MurphyA/hacker-news huggingface dataset:
by NateEag | 2026-03-10 13:14:13+00:00
As others have pointed out in this discussion, there's a big difference between some humans producing drawings in a given style and a machine producing millions of illustrations per day in that style.

I have rarely been as disheartened as I am by the transformation of Studio Ghibli's beautiful art style, painstakingly developed over decades, into a heap of slop-trash that actively erases the human connections so artfully depicted in Hayao Miyazaki's work.

All that sorrow and it's not even my style.

So, no - a human who's willing to draw an illustration in a particular style, perhaps one they live and admire, is not necessarily a hypocrite for seeing genAI's ability to produce billions of images in that style.
by ApolloFortyNine | 2026-03-10 13:14:21+00:00
>Or you can complain to the void that open source maintainers don't want to deal with low effort vibe coded bullshit PRs.

If you look back and think about what your saying for a minute, it's that low effort PRs are bad.

Using an LLM to assist in development does not instantly make the whole work 'low effort'.

It's also unenforceable and will create AI witch hunts. Someone used an em-dash in a 500 line PR? Oh the horror that's a reject and ban from the project.

2000 line PR where the user launched multiple agents going over the PR for 'AI patterns'? Perfectly acceptable, no AI here.
by hijnksforall956 | 2026-03-10 13:15:12+00:00
How is that different than before LLMs? You have no idea how the person came up with it, or whether they really understood.

We are inventing problems here. Fact is, an LLM writes better code than 95% of developers out there today. Yes, yes this is Lake Wobegone, everyone here is in the 1%. But for the world at large, I bet code quality goes up.
by aleph_minus_one | 2026-03-10 13:15:52+00:00
Translation software does not solve the problem that the tone that you have to use in English is often very different from the tone in your native language. What I would write in German would sometimes not be socially acceptable for English speakers.

If the native language is very different from English, this problem gets much worse.

This is a problem that LLM claim to partially mitigate (and is one reason why non-native speakers could be tempted to use them), but hardly any classical translation tool can.
by Kamil_KKA | 2026-03-10 13:16:11+00:00
I kept losing track of AI prompts I liked or wanted to reuse, so I built IdeaPrompts — a central place to store, organize, and share prompts.
You can build your collection, collaborate with others, and improve your AI interactions without hunting through old notes or chat histories.
It’s simple, personal, and keeps prompts useful instead of forgotten.
by dirk94018 | 2026-03-10 13:16:13+00:00
Author here. AI as pipe, not platform. toast is sed with a brain — reads stdin, writes stdout, honors the Unix contract. We're rewriting the command line around that idea, one tool at a time.

Generation is cheap now. Review is not. The skill that can't be automated is the stopping condition. Knowing what should not exist.

The market wants agents. Agents don't work. A pipe does. If this resonates and you build this way, I'd like to talk.
by squidbeak | 2026-03-10 13:16:46+00:00
> What is known is that the majority believe that if artists were to be copied, they should at least be compensated.

I get the emotional side of this argument - artists going hungry while someone else cashes in on their ideas. But compensation is a dangerous premise, because derivative art is an established type of artistic freedom. Artists routinely mimic styles, or work within the bounds of styles established by masters, but they've never been expected to compensate those styles' pioneers. Imagine it as a precedent:

"Your stuff borrows from Warhol? Guess what buddy, you owe the Warhol estate x% of your sale."

Perhaps you're arguing things change when commercial interests are involved? But again, this has never been the case for advertising companies (with their hired artistic guns) or any kind of graphic design leaning on established artistic styles for effect and making a killing in the process.

In the case of AI, even if it has a commercial master, it seems much closer to the borrowing of an ordinary artist. It's a trained entity, with deep understanding of styles, capable of making new works. On top of that, it works under the instruction of a user with their own ideas, whose guidance is crucial in deciding the work's final state. The user is the artist here - like one of the visionaries who delegate the nitty gritty of production to helpers. In this case the helper is leased from the AI company, which is more like an agency supplying those helpers.

All in all it's hard to see how any compensation model wouldn't end up constricting the artistic freedom most of these artists depend on.
by az226 | 2026-03-10 13:19:25+00:00
Yann LeCun seeks $5B+ valuation for world model startup AMI (Amilabs).

He has hired LeBrun to the helm as CEO.

AMI has also hired LeFunde as CFO and LeTune as head of post-training.

They’re also considering hiring LeMune as Head of Growth and LePrune to lead inference efficiency.

https://techcrunch.com/2025/12/19/yann-lecun-confirms-his-ne...
by PaulHoule | 2026-03-10 13:19:41+00:00
I did a lot of study of Lotus Notes circa 2015 when I was thinking about a no-/low-code future. It is still ahead of its time when it comes to having a document database that supports merging but it's unthinkable that you'd build a system like that around email today as today an email system is 99% spam filter and 1% other stuff.
by fileshotdev | 2026-03-10 13:19:41+00:00
Hi HN,

I’ve been building FileShot (https://fileshot.io
), a file-sharing platform focused on speed, simplicity, and giving creators more control over how they distribute files.

