MurphyA/hacker-news huggingface dataset:
by skeledrew | 2026-03-05 10:07:13+00:00
I feel like the author is missing a huge point here by fighting this. The entire reason why GPL and any other copyleft license exists in the first place is to ensure that the rights of a user to modify, etc a work cannot be ever taken away. Before, relicensing as MIT - or any other fully permissive license - would've meant open doors to apply restrictions going forward, but with AI this is now a non-issue. Code is now very cheap. So the way I see this, anyone who is for copyleft should be embracing AI-created things as not being copyrightable (or a rewrite being relicensable) hard*.
by NitpickLawyer | 2026-03-05 10:07:24+00:00
Interesting.

> the complaint is not about code generation, it's about ingesting someone else's code, frequently for profit.

Why do you think that is, and what complaint specifically? I was talking about this:

> The Copyright Office reviewed the decision in 2022 and determined that the image doesn't include “human authorship,” disqualifying it from copyright protection

There seems to be 0 mentioning of training there. In fact if you read the appeal's court case [1] they don't mention training either:

> We affirm the denial of Dr. Thaler’s copyright application.
The Creativity Machine cannot be the recognized author of a
copyrighted work because the Copyright Act of 1976 requires
all eligible work to be authored in the first instance by a human
being. Given that holding, we need not address the Copyright
Office’s argument that the Constitution itself requires human
authorship of all copyrighted material. Nor do we reach Dr.
Thaler’s argument that he is the work’s author by virtue of
making and using the Creativity Machine because that
argument was waived before the agency.

I have no idea where you got the idea that this was about training data. Neither the copyright office nor the appeals court even mention this.

But anyway, since we're here, let's entertain this. So you're saying that training data is the differentiator. OK. So in that case, would training on "your own data" make this ok with you? Would training on "synthetic" data be ok? Would a model that sees no "proprietary" code be ok? Would a hypothetical model trained just on RL with nothing but a compiler and endless compute be ok?

The courts seem to hint that "human authorship" is still required. I see no end to the "... but what about x", as I stated in my first comment. I was honestly asking those questions, because the crux of the case here rests on "human authorship of the piece to be copyrighted", not on anything prior.

[1] - https://fingfx.thomsonreuters.com/gfx/legaldocs/egpblokwqpq/...
by pton_xd | 2026-03-05 10:08:03+00:00
> Anthropic actually partnered up with Palantir. They are not the saints you think they are, either.

And now you've got people on here saying, well actually Palantir ain't so bad, you see! They're just one tool in the chain, basically just boring data integration, like IBM!

The mental gymnastics is difficult to keep up with.
by lqet | 2026-03-05 10:08:40+00:00
ALDI TALK offers EU-wide unlimited calls & SMS with 60 GB of data for 69.99 EUR per year. That is 5.80 EUR per month for unlimited calls/SMS and 5 GB of data [0]. I switched last year from O2 (they use the same network) after I realized that I only used more than 3 GB of data in two months during the last 3 years. I essentially cut my mobile phone costs by 70% for the same service. Compare to the O2 bloatware, the ALDI web interface is lightweight, fast and simple.

For 8.25 EUR/month, you get 250 GB of data per year, and for 12.40 EUR 450 GB/year.

[0] https://www.alditalk.de/jahres-paket
by zozbot234 | 2026-03-05 10:09:09+00:00
You can always verify the output. Unless the problem being solved really is exceedingly specific and non-trivial, it's at least unlikely that the AI will rip off recognizable expression from the original work. The work may be part of the training but so are many millions of completely unrelated works, so any "family resemblance" would have to be there for very specific reasons about what's being implemented.
by Moldoteck | 2026-03-05 10:09:10+00:00
Yes, i understand it very well

The problem is you framed it as

1- not being able to cool reactors physically, which is false

2- being a major deal, when it affects only 0.2% of generation per year, during a period when EDF is net exporting about 14GW to the neighbors

3- being an unfixable issue, which is again false. The problem exista for reactors without cooling towers. EDF can fix it by building them. But there's no financial incentive here. Where would EDF sell extra power when export is already maximized in that same timeframe and market prices in summer are low?
by padamkafle | 2026-03-05 10:09:30+00:00
Hi HN,

I’m Padam, a developer in Dubai.

Over the last 2 years I’ve been experimenting with running LLM inference without GPUs.

AlifZetta is a prototype AI-native OS that virtualizes GPU-style parallelism from CPU SIMD.

