MurphyA/hacker-news huggingface dataset:
by gilleain | 2025-12-09 10:56:48+00:00
Also, if you bought an album, that meant getting some tracks you liked, and some you did not. Oddly enough I bought Suzanne Vega's self-titled album with 'Cracked' on it (off a guy in a stall off Brick Lane, only a fiver), and some of them are fantastic some slightly less so. Some albums I own I turn off one or two of the tracks as they are rubbish, but that was slightly more difficult if you had to fast-forward past them on a tape.

That said I listen to a lot of music on youtube, and it's a rare case where the dreaded 'algorithm' actually works to recommend things I had not heard before. I'm pretty sure that's where I learned of Unkle (UNKLE?) - who I _should_ have heard back in the day, but somehow never did.

(Incidentally, I found 'Daughter' recently, a UK band that is similar in tone to Suzanne Vega. Possibly also Heather Nova, although a bit more dreamy.)
by tsimionescu | 2025-12-09 10:57:30+00:00
At some point, Bob will want to spend the coins on something that he needs. At that point, you'll be able to trace the whole chain of transactions and know that Bob got the coins from Alice. Sure, you won't know that Alice transferred the private keys to Bob, but you'll still see a chain of transactions that starts with money in a wallet associated with Alice and ends in a wallet associated with Bob. The private key transfer doesn't achieve anything at all: Bob could just as easily have opened a new wallet and asked Alice to transfer money there instead of his known wallet, nothing in the analysis would have changed.
by ghusbands | 2025-12-09 10:58:11+00:00
A simpler way: You can avoid sampling neighbours by clamping the ray-march step so it never moves further than the current cell's boundary (plus a tiny epsilon). That way, you only cross into adjacent cells at the edge and avoid the 8 to maybe 26 extra SDF samples. (This only works if the geometry is entirely contained within each cell.)
by DaSHacka | 2025-12-09 10:58:20+00:00
Believe me, I wish that were true, but Trump's approval rating is in the low 40's right now.

He's also obviously not making it to the next election, and JD Vance doesn't have nearly the same pull or unifying ability.

I think it's much more likely the right wing splits into subfactions over the matter of Israel than having another red sweep like we saw this past election.

It looks like dems are slowly pulling their heads out of their assess too, so there's a decent chance they'll be more unified come election night.
by the_other | 2025-12-09 10:58:29+00:00
> No CSS is better than bad CSS

That's only true if the markup and JS are also good. If, for sake of argument, the HTML had been badly authored such that the links in that menu were DIVs with click event handlers, rather than real links, then removing CSS would likely make the experience worse rather than better.

I guess that a key point underpinning your comment is that progressive enhancement is still better than assuming all potential users are on the bleeding edge, despite the evergreen update pattern for the most popular 3 or 4 browsers.
by j45 | 2025-12-09 10:59:48+00:00
This looks great.

For the demo on the screen, it would be great to reveal each subgraph as a step before it all flows together.

Is there any thought / plan / feasibility for adding a "reveal" type verb that could be placed between each subgraph to wait for a keypress to reveal the next subgraph? In the meantime, one could create 3 diagrams I guess of with one more subgraph added.
by NotOscarWilde | 2025-12-09 11:00:33+00:00
> Is the lock structuring here really deadlock safe? The model will tell you with complete confidence its code is perfect

Fully agree, in fact, this has literally happened to me a week ago -- ChatGPT was confidently incorrect about its simple lock structure for my multithreaded C++ program, and wrote paragraphs upon paragraphs about how it works, until I pressed it twice about a (real) possibility of some operations deadlocking, and then it folded.

> Every time a major announcement comes out saying so-and-so model is now a triple Ph.D programming triathlon winner, I try using it. Every time it’s the same - super fast code generation, until suddenly staggering hallucinations.

As an university assistant professor trying to keep up with AI while doing research/teaching as before, this also happens to me and I am dismayed by that. I am certain there are models out there that can solve IMO and generate research-grade papers, but the ones I can get easy access to as a customer routinely mess up stuff, including:

* Adding extra simplifications to a given combinatorial optimization problem, so that its dynamic programming approach works.