Originally it started as a simple way to upload a file and instantly get a shareable link. Over the last few months I’ve rebuilt a lot of the platform and added some bigger features.

Some of the recent updates:

• Custom user subdomains – Users can now create pages like
username.fileshot.io to host and showcase their uploads.
Some people are already using it as a simple portfolio or file hub.

• Paid file access – Uploaders can optionally charge for downloads.
This pairs well with the subdomain pages for selling digital files, assets, or documents.

• Browser extension – You can now upload files directly from the browser and instantly generate share links.

• UI overhaul – The entire interface was redesigned to make uploading and sharing faster and simpler.

• High limits and fast transfers – One of the main goals with FileShot is keeping limits high and uploads fast so sharing large files is painless.

The idea behind the project is to combine a few things that usually live on different platforms:

simple anonymous file sharing

creator pages / file hubs

optional monetization for downloads

All in one place.

I’m still actively developing it and would love feedback from the HN community — especially around features, usability, and things that could make it more useful.

Thanks for checking it out.

Couple small HN tricks that matter a lot:

1. Put the link in the body, not the title.
HN prefers that.

2. Be ready to reply to comments quickly.
Posts that get early engagement climb the ranking.

3. Launch early in the morning (Pacific time).
That’s when most HN traffic hits.
by philipstorry | 2026-03-10 13:19:43+00:00
Yo. Firstly, thanks for the trip down memory lane - well written, engaging, fun. My mind is still stuck in those days even after finishing the article, as you can tell from my anachronistic greeting.

Secondly, as someone who spent 15 years working with Lotus Notes, I can assure you that you can run it standalone. Obviously it makes no real sense for a Groupware product, but it can be done. To the Notes client opening a database locally or on a mail server is largely the same.

The main issue is that people used Notes to communicate and collaborate. So you could just go creating new Address Books, Discussion databases, Document Libraries and so on, but what exactly are you proving with that? It's be like just firing up the Microsoft Mail client and only looking at the address book...

Whilst I'm aware that there's plenty in Notes that people didn't like, I do think that there are some gems hidden in there which it would have been nice to have kept. The Notes dialect of Rich Text had a couple of niceties (programmable buttons, collapsible/expandable Sections). The database engine itself was unparalleled at the time, and in some ways it still hasn't been bettered.

But the issue remains that you'd need to set up a Notes/Domino Server (depending on your version - 4.5 onwards it's called Domino), and a small network. And that's a ball-ache that nobody wants. It can speak IPX/SPX and NetBIOS, so it doesn't have to be as complicated as TCP/IP, but it's still a lot of prep work before you even get to start looking at the usage. :-(

That having been said, I was a Principal Certified Lotus Professional on the Sysadmin track for about three versions of Notes, from 4.6 to 6, and can definitely help if you ever did want to do that. Feel free to email me at phil [at] philipstorry.net if you're ever so lacking in subjects that you feel forced into this last resort.
by sergF | 2026-03-10 13:20:11+00:00
Yeah, that makes sense too. I also try to keep things synchronous as long as possible.

In practice async usually shows up once there are external APIs, retries, scheduling, or anything that shouldn't block the request, and that's where I end up building some kind of job system again.

I'm trying to figure out if that point happens often enough to justify moving this outside the app entirely.
by flyinghamster | 2026-03-10 13:20:16+00:00
As with so many old things, it's still alive, but it's down to the die-hards. I still miss it, though - I participated in Net 232 (Champaign-Urbana) for a while, then Net 115 in Chicago. We had some great gatherings back in those days, but in the Chicago area, the scene blew away pretty quickly when the internet opened up.
by dnhkng | 2026-03-10 13:20:23+00:00
Author here. I found that duplicating a specific block of 7 middle layers in Qwen2-72B, without modifying any weights, improved performance across all Open LLM Leaderboard benchmarks and took #1. As of 2026, the top 4 models on that leaderboard are still descendants.

The weird finding: single-layer duplication does nothing. Too few layers, nothing. Too many, it gets worse. Only circuit-sized blocks of ~7 layers work. This suggests pretraining carves out discrete functional circuits in the layer stack that only work when preserved whole.

The whole thing was developed on 2x RTX 4090s in my basement. I'm now running current models (GLM-4.7, Qwen3.5, MiniMax M2.5) on a dual GH200 rig (see my other post). Code and new models coming soon.

Happy to answer questions.
Show HN: Parascene – a platform for AI, algorithmic, and traditional art
by heddycrow | 2026-03-10 13:20:39+00:00
Hi HN — I am building Parascene as a place to create and share different kinds of art.

