MurphyA/hacker-news huggingface dataset:
by xanthor | 2026-03-01 16:36:45+00:00
You chose the Internet Archive as authoritative evidence, not me. Your back-pedaling "most likely explanation" is again disproven by your own source as the Internet Archive recorded an error page for that URL just four minutes prior. So we know that the document was not available before September 1, after Bachelet's term had ended.

Where has the UN asserted that Bachelet prepared this report? Please share if you are aware of any such assertion.

Again, the report does not make any reference to the High Commissioner's inquiries as other reports do. Your "most likely explanation" fails to account for this.

Yes, media outlets lie and make errors all the time. Sorry to be the one to break this to you.
by KPGv2 | 2026-03-01 16:36:47+00:00
The USSR's (well, Russia's) growth had begun before WW2, and it was in response to pre-WW1 Russian being severely underdeveloped. There was a ton of room for growth that started before WWII, and it continued unabated.

Basically, Russia up to WW2 had economic growth because it was "catching up" to the West. Industrialization was one place. Literacy was another. There was a huge effort to improve literacy after the Tsar was killed.

Finally, because the Nazis occupied Ukraine during WW2, Russia/the USSR had to develop other places during WW2 just to feed its people, which accelerated growth post-war.

These conditions do not exist today, I don't think. But this isn't my area of expertise. I just know that Russia was a feudalistic shithole until the Tsar was overthrown, and then they worked hard to turn the serfs into educated and literate people, right as they were forced by invasion to economically develop previously overlooked lands.

If you want a very pro-1% take on this, check out Anna Karenina. The "good guy" main character of the novel is a large landowner with a lot of serfs (read: slaves) whom he visits and instructs, based on latest science, how to farm better.

Same thing happened in Japan about a generation or two earlier. There's ar eason tiny, flyover Japan beat Russia in the Russo-Japanese war. Russia was totally backwards, even by "barely industrialized Japan" standards.
by pbohun | 2026-03-01 16:36:57+00:00
It's not ape coding. It's skill coding. People who don't have the skill to do math and logic ask others to do it for them.

The reason we have programming languages is the same reason we have musical notation or math notation. It is a far more concise and precise way of communicating than using natural languages.

We could write music using natural language, but no one does because a single page of music would require dozens of pages of natural language to describe the same thing.
by spwa4 | 2026-03-01 16:37:13+00:00
Israel did not set up Hamas, Israel prevented the PA, then the PLO, which was taken over and supported by the KGB from massacring Hamas in it's krib.

That's one very underappreciated part of the conflict there. That the KGB and Israel fought one another, obviously long ago. As part of that fight, they both helped/financed/protected/... lunatic Palestinian movements. The KGB is long dead and Israel started regretting many of it's actions against Russia decades ago, but the lunatic movements each created are still massacring one another.

Oh and the UN is still supporting and financing the PA, even against Hamas. Hmmm, I wonder if anyone at the top of the UN ever had any affiliation with Soviet Foreign policy ... (say, for example, the best-paid politician in the entire world, obviously a communist)
by cmyk_student | 2026-03-01 16:37:24+00:00
They weren't published because the person who interviewed everyone is now the project maintainer, and ran out of time to do transcriptions. :)

I volunteered to help with transcription, so I was given several audio recordings and started working on them. The first "resurfaced" one was Simon Budig: https://www.gimp.org/news/2025/11/01/simon-budig-interview-w...

There's about 4 more from another event which I'll be working on between coding and other things. There's definitely some material that's a bit dated (for instance, the comment about non-destructive editing), but I think it's still interesting insight into development.
by pelasaco | 2026-03-01 16:37:38+00:00
"AI is making junior devs useless" is a dangerous and incorrect conclusion. If this idea is repeated too often, people may start to believe it and even quit studying computer science altogether.

First of all, developers who only learn to code in a short bootcamp are often not well prepared — but that was already true before AI. In the past, many junior developers were students who were learning programming while studying, not just people who took a quick Python course on Udemy.