* Claiming some inequality is true but upon reflection it derived A >= B from A <= C and C <= B.

(This is all ChatGPT 5, thinking mode.)

You could fairly counterclaim that I need to get more funding (tough) or invest much more of my time and energy to get access to models closer to what Terrence Tao and other top people trying to apply AI in CS theory are currently using. But at least the models cheap enough for me to get access as a private person are not on par with what the same companies claim to achieve.
by oppi | 2025-12-09 11:01:39+00:00
Hi HN — I’m building an early-stage B2B SaaS (pre-seed, no customers yet). The product is a company-wide “agentic AI layer”: employees have identity-bound agents that coordinate work, and the system relies on an inter-agent secure communication protocol (authenticated, encrypted messages; policy-scoped data sharing; auditability).

We’re debating going open-source to build trust and adoption, but we’re worried about (a) cloning the SaaS, (b) increasing maintenance burden too early, and (c) undermining the business before PMF.

Concrete questions I’d love advice on:

- If you were in our shoes, would you open-source (1) protocol spec + test vectors, (2) client SDKs, (3) a reference server, or keep it closed until later?

- Where’s the best open/closed boundary so open-source helps adoption without giving away the whole product?

- Any hard-learned lessons on licenses for this situation (permissive vs copyleft vs dual-licensing)?

- What are the “minimum hygiene” requirements before open-sourcing (docs/CI/security policy/contribution process)?

- For security protocols specifically: what would you expect to see published (threat model, audits, test vectors, etc.) to take claims seriously?

If helpful, I can share a high-level architecture description (no proprietary customer data / no secrets). Thanks!
Show HN: I reimplemented TRM – trains on Sudoku 6×6 in minutes on an A10
by whiplash451 | 2025-12-09 11:02:39+00:00
Hi folks!

Tiny Recursive Models reach impressive results on ARC AGI. I implemented a version from scratch, with ease of experimentation in mind:

- cleaner config: hydra, uv, lightning - smaller datasets for faster iteration (Sudoku 6x6 and 9x9) - introduction, in-code video

All important implementation details have been carefully kept. The results of the paper are reproducible (Sudoku Extreme, Maze Hard).

Feedback/contributions welcome.
by slightlygrilled | 2025-12-09 11:02:41+00:00
On web there is SpectorJS https://spector.babylonjs.com/

Which offers the basics, but at least works across devices, you can also trigger the traces from code and save the output, then load in the extension. Very useful for debugging mobile.

You can just about run chrome through Nvidias Nsight (of course you're not debugging webgl, but the what ever its translated to on the platform), although I recently tired again and it seems to fail...

these where the command line args i got nsight to pass chrome to make it work

" --disable-gpu-sandbox --disable-gpu-watchdog --enable-dawn-features=emit_hlsl_debug_symbols,disable_symbol_renaming --no-sandbox --disable-direct-composition --use-angle=vulkan <URL> "

but yeah really really wish the tooling was better, especially on performance tracing, currently it's just disable and enable things and guess...
by ulinycoin | 2025-12-09 11:02:46+00:00
Hi HN! I'm the creator of LocalPDF (https://localpdf.online) — a privacy-first PDF toolkit that works entirely in your browser.

I wanted to share something fascinating: ChatGPT has become my biggest traffic source, accounting for ~50% of visitors, compared to ~45% from Google. This happened organically — I didn't optimize specifically for AI assistants.

Key Stats: - ChatGPT: ~50% of traffic - Google Search: ~45% - Direct/Other: ~5% - Conversion rate from ChatGPT: 2x higher than Google - ChatGPT users stay 40% longer on average

What I think is happening:

GEO (Generative Engine Optimization) vs SEO Traditional SEO focuses on keywords, backlinks, and content clusters. But AI assistants work differently: - They parse semantic HTML structure - They value clear, descriptive content over keyword density - They prefer sites that solve problems directly

The ironic part? My site was built with basic semantic HTML and clear descriptions — not because I was targeting AI, but because it's good web development practice.