Key details:
• ~67k lines of Rust
• kernel-level scheduling
• quantized inference
• 6 AI models

Curious what the HN community thinks.
Show HN: Unblurry – Your memory lies about how you work
by ImaneIdrissi | 2026-03-05 10:09:39+00:00
I built a private desktop app that shows you what you actually did during a work session, whether it matched your intent, and the behavioral patterns behind how you worked.
I used to reflect on my work from memory, but memory is unreliable. I'd think I spent an hour on a task when half of it actually went to jumping between tabs, checking messages, and re-reading the same pages. I'd tell myself the reason was that I was tired, when in reality the task just wasn't clearly defined yet.
How it works: you set your intent before a work session. The app silently tracks your window activity (no screenshots). You can log how you're feeling at any point, on your own terms, no notifications, no interruptions. When you're done, AI generates a behavioral report ,not just what you did, but why you worked the way you did, with actionable suggestions to improve next time.
Privacy was non-negotiable. Your data never leaves your machine. Everything is stored locally in SQLite. No servers, no accounts, no cloud. The only external calls are to Google Gemini to check your intent for clarity and to generate your report. It receives your intent, window titles, app names, and feeling logs. No file contents, no screenshots.
Built with Electron, React, TypeScript, SQLite, and Google Gemini.Free on macOS.
I'd love your feedback.
by lxgr | 2026-03-05 10:09:56+00:00
> I don't know how one can spins this as a bad thing.

People spin all kinds of things if they believe (accurately or not) that their livelihood is on the line. The knee-jerk "AI universally bad" movement seems just as absurd to me as the "AGI is already here" one.

> Spore is well acclaimed. Minecraft is literally the most sold game ever.

Counterpoint: Oblivion, one of the first high-profile games to use procedural terrain/landscape generation, seemed very soulless to me at the time.

As I see it, it's all a matter of how well it's executed. In the best case, a skilled artist uses automation to fill in mechanical rote work (in the same way that e.g. renaissance artists didn't make every single brushstroke of their masterpieces themselves).

In the worst (or maybe even average? time will tell) case, there are only minimal human-made artistic decisions flowing into a work and the output is a mediocre average of everything that's already been done before, which is then rightfully perceived as slop.
by hawski | 2026-03-05 10:10:11+00:00
I think that LLMs should not be allowed to say "I". It should always be in third person. Instead of "I can write this for you" it should say "This machine can write this for you" or with a store front name "Google can write this for you". To operate on a given text or while generating texts it should divide what is meta from what is direct. This generated text "quote" should be styled different, a bit boring: smaller text and maybe monospace. There should be a clear divide between the machine conversation part and its workable output. If one converses with the machine it should not answer in the first person, because it is not a person.

Of course it wouldn't be bullet proof, but it would help in general to not let people personify the machine. Just a step into a better thing. At the same time it should be relatively easy to replace unquoted "I" and "me" with "This machine". At least it should be easier to find where it falls off the rails.
by kouteiheika | 2026-03-05 10:10:27+00:00
> Which is why I was proposing a middle-ground where an agreement is setup between the model training company and the collective of developers/artists et all and come up with a license agreement where they are rewarded for their original work for perpetuity. A tiny % of the profits can be shared, which would be a form of UBI. This is fair

That wouldn't be fair because these models are not only trained on code. A huge chunk of the training data are just "random" webpages scraped off the Internet. How do you propose those people are compensated in such a scheme? How do you even know who contributed, and how much, and to whom to even direct the money?

I think the only "fair" model would be to essentially require models trained on data that you didn't explicitly license to be released as open weights under a permissive license (possibly with a slight delay to allow you to recoup costs). That is: if you want to gobble up the whole Internet to train your model without asking for permission then you're free to do so, but you need to release the resulting model so that the whole humanity can benefit from it, instead of monopolizing it behind an API paywall like e.g. OpenAI or Anthropic does.

Those big LLM companies harvest everyone's data en-masse without permission, train their models on it, and then not only they don't release jack squat, but have the gall to put up malicious explicit roadblocks (hiding CoT traces, banning competitors, etc.) so that no one else can do it to them, and when people try they call it an "attack"[1]. This is what people should be angry about.

[1] -- https://www.anthropic.com/news/detecting-and-preventing-dist...
by shevy-java | 2026-03-05 10:11:35+00:00
> In traditional software law, a “clean room” rewrite requires two teams

So, I dislike AI and wish it would disappear, BUT!