Instead of declaring junior developers useless, we should raise the standard: learn how to code properly, how to maintain code, understand networks, and build strong foundations in math and computer science. A well-trained junior developer is still extremely valuable and will always be needed.
by robwwilliams | 2026-03-01 16:37:45+00:00
Perfect! I read this “heart-warming” overview of two papers in Science and learned zero about why this is of any significance. The discovery is significant but I had to probe Opus 4.6 to find out why.

The personal focus is a
distraction. It would be great if science writers could focus on the science and significance of the advance.
by jraph | 2026-03-01 16:38:34+00:00
A lot of the complains expressed in this article are distinctly from the proprietary parts.

Stock Android, and especially stock Samsung, is far from being a free software solution.

A turnkey solution based (almost exclusively, and except the driver blobs) on free software would be to buy a phone running something like /e/. I think they also provide backups.

Of course, stuff requiring SafetyNet (or whatever Google current oppressive attestation system) may not work (though microG makes some of it work).
Show HN: OpenTT – a self-hosted tool for managing table tennis leagues
by tradicije | 2026-03-01 16:38:46+00:00
Hi HN,

I built OpenTT, a self-hosted tool for managing table tennis leagues.

It started as an internal solution for my own amateur club. We were relying on PDFs, spreadsheets, and messaging groups to track match results and standings, which quickly became difficult to maintain and inconsistent.

OpenTT automates:

- League management
- Match tracking
- Dynamic standings and rankings
- Context-aware tables (standings adjust based on the round being viewed)

It’s designed to be self-hosted so clubs keep full control over their data. The project is open source (AGPL-3.0) and intended for small clubs and amateur leagues that don’t want SaaS subscriptions.

Repository:
https://github.com/tradicije/ttopen

Release:
https://github.com/tradicije/ttopen/releases/tag/v1.0.0

I’d appreciate feedback, especially around:
- Feature scope
- Deployment expectations
- What would make this genuinely useful for small organizations

Happy to answer any technical questions.
by __bjoernd | 2026-03-01 16:38:59+00:00
> Here is something that gets lost in all the excitement about AI productivity: most software engineers became engineers because they love writing code.

This resonates somewhat, but for a different reason. My mental model is that there are two kinds of developers, the craftsmen and the artists.

The artist considers the act of writing code their actual fulfillment. They thrive on beautifully written code. They are often attached to their code to a point where they will be hurt if someone criticizes (or even deletes) it.

The craftsman understands that code exists to serve a purpose and that is to make someone's life easier. This can be a totally non-technical customer/user that now can get their work done better. It could be another developer that benefits from using a library we wrote.

The artist hates LLMs as it takes away their work and replaces their works of beauty with generic, templatized code.

The craftsman acknowledges that LLMs are another tool in the toolbelt and using them will make them create more benefits for their customers.
by skeledrew | 2026-03-01 16:39:04+00:00
All that humanity has achieved happened due to the simple loop of identifying a desire/need and finding a way to satisfy it. Also known as reinforcement learning. The only thing that really differentiates humans from machines is... history. We've been learning and passing on our knowledge to successive generations over millennia. Nothing really special there; give the machines a few years to learn and see what happens.
by s_ting765 | 2026-03-01 16:39:40+00:00
> Ptyxis: Your Container-Oriented Terminal for GNOME

> A modern terminal emulator built for the container era.
Seamlessly navigate between your host system and local containers like Podman,
Toolbox, and Distrobox with intelligent detection and a beautiful, responsive
GNOME interface.

https://gitlab.gnome.org/chergert/ptyxis/-/blob/main/README....
by crazy5sheep | 2026-03-01 16:40:26+00:00
The whole point is that LLMs, especially the attention mechanism in transformers, have already paved the road to AGI. The main gap is the training data and its quality. Humans have generations of distilled knowledge — books, language, culture passed down over centuries. And on top of that we have the physical world — we watched birds fly, saw apples drop, touched hot things. Maybe we should train the base model with physical world data first, and then fine tune with the distilled knowledge.
by lenerdenator | 2026-03-01 16:40:32+00:00
You're going to have to do the unthinkable:

Invest in the training of your junior employees.