Technical Details: - Stack: Astro + TypeScript, client-side PDF.js - No tracking, no uploads — everything processes locally - Semantic HTML: proper headings, landmarks, meta descriptions - Clear tool descriptions with use cases

Why ChatGPT users convert better: 1. Intent clarity: They ask specific questions ("how to compress PDF without losing quality") 2. Contextual recommendations: ChatGPT explains why LocalPDF fits their needs 3. Trust transfer: AI assistant endorsement acts as social proof

Limitations: - Can't track which specific ChatGPT prompts drive traffic - No direct way to optimize for AI recommendations - ChatGPT's recommendations can change unpredictably

Questions for HN: 1. Are you seeing similar traffic patterns from AI assistants? 2. How do you measure/optimize for GEO vs traditional SEO? 3. What happens when every AI assistant has different ranking criteria?

This feels like early Google days — there's a level playing field where good products with clear value propositions can get discovered organically, without massive SEO budgets.

Happy to answer questions about the technical implementation, traffic patterns, or anything else!
by demarq | 2025-12-09 11:02:49+00:00
Worse still, EU isn’t actually a democracy. It’s an economic union. Which citizens voted for Vonderleyen? What power do EU citizens have over policies tabled in EU parliament? Who made the final choice on chat control?

Autocracy is what threatens EU democracy, not a check mark on a social media website.

So I don’t get called a Pro-Elon shill, I don’t like Elon, and think he is an ass. But he has done (maybe unwittingly) more for democracy on social media than his counterparts.

EDIT: Community notes might have been before Elon. So he only gets a half credit.
by mr_mitm | 2025-12-09 11:04:20+00:00
The photon doesn't have an inertial frame of reference precisely because it's moving at the speed of light, so it doesn't have a perspective. It's a (quantized) wave in the electromagnetic field. The closer you get to the speed of light, the closer the proper time of the journey goes to zero, but actually taking the limit does not make sense physically.
by flowerthoughts | 2025-12-09 11:04:47+00:00
Layman thoughts: The photon cannot experience the universe as it passes through it instantly. It seems to me the universal speed limit creates an observability barrier that is really fascinating. The question is what are we missing, because we're zipping through _something_ at the speed of light relative to it.

Lately, I've been wondering what evidence we have that the speed of the photon/light is really the universal speed limit, and not a very close fraction of it. I could find the argument that a photon must be massless, otherwise photons of different wavelengths would travel at different speeds. But that says nothing of the speed of a massless photon relative to maximum causality propagation speeds.
by baden1927 | 2025-12-09 11:04:57+00:00
USGS Tsunami warning circa. Dec. 2024

Seismic measurement, where weak or strong faults that are measured as seismometer, textual references to cartography, taking stock of tectonic plates.

[1]: https://news.ycombinator.com/item?id=42331326

[2]: https://web.archive.org/web/20250318161013/https://www.tsuna...
by raesene9 | 2025-12-09 11:04:57+00:00
In a lot of ways Notes was ahead of its time. You could easily have encrypted replicated databases with offline work, which was very handy for traveling users back before high bandwidth connections were widely available, and you could build quite complex apps on top of those databases.

I saw at least one large company that migrated from Notes to exchange and they got the email/calendaring bit done quite easily and were still running notes servers for line of business applications years later.
by ben_w | 2025-12-09 11:05:03+00:00
> Do you think they’ll allow AI to take all the jobs, destroying China’s domestic economy in the process?

If AI can take all the jobs (IMO at least a decade away for the robotics, and that's a minimum not a best-guess), the economy hasn't been destroyed, it's just doing whatever mega-projects the owners (presumably in this case the Chinese government) want it to do.

That can be all the social stability stuff they want. Which may be anything from "none at all" to whatever the Chinese equivalent is of the American traditional family in a big detached house with a white picket fence, everyone going to the local church every Sunday, people supporting whichever sports teams they prefer, etc.

I don't know Chinese culture at all (well, not beyond OSP and their e.g. retelling of Journey to the West), so I don't know what their equivalents to any of those things would be.
by card_zero | 2025-12-09 11:06:22+00:00
I think our language is filled with misleading semantics about the flow of time, the passing of time, past, present, future, the arrow of time, all of that. It would be hopeless to try to use different language. But time isn't doing anything. There's no time for time to do anything in.

