.

No but nice strawman straight out out of the eu oligarch handbook. Threats and calls to violence are already a crime even in the US and rightfully so.

10 seconds of research would show you criticism and jokes will get you prosecuted and raided:

https://brusselssignal.eu/2024/11/german-police-raid-mans-ho...

https://www.mainzer-medieninstitut.de/erfolglose-verfassungs...

Looking forward to your on topic justification.
by tovej | 2026-03-05 09:20:10+00:00
We already have tools to generate boilerplate, and they work exceptionally well. The LLM just produces nondeterministic boilerplate.

I also don't know what work you do, but I would not characterize the codebases I work in as "small bits of novelty" on boilerplate. Software engineering is always a holistic systems undertaking, where every subcomponent and the interactions between them have to be considered.
by spoiler | 2026-03-05 09:20:15+00:00
That whole clean room argument makes no sense. Project changed governance and was significantly refactored or reimplemented... I think the maintainers deserve to call it their own. Original-pre MIT release can stay LGPL.

I don't think this is a precedent either, plenty of projects changed licenses lol.

I keep kind mixing them up but the GPL licenses keep popping up as occasionally horror stories. Maybe the license is just poorly written for today's standards?
by Roritharr | 2026-03-05 09:21:05+00:00
As part of my consulting, i've stumbled upon this issue in a commercial context.
A SaaS company who has the mobile apps of their platform open source approached me with the following concern.

One of their engineers was able to recreate their platform by letting Claude Code reverse engineer their Apps and the Web-Frontend, creating an API-compatible backend that is functionally identical.

Took him a week after work. It's not as stable, the unit-tests need more work, the code has some unnecessary duplication, hosting isn't fully figured out, but the end-to-end test-harness is even more stable than their own.

"How do we protect ourselves against a competitor doing this?"

Noodling on this at the moment.
by scosman | 2026-03-05 09:21:49+00:00
Sounds like they didn’t build a proper clean room setup: the agent writing the code could see the original code.

Question: if they had built one using AI teams in both “rooms”, one writing a spec the other implementing, would that be fine? You’d need to verify spec doesn’t include source code, but that’s easy enough.

It seems to mostly follow the IBM-era precedent. However, since the model probably had the original code in its training data, maybe not? Maybe valid for closed source project but not open-source? Interesting question.
by ternaus | 2026-03-05 09:22:00+00:00
I wrote a long practical guide on image augmentation based on ~10 years of training computer vision models and ~7 years maintaining Albumentations.

Despite augmentation being used everywhere, most discussions are still very surface-level (“flip, rotate, color jitter”).

In this article I tried to go deeper and explain:

• The *two regimes of augmentation*:
– in-distribution augmentation (simulate real variation)
– out-of-distribution augmentation (regularization)

• Why *unrealistic augmentations can actually improve generalization*

• How augmentation relates to the *manifold hypothesis*

• When and why *Test-Time Augmentation (TTA)* helps

• Common *failure modes* (label corruption, over-augmentation)

• How to design a *baseline augmentation policy that actually works*

The guide is long but very practical — it includes concrete pipelines, examples, and debugging strategies.

Would love feedback from people working on real CV systems.

Link:
https://medium.com/data-science-collective/what-is-image-aug...
by lioeters | 2026-03-05 09:22:04+00:00
> Phart is exploring New Media to express itself through Math, Science, and Visual Arts!

I don't understand what is going on in this project, and honestly I think you could edit the text to remove about 80% of words and communicate the same information in a more organized way - but the colorful diagrams are pretty and I was quite entertained skimming through it.

It's nice to see someone enjoying creative computing, and if it takes the audience some effort to digest the mad genius (or just mad) rambling stream of consciousness, well, it's your hypermedia software novel, you can make it how you want and that's the fun and freedom of artistic expression!
by Ajakks | 2026-03-05 09:22:30+00:00
This is actually quite good and you ought to be proud of it!

You have an almost trigger attention grab - from a marketing/advertising pov, I'll repeat, this is quite good. I wish the content was different but only bc I think it will really strongly resonate with some people - which of course is itself a metric of success.

I really like the experience and the incredible potential for artistic expression with this framework.

I think you might be onto something significant - it could almost be like its own form. (I'm not on much of the internet - so just ignore me if this a style I ought to exactly know)

Regardless, well done!
by matwood | 2026-03-05 09:22:51+00:00
There's definitely a procrastination trap that someone has to be aware of, but I wouldn't say all the self-help/management is a sham. Much like people who get stuck researching, there comes a point where you simply have to act. There's also value in learning how to quickly pull items out of texts that you can use right now and discarding the rest.