The cost of generating code is now laughable, so that's not the economic value brought to the table by a junior engineer, or really, any engineer. The value is now generated by knowing what code is good code. You're going to have to have talks, book clubs, hackathons, and the like to get your juniors to know what good code is. Do they know what design patterns are? How about good architecture? If they can't name a few design patterns, you're not investing enough.
by g947o | 2026-03-01 16:40:44+00:00
It is very easy to understand -- Google loses nothing by acting this way. They despise these users (and users in general by not providing any meaningful customer service), so it's natural they just cut off access completely.

If you think about how people's entire Google accounts are getting banned without apparently violating any terms without the ability to talk to someone or appeal, this feels almost nothing.
by hagbard_c | 2026-03-01 16:40:47+00:00
What is it in your life which makes it 'impossible' to use free software, Google-free AOSP-derived Android distributions being part of this? I run close to exclusively free software and have done so for decades and have yet to feel the need to change this. Of course there are exceptions, e.g. I need to run proprietary applications for banking and electronic ID but those are the exceptions to the rule. My server runs only free software, on desktop I sometimes run an older version of Sketchup to start modelling things but that's the only non-free package I use there. We have children, a cat, a dog, 4 horses, a farm, a large forest, the works. We have multi-device backup and restore as well. Things work fine, using free software, not using 'the cloud'. Where are the sticking points for you and what would it take to take those away?
by VladCovaci | 2026-03-01 16:40:56+00:00
Here is what we’ve built: founderspace.work to help founders validate and position their startup idea before writing any code. You explain your idea in simple terms, and our AI evaluates market demand, competition, timing, and early adopters, then creates a clear validation brief with practical next steps. The goal is to save time by avoiding ideas that sound good but don’t have real demand.

How we’ve done it:

We used BMAD Core agents for planning. These agents are crucial because it’s like having a whole Product department inside your codebase. These agents are creating and providing the context your coding agents need.

For coding we used claude code the 20$ a month plan.

As a conclusion: Validate -> plan with AI Agents -> execute -> GTM

Thank you Hacker News Community
by kevinsync | 2026-03-01 16:41:14+00:00
> The pessimist in me thinks that the window of opportunity to create something successful is shrinking.

Dunno man. Ideas alone aren't worth anything [0] and execution is everything [1], but good ideas and great execution will never go out of style regardless of how much competition is out there. I'm of the opinion that even if 10% of the population is now capable of creating a side project, there's still the same relatively-fixed amount of people capable of making a good side project, and even fewer who will see it through to a real product. Nothing has really changed in the aggregate. It's like architecture, there are always improvements in materials, tools and processes, and Claude and Codex can provide more laborers for almost free, but most people are still gonna be building uninspired McMansions instead of the Guggenheim.

[0] https://youtu.be/YYkj2yYaGtU?t=112

[1] https://youtu.be/YYkj2yYaGtU?t=160
by eibrahim | 2026-03-01 16:41:28+00:00
The article makes a reasonable case for internal tools but glosses over the elephant in the room: if every company can vibe code their own B2B tools, what happens to the SaaS vendors? The ones that survive will be the ones where the distribution and ecosystem around the product matters more than the code itself. Nobody is going to vibe code their own Stripe or Salesforce, but the long tail of niche B2B tools is absolutely vulnerable.
by zozbot234 | 2026-03-01 16:41:28+00:00
> Because the bottleneck was never typing code. It was always understanding the problem, making architectural decisions, debugging edge cases, and most importantly - knowing what NOT to build.

The AI can help you in these tasks too, but you need to ask for the help in terms that it can help you with, and not expect it to be genuinely intelligent or to have a crystal ball. As a bonus, once you've gotten these things into the agentic context, the code itself becomes better too.