I'll acknowledge relativity and different frames of reference, but that isn't really the point.
by thomasweiser | 2025-12-09 11:06:38+00:00
Summary as given in the post: 1. formal verification is about to become vastly cheaper; 2. AI-generated code needs formal verification so that we can skip human review and still be sure that it works; 3. the precision of formal verification counteracts the imprecise and probabilistic nature of LLMs. These three things taken together mean formal verification is likely to go mainstream in the foreseeable future. I suspect that soon the limiting factor will not be the technology, but the culture change required for people to realise that formal methods have become viable in practice.
by dsego | 2025-12-09 11:07:36+00:00
There is a TV movie In Pursuit of Honor (1995) claiming to be based on true events. My short search online states that such things were never really documented, but it's plausible that there were similar things happening.

> In Pursuit of Honor is a 1995 American made-for-cable Western film directed by Ken Olin. Don Johnson stars as a member of a United States Cavalry detachment refusing to slaughter its horses after being ordered to do so by General Douglas MacArthur. The movie follows the plight of the officers as they attempt to save the animals that the Army no longer needs as it modernizes toward a mechanized military.
by piokoch | 2025-12-09 11:08:03+00:00
"I'm always surprised how they supposedly also manage to be some of the most cunning and evil actors when it comes to hacking"

This sentiment is probably overblown. The fact that they are effectively robbing people to earn some money for their pathetic regime means only that they are on the level of nowadays internet scammers. They are good at that too.

Spending enough money (and they spend a lot - 26 million people work only for this) one can train people to do this or hire people to do this for them.
by pjmlp | 2025-12-09 11:08:07+00:00
SpectorJS is kind of abandoned nowadays, it hardly has changed and doesn't support WebGPU.

Running the whole browser rendering stack is a masochist exercise, I rather re-code the algorithm in native code, or go back into pixel debugging.

I would vouch the state of bad tooling, and how browsers blacklist users systems, is a big reason studios rather try out streaming instead of rendering on the browser.
Show HN: AlgoDrill – Interactive drills to stop forgetting LeetCode patterns
by henwfan | 2025-12-09 11:09:06+00:00
I built AlgoDrill because I kept grinding LeetCode, thinking I knew the pattern, and then completely blanking when I had to implement it from scratch a few weeks later.

AlgoDrill turns NeetCode 150 and more into pattern-based drills: you rebuild the solution line by line with active recall, get first principles editorials that explain why each step exists, and everything is tagged by patterns like sliding window, two pointers, and DP so you can hammer the ones you keep forgetting. The goal is simple: turn familiar patterns into code you can write quickly and confidently in a real interview.

https://algodrill.io

Would love feedback on whether this drill-style approach feels like a real upgrade over just solving problems once, and what’s most confusing or missing when you first land on the site.
by jll29 | 2025-12-09 11:10:09+00:00
This thread is dripping from nostalgia, in a good way.

I wonder how things are going to be in 25 or 50 years, what will today's kids look back with the same kind of devotion and nostalgia.

A lot of things are intangible/immaterial now (for non-geeks/non-hoarders, their inbox, online playlist and photos will likely be gone, they won't have any paper letters or plastic-framed holiday slide photographs or anything like that).
by devinprater | 2025-12-09 11:14:32+00:00
Yes, they can. NVDA has a Speech Viewer. VoiceOver (Mac) has the caption panel.

NVDA Speech viewer: https://download.nvaccess.org/documentation/userGuide.html#S... Caption Panel: https://support.apple.com/guide/voiceover/use-the-caption-pa...
by tuhgdetzhh | 2025-12-09 11:14:34+00:00
> One problem is that the idea of being "well-structured" has gone overboard at some point over the past 20 years

That's exactly my experience. While a well-structured monolith is a good idea in theory, and I'm sure such examples exist in practice, that has never been the case in any of my jobs. Friends working at other companies report similar experiences.
by littlestymaar | 2025-12-09 11:15:13+00:00
> People generally tend to work in exchange for money,

When they need it. Healthy retired people regularly do work for free in various charities and community work. Working people also don't usually seek to maximize their income, but balance it with plenty of factors.