I liken it to jiujitsu in a way. When I first started and knew nothing, I needed a lot of instruction and of course then practice. After years of that, I can now take a simple tweak to something I've been doing for years and suddenly it's much more effective. Finding those tweaks is the challenge, while also avoiding chasing silver bullets or bouncing to new thing after new thing and never getting good at something.
by ifh-hn | 2026-03-05 09:23:24+00:00
> So that will be my advice: the shell is fine for one-liners. Anything else, just use your favorite general purpose programming language...

Hhmmm. Seems to me that is the wrong conclusion. Seems the conclusion should be to know your tools and assumptions will bite you.

Sure bash has a lot of gottyas but it isn't "just" for one-liners. You need to be aware that it is what it is though.
by heggenhougen | 2026-03-05 09:23:27+00:00
Almost unbelievable:

=== FINITE ELEMENT SOLVER FOR MOBILE PHONE DESIGN @ 80% SPARSITY ===
Stiffness matrix: 8192 × 8192
Sparsity : 80%
Solver calls : 100000
Mode : Multi-CPU (optimized for Intel Intel(R) Xeon(R) CPU @ 2.20GHz)

[2026-03-04 23:14:08] Seed: 123456 | Zeros: 80%
A_hash: 383bcac388febd41579ec65cf6ce1a2e37d04014f3bb4bfc156317bd8426b18b | V_hash: af6b04009fc339f419ef6991fc35ca1b5c6c54495cf6b1aeb236c249f444c51b

ROLV build time: 6.075545 s

Per-iteration times:
ROLV : 0.000476 s
Dense PyTorch (MKL): 0.023720 s → Speedup vs Dense: 49.85× Energy saved: 98.0%
CSR Sparse (MKL) : 0.053517 s → Speedup vs Best Sparse: 112.48× Energy saved: 99.1%

JSON OUTPUT:
{
"benchmark": "Finite Element Solver - Mobile Phone Design",
"sparsity_pct": 80,
"rolv_per_iter_s": 0.000476,
"dense_per_iter_s": 0.02372,
"csr_sparse_per_iter_s": 0.053517,
"speedup_vs_dense_x": 49.85,
"speedup_vs_best_sparse_x": 112.48,
"energy_savings_vs_dense_pct": 98.0,
"energy_savings_vs_sparse_pct": 99.1
}
by armcat | 2026-03-05 09:23:28+00:00
I really like this, and have actually tried (unsuccessfully) to get PersonaPlex to run on my blackwell device - I will try this on Mac now as well.

There are a few caveats here, for those of you venturing in this, since I've spent considerable time looking at these voice agents. First is that a VAD->ASR->LLM->TTS pipeline can still feel real-time with sub-second RTT. For example, see my project https://github.com/acatovic/ova and also a few others here on HN (e.g. https://www.ntik.me/posts/voice-agent and https://github.com/Frikallo/parakeet.cpp).

Another aspect, after talking to peeps on PersonaPlex, is that this full duplex architecture is still a bit off in terms of giving you good accuracy/performance, and it's quite diffiult to train. On the other hand ASR->LLM->TTS gives you a composable pipeline where you can swap parts out and have a mixture of tiny and large LLMs, as well as local and API based endpoints.
by dalke | 2026-03-05 09:23:36+00:00
Over the last few days I have learned that using code generation tools are increasingly used to create a "clean room" version of a product, using a definition which is far from its standard use.

See https://tuananh.net/2026/03/05/relicensing-with-ai-assisted-... with discussion at https://news.ycombinator.com/item?id=47257803

I believe your use of "clean room" is another example of misusing the term.

Could you clarify how it was developed? Who had access to the original source code? Were code generation tools used, and if so, how? Was the PyMol source part of the training set for those tools? How did you ensure no copyright violations?

Warren was a friend of mine, and a passionate believer in open source software. He wanted people to be able to modify PyMol for their own purposes, and asked only for a license acknowledgment. Schrodinger, to their great credit, continues to honor Warren by maintaining the Open-Source PyMOL product.

If this project was not developed under true clean room practices, I ask that you continue to honor his work by including the PyMol license in your Rust rewrite.

If it was true clean room development, why does ./crates/pymol-algos/src/align/ce.rs say "This is a faithful port of PyMOL's `ccealignmodule.cpp`.", with comments like "Equivalent to PyMOL's `calcS`" and references to the original code in comments, like: "PyMOL: for (row = 0; row < wSize - 2; row++)"?
by user34283 | 2026-03-05 09:24:16+00:00
I find the wording "protect from unwanted use" interesting.