It supports AI-generated images, algorithmic/generative art, and traditional artwork. The goal is to put them in the same space so people can explore techniques, prompts, and creative ideas across mediums.

Current features include image generation tools, a public gallery, prompt sharing, and profiles where artists can post work.

Another goal is to encourage, enable, and reward local AI usage by sharing generation capabilities among the community.

I’m interested in feedback on the concept and the product. Does combining these mediums in one platform make sense?

https://www.parascene.com/help
Show HN: Gate – deterministic write-path checkpoint for AI agents
by cgallic | 2026-03-10 13:21:27+00:00
The write-path control plane for AI agents.

AI agents can read systems freely. The problem is writes — CRM imports, email sends, database updates, refunds. Once the agent does it, you can't unsee it.

Gate sits between the agent and production. Agents submit an intent, Gate evaluates a YAML policy, and only then issues a signed execution order. No LLM at evaluation time — same input always produces the same output.

The flow:
POST /v1/intents → policy evaluated → approved/blocked/pending
POST /v1/intents/:id/execute → gex_ token (15 min TTL)
Worker uses token → reports outcome
Full audit trail: proposed → policy_checked → approved → execution_requested → execution_succeeded
by stevepike | 2026-03-10 13:21:37+00:00
It looks like this is a community continuation of the axlsx gem which was maintained back in the day by Randy Morgan (randym) over at https://github.com/randym/axlsx. One of my earliest open source contributions was adding support so that you could output spreadsheets with "conditional" formatting (color something red if it is below some value, for instance). I remember Randy being extremely supportive of new contributors and it made me want to be a part of the ruby community.

Thanks for continuing the work!
by ACCount37 | 2026-03-10 13:21:43+00:00
There is no single answer. It depends on the exact components, their sensitivities, frequencies and energies used, and how much failure risk are you willing to take.

Rule of thumb: one simple xtal per board in small manufacturing runs (4 digits or less) means you're fine.

The larger your manufacturing runs are, and the more sensitive components you have on your boards, the more careful you want to be. Components can easily make the difference between 0.2% failure rate and 2% failure rate, and that 2% failure rate bites when you push units by hundreds of thousands.

Of course, there's always a chance of you getting a perfect match of the exact intensity and frequency used on a given manufacturing line, which you didn't know, with what happens to kill your specific components at a disproportionate rate, which you also didn't know. But it's a pretty low chance. Feeling lucky?

Because yes, it's not actually worth the engineering/support effort for you, your manufacturer and your part vendor to actually put the thinking cap on and characterize all of that shit for a typical low volume run. So luck it is.
by ericd | 2026-03-10 13:21:43+00:00
The Google paper (https://arxiv.org/pdf/2511.19468) didn’t seem too concerned with radiator mass/size when I skimmed it, but maybe I just missed it. My understanding is that if you run the chips relatively hot (and maybe boost with heat pumps? But then you’re not quite as solid state, and maintenance is tough up there), the radiation ability increases enough such that you can make the radiators slightly smaller than the solar panels, and they’d sit on the dark side of the panels. Many people like to point to the ISS system and scale that up, but there’s a big difference between a system assembled in space and meant to keep humans at human temps vs mass manufactured on the ground and keeping things around 100C.
Show HN: VR.dev – Open-source verifiers for what AI agents did
by SkiFreeWin3 | 2026-03-10 13:21:51+00:00
Hey HN,

Quick origin story: vr.dev started as a virtual reality project. The domain fit perfectly. The developer adoption did not. Rather than let a good domain go to waste, I pivoted to the other kind of VR: verification and rewards for AI agents.

The problem I kept running into: agents report success but system state tells a different story. The database row is still active. The IMAP sent folder is empty. The tests pass because the agent modified the tests. Real benchmarks put agent success at 12-30%, and even among reported successes a large fraction are procedurally wrong in ways that are hard to catch without actually checking state.

So I built a library of verifiers that check real system state rather than trusting agent self-reports. There are 38 of them across 19 domains right now, organized into three tiers: HARD (deterministic probes against databases, files, APIs, git), SOFT (LLM rubric scoring for things like tone or coherence that don't have a deterministic test), and AGENTIC (verifiers that actively probe the environment via headless browser, IMAP, or shell).

The design decision I'd most like feedback on is the composition model. SOFT scores are gated behind HARD checks, so if the deterministic check fails, the composed score is 0.0 regardless of what the LLM judge says. The idea is to make reward hacking structurally harder rather than just hoping the judge catches it.

MIT licensed, runs locally via pip install vrdev, no dependency on the hosted API which matters if you're using it in a training loop. Full verifier list at https://vr.dev/registry.