One-shotted vibe coding is an anti-pattern.
by cmyk_student | 2026-03-01 16:41:28+00:00
We do now have a UX repo to ask for user UX/UI reports and feedback - anyone can contribute, no coding required: https://gitlab.gnome.org/Teams/GIMP/Design/gimp-ux/-/issues

Our release posts now regularly feature a UX/UI section where we highlight the work being done. We've implemented a lot of low-hanging fruit and localized fixs, while we continue to grow our design volunteer group and build larger designs.
by srean | 2026-03-01 16:42:23+00:00
What I am claiming isn't even controversial. It's quite well known and accepted. So much so all the standard search engines will confirm it, and search engines typically reflect a consensus view of crawlable documents.

This is what I get when I pose the question

"Yes, Israeli officials have acknowledged providing covert financial support to Sheikh Ahmed Yassin’s Islamist networks in Gaza during the late 1970s and 1980s. This was done to bolster religious groups as a counterweight to the secular Palestine Liberation Organization (PLO), which was viewed as the primary adversary at the time"
by oytis | 2026-03-01 16:42:23+00:00
I think it has got past the uncanny valley really - it does read like a human, just a very attention-seeking one, like your typical LinkedIn salesman.

That's probably just default settings though - I asked it to rewrite, and most of the tell-tale signs are gone as I can see (apart from the em-dash)

https://chatgpt.com/s/t_69a46b290fb08191ad3bd93066b8cad4
by gimmeThaBeet | 2026-03-01 16:42:33+00:00
I agree, or at least I would stress that people should be allowed to consent to that.
I don't know what the prevailing medical ethics of doing that kind of thing in consenting patients
in that state, but my uninformed intuition is I would disagree with it.

Though one thing that I might think researchers might not want is people may be too sick to recover even if their cancer disappeared tomorrow.
by dismalaf | 2026-03-01 16:43:07+00:00
This is literally the midwit meme...

Here's how you actually set up an Android phone:

- log into Google account

- select a few checkboxes (basically just if you want to restore apps or not)

- done, everything else is automatic

All the fuckery they decided to do because they think they're tech savvy wasn't required.
by saghm | 2026-03-01 16:43:09+00:00
Producing code that does what's intended. The metric is fuzzy and based on the usage of the software, not the scale of lines of code. The extent of the importance of the code itself is that I'm practice software tends not to be "one and done", so you need to be able to go back and modify it to fix bugs, add features, etc., and it turns out that's usually hard when the code is sloppy. Those needs still should stem from the sandal actual user experience though, or else we've lost the plot by treating the mechanism as the goal itself
by errorlsc | 2026-03-01 16:43:44+00:00
I'm the author of Polars.NET, a project which aimed to bring pola-rs to .NET world.
Recently I got a issue that asked me to add delta table support for Polars.NET, that is really a good idea, then I tried my best. But since there is no direct rust API from pola-rs let me to call like scan_delta or sink_delta, I have to build the solution by combining pola-rs and deltalake rust crate.
Scanning is not that hard but for write side, I tried to export polars dataframe to arrow record batch to let deltalake help me to write, but I have to turn on datafusion as an extra dependency and SQL parser is also needed here, which will make the final binary size huge(near 80MiB). The final solution I chose is to build delta calculation layer by pure polars expression engine, and use deltalake crate to commit transactions.

Thing turns out that everything goes well since the benchmark result is quite amazing. Because I'm gluing everything in Rust rather than C# side, Z-ordering and deletion vector can also be handed by polars and some rust functions, which is efficient
by 7777777phil | 2026-03-01 16:43:55+00:00
I went through 12 bank AI research reports (1) last week and power was the one thesis that held up no matter where you stand on the productivity question. Barclays projects US data center power hitting 560 TWh by 2030, up from roughly 160 TWh now, about 13% of total electricity. Goldman says 60% of that needs net-new generation on a grid that averages 40 years old.

What this article gets at is that the volatility.. Steady demand growth you can plan for. Facilities that swing from full draw to near-zero faster than operators can rebalance, that's a different kind of stress entirely.