It is my understanding that what a GPL license requires is releasing the source code of modifications.

So if we assume that a rewrite using AI retains the GPL license, it only means the rewrite needs to be open source under the GPL too.

It doesn't prevent any unwanted use, or at least that is my understanding. I guess unwanted use in this case could mean not releasing the modifications.
by spacedcowboy | 2026-03-05 09:24:49+00:00
Yeah, we did it too, in the early 80’s. I’m not an “artsy” type, very focused on maths and sciences (6 A levels), but I can quote two poems verbatim from all those years ago. The first is “Jabberwocky” because I had to memorise it for a school performance, it’s still something of a party-trick, a real tone-poem, the first and last verses are identical, but spoken so differently, the alliteration, tempo-changes, etc. etc.

The second is “Dulce et decorum est”, which we studied and analysed for “O” level. This poem, very much, is not a party-trick.
by vladms | 2026-03-05 09:25:26+00:00
> Regarding art, what do you feel about museums? Why would you go see an original instead of simply looking at a jpg.

I go to a museum to see a curated collection with explanations in a place that prevents distractions (I can't open a new tab) and going with people that might be interested to talk about what they see and feel. It's as well a social and personal experience on top information gathering.

> there is clearly a group of people who appreciate seeing the original,

There are many people interested in many things, do you want to say that "because some people think it is important, it must be important"? There were many people with really weird and despicable ideas along history and while I am neutral to this one, they definitely don't convince me just by their numbers.

> simply looking at a jpg.

Technically a jpg would not work because is lossy compression. But a png at the correct resolution might do the trick for some things (paintings that you see from far), but not for others. Museum have multiple objects that would be hard to put in an image (statues, clothes, bones, tables, etc.). You definitely can't put https://en.wikipedia.org/wiki/Comedian_(artwork) in a jpg - but the discussion surrounding it touches topics discussed here.
by zozbot234 | 2026-03-05 09:26:46+00:00
This seems right to me. If you ask a LLM to derive a spec that has no expressive element of the original code (a clean-room human team can carefully verify this), and then ask another instance of the LLM (with fresh context) to write out code from the spec, how is that different from a "clean room" rewrite? The agent that writes the new code only ever sees the spec, and by assumption (the assumption that's made in all clean room rewrites) the spec is purely factual with all copyrightable expression having been distilled out. But the "deriving the spec (and verifying that it's as clean as possible)" is crucial and cannot be skipped!
by tialaramex | 2026-03-05 09:26:59+00:00
Yes, you've basically got it, the customers for fuck-trump.example just write your chosen value in OuterSNI and fuck-trump.example in the InnerSNI, which is encrypted and you do the (very cheap on modern hardware) decryption and route fuck-trump.example. In practice it might work (but isn't guaranteed to) to write something else in OuterSNI like whitehouse.gov rather than the value chosen by the operator.

It's apparent from other responses that most people didn't understand that we're not talking about a weird new feature which might work if people implement it. This is the published document explaining how it works, but the reality is that it's widely deployed today. This is already how it's working today, if you tell people first they raise all sorts of objections and insist it's unworkable, so, we didn't tell them first we just did it. Here's a relevant quote:

"Dan, I'm not a Republic serial villain. Do you seriously think I'd explain my master-stroke if there remained the slightest chance of you affecting its outcome? I did it thirty-five minutes ago" -- Watchmen, by Alan Moore.
by msdz | 2026-03-05 09:27:09+00:00
They’d probably get the farthest, but they won’t pursue that because they don’t want to end up leaking the original data from training.
It is possible in regular language/text subsets of models to reconstruct massive consecutive parts of the training data [1], so it ought to be possible for their internal code, too.

[1] https://arxiv.org/abs/2601.02671
by actionfromafar | 2026-03-05 09:27:24+00:00
Yeah I think, the Compaq / IBM precedent can only superficially apply. It would be like having two teams only meet in a room full of documentation - but both teams crammed the source code the day before. (That, the source code you are "reverse engineering" is in the training data.) It doesn't make sense.

Also, it's weird that it's okay apparently to use pirated materials to teach an LLM, but maybe not to disseminate what the LLM then tells you.
by fc417fc802 | 2026-03-05 09:27:37+00:00
The linked article seems to suggest that rather than "appearance" what's actually meant is "anything non-verbal"? In which case the related english language thing to look for is writings on the importance of the non-verbal aspects of communication, of which there are a lot.