> and the more money they earn thereby, the more effort they'll want to put in their work. (This broad idea is sometimes known as "efficiency wages"; it often leads to paying workers more than they could directly compete for on the market!)

This only works up to a point, you can't pay a taxi driver a million bucks in the hope of getting to destination 10 000 times faster. People do work better and harder when they feel they are fairly compensated vs when they feel they are being abused but that's it.

> Some independently rich folks may obviously choose not to work in any high-paid job at all, but given that they are, it makes sense to ask what motivates them.

And the answer is not the income proper, but everything that comes with such jobs and income, particularly “I'm making more money than Bob”. As long as Bob and him are being taxed similarly, then the actual amount makes little difference.

As I said above the marginal utility of money converges to zero the more money you have: a million dollar would change the life of the median US worker but wouldn't even be noticed by Tim Cook. (And even a billion doesn't change Jeff Bezos perception of worth an inch).

> In practice, it's often more important not to push too far away from optimality with punitive levels of taxation than to precisely match the outcome of any given theoretical mode

The concept of “punitive taxation” is in itself a political one, and again I can build a model in which the optimal income taxation is 100% above 1M and then say “we shouldn't push too far from the optimal” and that would be equally nonsense.
by maciejzj | 2025-12-09 11:15:26+00:00
I may have developed some kind of paranoia reading HN recently, but the AI atmosphere is absolutely nuts to me. Have you ever thought that you would see a chart showing how population of horses was decimated by the mass introduction of efficient engines accompanied by an implication that there is a parallel to human population? And the article is not written in any kind of cautionary humanitarian approach, but rather from perspective of some kind of economic determinism? Have you ever thought that you would be compared to a gasoline engine and everyone would discuss this juxtaposition from purely economic perspective? And barely anyone shares a thought like "technology should be warranted by the populace, not the other way around?". And the guy writing this works at Anthropic? The very guy who makes this thing happen, but is only able to conclude this with "I very much hope we'll get the two decades that horses did". What the hell.
by lanthissa | 2025-12-09 11:15:58+00:00
i think theres a huge section of tasks which required you pay high salaries for which are gone.

just thinking from the finance world, in 2010 no knew how to program on the desk and no one knew sql, and even if they did the institutional knowledge to use the dev systems was not worth their time. So you had multiple layers of meetings and managers to communicate programs. As a result, anything small just didn't get done, and everything took time.

by 2020 most junior guys knew enough python to pick up some of the small stuff

in 2025 ai tools are good enough that they're picking up things that legit would have taken weeks to do in 2010 because of the processes around them not the difficulty and doing it in hours. A task that would take an hour to do used to take multiple meetings to properly outline to someone without finance knowledge and now they can do themselves in less time than it took to describe to a fresh cs grad.

Those tasks that junior traders/strats are able to do now that would have taken weeks or months to get into prod going through an it department i'm seeing cost drop 90% everyday right now. Which is good, it lets tech focus on tech and not learning the minutia of options trading in some random country
by kacper-vstorm | 2025-12-09 11:17:30+00:00
Python deep agent framework built on top of Pydantic AI designed to help you quickly build production-grade autonomous agents with planning, filesystem operations, subagent delegation, and skills.

A complete demonstration of all pydantic-deep features in a web application. -> (demo repository) https://github.com/vstorm-co/pydantic-deep/blob/main/example... -> (demo video) https://drive.google.com/file/d/1hqgXkbAgUrsKOWpfWdF48cqaxRh...

Features

Multiple Backends: StateBackend (in-memory), FilesystemBackend, DockerSandbox, CompositeBackend Rich Toolsets: TodoToolset, FilesystemToolset, SubAgentToolset, SkillsToolset File Uploads: Upload files for agent processing with run_with_files() or deps.upload_file() Skills System: Extensible skill definitions with markdown prompts Structured Output: Type-safe responses with Pydantic models via output_type Context Management: Automatic conversation summarization for long sessions Human-in-the-Loop: Built-in support for human confirmation workflows Streaming: Full streaming support for agent responses