(1) https://philippdubach.com/posts/when-every-bulge-bracket-ban...
by RevEng | 2026-03-01 16:44:01+00:00
Same here. I like bringing ideas to life; code is just a means to an end. I can now give detailed designs to an AI and let it write the hundreds of lines of code in just minutes, and with far fewer typos than I would make. It's still not perfect - I have to review it all - but if I give it a proper spec in generally creates exactly what I had in mind.
by Bumblebiber | 2026-03-01 16:44:15+00:00
Some core features worth calling out:

5-level lazy loading instead of flat RAG. On spawn, agents receive only L1 — one-line summaries of every memory entry.
When something looks relevant, they drill into L2, L3, etc. on demand. This keeps startup context small (~2k tokens
for 200 entries) while still having full verbatim detail available at L5.

Tab indentation maps directly to tree levels. No schema to think about — just write:

write_memory(prefix="L", content="Always restart MCP server after recompiling TS
Running process holds old dist — tool calls return stale results
Fix: kill $(pgrep -f mcp-server)")

Indented lines become children. Siblings at the same depth are siblings in the tree. append_memory adds children to
any existing node without overwriting.

Smart bulk-read selection. Not all L1 entries are shown equally. The V2 selection expands (shows children) for: newest
N entries per prefix, most-accessed M entries (time-weighted score), and all favorites. Everything else shows as a
compact title with a [+7 →] hint. This mirrors how human working memory works — recent and frequently-used things are
immediately accessible.

Obsolete, not deleted. When a lesson turns out wrong or a decision gets reversed, you mark it obsolete with a
correction reference ([E0076]). The old entry gets hidden from bulk reads but stays searchable. Past mistakes still
teach — you just don't pay tokens for them every session.

Per-agent isolation + optional shared store. Each agent has its own .hmem SQLite file. There's also a company.hmem
with role-based access control (worker/al/pl/ceo) for knowledge that should be shared across agents.

The whole thing is a single MCP server, ~3k lines of TypeScript, backed by SQLite with WAL mode. No vector embeddings,
no external services. Works offline.

OpenClaw users: you can integrate hmem directly by pointing your Claw at the GitHub repo — it'll figure out the rest.
npx hmem-mcp init gets you running in under a minute.
by librasteve | 2026-03-01 16:44:31+00:00
This looks very much fun. A little known fact is that the original Raku implementers were all Haskell heads and PUGS one of the first Raku parsers was written in Haskell by Audrey Tang.

Raku is mainly written in a custom subset “NQP” and the team is now cranking on RakuAST for 6.e which is rewriting the Raku parser as a Raku Grammar.
by devsda | 2026-03-01 16:44:47+00:00
Ah, just in time summarizing what we went through recently. Our "leaders" officially added these to our already nonsensical list of goals.

A. Measurably demonstrate that atleast 50% of code/tests are AI generated.

B. X% Faster delivery timelines due to improved productivity tools.

You can't expect to make a pizza in 50% less time just because you bought a faster doughmaker. Specially when you don't even know whether the dough comes out under kneaded, over kneaded or as plain lumps!
by ndriscoll | 2026-03-01 16:45:03+00:00
I suspect that the quality is ironically correlated with the expertise of the user (i.e. it is knowledgeable if you are knowledgeable), which puts you in a conundrum (I can report that with a couple decades of experience, LLMs are giving me high quality, correct results, but I can already see that it somehow doesn't work as well for some of my less experienced colleagues. A lot of what I've been doing over the last couple months is trying to find how to make it "just work" for them.).

As a general principle, take advantage of the fact that it can easily generate stuff. If you don't know whether something is true, have it prove it. Make a PoC/test/benchmark to demonstrate what it's saying. Have it pull metrics that you have access to. Add more observability. Create feedback loops (or rather, ask it to create feedback loops). They're very good at reasoning given access to the ground truth, so give them more ability to ground themselves.

They also have fantastic knowledge of public things, but no knowledge of your company, so your instructions should mostly be documentation of what's unique to your company. If it can write an instruction on its own (e.g. how to use git or kubernetes), it is a useless instruction; it already knows that. What it doesn't know is e.g. where your git server is. It also doesn't know what matters to your company: are you a startup trying to find product market fit? Are you an established company that is not allowed to break customer setups? etc. You might even be able to ask it what kinds of questions a senior might ask about how a company/team works when coming into a new job, and then see if you can answer those questions (or find someone who can).