Also, why does the linked article (容姿) contain a fully nude image? I don't understand the usefulness or significance (and wouldn't have expected it to be permitted regardless). https://ja.wikipedia.org/wiki/%E5%AE%B9%E5%A7%BF
Show HN: I Built Glassdoor but for Food Delivery Drivers in Dubai
by shraddha92 | 2026-03-05 09:28:52+00:00
Hey everyone, just a bit of context into what I built.

The essential question was - What do food tech companies despite being major competitors, have in common?

Their food delivery riders are all used as guinea pigs for online clout by influencers

You know what I mean, those videos where money or food is handed out as gifts to show what a generous person the giver is, or how they’re breaking the norm by showing kindness etc “…….”

Keeping aside my personal disdain for filming a good act for attention, the fact that they have no consideration for the drivers privacy even when editing the video is wild. You can make all those edit cuts but can’t blur the drivers face?

I built igotfilmed.com exactly for that.

I initially built it with 5 language versions for the majority i see in dubai - Hindi, Afrikaans, Nepali, Malayalam and Tagalog- planning to add more options later

Drivers can now report/submit filming incidents where they noticed they’ve been filmed quietly, their videos have been uploaded on social media without their explicit knowledge or permission or even times when they were asked for permission.

The idea is to create a centralized location where all food tech companies delivery drivers can be made aware of which areas are the most common for these issues and which category is the most common. And for the ones who’s videos have been submitted without their permission- I have a plan for that

The company where they work at etc is kept entirely private as it’s not shown on the site ever. Interestingly enough tho, 2 companies popped up all the time when I was collecting sample data (which is what you see on the map now)

The map legend colors do not denote the company. They’re just colors chosen randomly.

It’s free for them to use.
by jhbadger | 2026-03-05 09:29:56+00:00
It all depends on whether the paper fits the journal. Minor journals serve a useful service as a repository for minor results. And minor results are still worth publishing because they might provide a detail or technique later needed for a major result. The thing to be wary of is when you see a stunning result that should really be in _Nature_ or _Science_ in some minor journal. Why isn't it? Was it submitted there first and rejected? It would be nice if the history of a manuscript (and its peer review) stayed with a manuscript so you could see if the authors really corrected problems brought up by peer review or were just spamming journals with a flawed manuscript until they found one that published it.
by kavith | 2026-03-05 09:31:09+00:00
Not sure if this will help but I've set up Handy [1] with Parakeet V2 for STT and gpt-oss-120b on Cerebras [2] for post-processing and I'm happy with the performance of this setup!

[1] https://handy.computer/
[2] https://www.cerebras.ai/
by esskay | 2026-03-05 09:31:22+00:00
Yeah theres very little difference at this point between the A and M lines, think of the M as just being the more powerful line, but that doesnt make the A line weak, not by any stretch. Both are completely binary compatible at this point.

The A18 Pro single core performance is on-par with the M4 (a smidge lower but barely anything in it), and outperforms the M3.
by myrmidon | 2026-03-05 09:31:23+00:00
Because on-site powerplants owned by datacenter operators are not "just another supplier".

The threat is: This "datacenter power" disincentives buildout of "free" powerplants (by eating up significant demand at very low margins thanks to basically vertical integration); this slows down buildout of "normal" infrastructure (possibly both grid connectivity and power), and the electrical energy market becomes worse for consumers than it is now.

I personally think all of this is very speculative for now, but allowing industry to rely on the grid (which they still would!) while almost exclusively "buying" their own power is a risky proposition from a consumer perspective.
by spoiler | 2026-03-05 09:31:56+00:00
So effective, LGPL means you freely give all copyright for your work to the license holder? Even if the license holder has moved on from the project?

What if I decide to make a JS or Rust implementation of this project and use it as inspiration? Does that mean I'm no longer doing a "clean room" implementation and my project is contaminated by LGPL too?
by tanya-donska | 2026-03-05 09:32:24+00:00
Every UI/UX design agency in New York claims SaaS specialization. Most are lying.

Check their portfolio. If it’s only landing pages and marketing sites, they don’t design products. If it’s consumer apps, they don’t understand B2B. If there’s no admin panels, user management, or settings screens, they’ve never designed multi-tenant platforms.

Real specialization shows depth: onboarding systems, role-based dashboards, permissions UI, empty states, data tables, admin tools. Not pretty hero shots.