Curious whether the HARD/SOFT/AGENTIC taxonomy makes sense to people, whether fail_closed is the right default, and whether anyone has built something similar and run into problems I haven't hit yet.

https://vr.dev
https://github.com/vrDotDev/vr-dev
https://pypi.org/project/vrdev/
by dingleberry | 2026-03-10 13:21:52+00:00
probably not worse ergonomic because i type '(' with left pinky and right ring finger and ')' with left pinky and right pinky whereas {} [] etc, i have to use the very same overworked right pinky to distinguish two keys next to each other.

i always have problems with keys that have no obvious dedicated finger position like the middle vertical columns especially 6 and b and of course keys reachable on the right pinky, especially \ and =
by fxwin | 2026-03-10 13:22:14+00:00
extensive tracking of self-related metrics to improve ones health is the equivalent to reading tons of self-help books to improve ones life/social skills/...

We already mostly know what makes people happy/healthy: personal connections, physical activity, healthy diet and some sort of purpose/goal in life that goes beyond day-to-day activities.
The problem is that these things generally require (hard) work and can be unpleasant sometimes, so humans do what humans do and spend unreasonable amounts of time doing the more pleasant things such as reading and gathering info rather than applying these and what they already know.
(That's not to say that a project like this can't be fun or lead to insights, especially across longer time spans, but i feel like all of the questions in the first paragraph have fairly obvious answers if you know yourself at all, that don't require extensive tracking of stats to get)
by al00sh | 2026-03-10 13:22:35+00:00
So I've been following the Iran situation pretty closely and realized I was spending half my time just trying to figure out what actually happened where. The closest thing out there is Liveuamap, but it's turned into more of a general news aggregator — it dumps everything onto the map (protests, political statements, weather, car accidents) with intrusive ads layered on top, and the sourcing is mostly just reposted tweets with no real verification or analysis. There are a couple other websites like that with similar issues. I wanted something that's specifically focused on combat events, verified before it goes live, and has actual video of what happened.
So I built Defogwar (https://www.defogwar.com). It's an interactive Mapbox GL globe where military events — airstrikes, drone strikes, artillery, ground assaults, territorial changes — get plotted with color-coded factions. You can scrub through time with a slider to watch how things unfold day by day, and clicking on a marker pulls up details with embedded video when we have footage. No news ticker spam, no political commentary pins, just combat events with sources.
The interesting engineering problem was the data pipeline. Manually curating conflict events doesn't scale when you're one person, so I built an ingestion layer that pulls RSS feeds and Telegram channels, pipes everything through Gemini 2.0 Flash for structured extraction (coordinates, event type, factions, severity), and dumps it into a review queue. Everything goes through human review (me) before it hits the map. The hardest thing was removing propaganda from the AI curation. Obviously it'll still be somewhat objective but I had to often remove manually some phrases like "The terrorist state of Iran" or "Tel-Aviv was completely battered" because honestly the best combat footage sometimes comes from propaganda like sources. I'm working on the curation pipeline to better filter that out in the future though. Getting good coordinates from posts/news articles was also a hassle.
Stack is Next.js 14, PostgreSQL with PostGIS for spatial queries, Cloudflare R2 for video storage (zero egress fees was the selling point there), and Railway for hosting.
Right now the coverage is focused on the Iran conflict — I had other conflicts mapped but pulled them back to get the data quality right first. Those will come back once the pipeline is solid. In the future I'm also considering putting historical conflicts on there from throughout history. Would love feedback on the map UX and if anyone has suggestions for good open OSINT data sources I'm not using.
by robertandrewp | 2026-03-10 13:23:11+00:00
The .xlsx experience is even messier in a business context. I work daily across Windows and Mac, and my two worst offenders are Excel and QuickBooks.

Excel on Mac has been closing the gap, but VBA macros from Windows colleagues still break regularly — sometimes silently, sometimes loudly. A workbook that runs perfectly on Windows will open on Mac and just do nothing, with no error. I've ended up keeping a Windows machine running purely because of macro-dependent spreadsheets.

QuickBooks is the more frustrating one. Intuit has historically treated the Mac version as a feature-lagged port — payroll features, industry-specific reports, and bank reconciliation behaviour all differ between platforms. The company essentially wrote the same product twice and kept them deliberately out of sync. Muscle memory from one doesn't transfer to the other.

The only partial escape I've found is pushing financial calculations out to platform-neutral layers entirely — whether that's a shared Google Sheet, a web-based tool, or an API. The moment the logic lives in a .xlsm file, you're platform-dependent again.
by flexagoon | 2026-03-10 13:23:40+00:00
> The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

Quantified Self, at least in the intended form, is focused on testing specific theories, not on collecting large amounts of data and trying to find something interesting in them.

See, for example:

https://gwern.net/zeo/zeo#what-qs-is-not-just-data-gathering