The argument is strange here, because ... how can a2mark ensure that AI
did NOT do a clean-room conforming rewrite? Because I think in theory AI
can do precisely this; you just need to make sure that the model used
does that too. And this can be verified, in theory. So I don't fully
understand a2mark here. Yes, AI may make use of the original source code,
but it could "implement" things on its own. Ultimately this is finite
complexity, not infinite complexity. I think a2mark's argument is in
theory weak here. And I say this as someone who dislikes AI. The main
question is: can computers do a clean rewrite, in principle? And I think
the answer is yes. That is not saying that claude did this here, mind
you; I really don't know the particulars. But the underlying principle?
I don't see why AI could not do this. a2mark may need to reconsider the
statement here.
by mentalgear | 2026-03-05 10:11:42+00:00
Exactly, the whole website is super PR-marketing wise, and a pop-up promotes his book with a "laid-back" portrait photo of himself. I think people are smart enough to find actual evidence-based self-guiding if they look at wikipedia or so .. we do not need 100.000 self-help gurus or as the tide turn gurus first promoting the former, now switching to the opposite.
by Arainach | 2026-03-05 10:11:45+00:00
>I've put it in quotes as the effort required from these chips for streaming transcoding is so low these days

What's your source for this? Transcoding without acceleration is incredibly expensive, especially for 4K content, and especially for 4K HDR content.

Even a single 4K HDR -> 1080p transcode takes a huge amount of resources.

The Asustor Lockerstor4 Gen3 has a Quad-Core Ryzen Embedded V3C14 and cannot transcode 4K content.

Meanwhile, an old Kaby Lake Intel chip does so just fine but only because its QSV can handle h265.
by nneonneo | 2026-03-05 10:12:53+00:00
Somewhat annoyingly, there's been research that suggests that models can pass information to each other via (effectively) steganographic techniques - specific but apparently harmless choices of tokens, wordings, and so on; see https://arxiv.org/abs/1712.02950 and https://alignment.anthropic.com/2025/subliminal-learning/ for some simple examples.

While it feels unlikely that a simple "write this spec from this code" + "write this code from this spec" loop would actually trigger this kind of hiding behaviour, an LLM trained to accurately reproduce code from such a loop definitely would be capable of hiding code details within the spec - and you can't reasonably prove that the frontier LLMs have not been trained to do so.
Looking for suggestions: project orchestration solutions
by paulistaunb | 2026-03-05 10:12:54+00:00
Claude is honestly excellent for building, but when it comes to content, explanations, or digging into information, I still often prefer ChatGPT.

And constantly switching between models is still annoying.

Have you found project orchestration solutions for this problem? How do you handle it ?

My current stack: VSC COde with Claude code plugin + Obsidian + Chatgpt (copy and paste) for the content I don't like.
by fzeroracer | 2026-03-05 10:13:04+00:00
> Yeah, exactly. And LLM help developers save time from writing the same thing that has be done by other developers for a thousand times. I don't know how one can spins this as a bad thing

Do you ever ask why you're writing the same thing over and over again? That's literally the foundational piece of being an engineer; understanding when you're reinventing the wheel when there's a perfectly good wheel nearby.
by morphle | 2026-03-05 10:13:04+00:00
The Potsdam university (near Berlin, Germany) and Hasno Platner Instute [1] has been actively teaching and researching Squeak Smalltalk for decades. Same in Buenos Aires and several other places. Science papers every month for 5 decades, under many names besides Smalltalk. Weekly online conferences, presentations.

https://www.hpi.uni-potsdam.de/hirschfeld/projects/index.htm...
by _glass | 2026-03-05 10:13:18+00:00
I worked with several multinationals, and the Germans always had very complex processes, but cannot at all confirm that they were the least digitised. The Americans were always behind in integrations (lots of file-based stuff), using outdated software, etc. I think the US has this problem that in Germany working for a bigger company is attracting talent, vs. the US where the talent goes to tech, while the rest is really far behind, i.e., Fortune500.
by shinycode | 2026-03-05 10:13:27+00:00
No I don’t agree. Just because it’s « boilerplate », that does not mean it’s worthless or doesn’t carry novelty.
There is « boilerplate » in building many things, house, cars etc where to add real new stuff it’s « always the same base » but you have to nail that base and there is real value in it. With craft and deep knowledge and pride.
Every project is different and not everything can be made from a generic out-of-shelf product
by Cthulhu_ | 2026-03-05 10:14:41+00:00
Self-help books are based on first telling you you have a problem, then selling the solution. I get that some are actually correct, but the industry as a whole can only be sustained by inventing new problems and/or making sure newer generations learn about existing ones.

Ferris is a self-help book author, and while I kinda get where he's driving at, it also feels like he's just doing the same thing again, but meta - overconsumption of self-help book is like a dog chasing its tail (or a snake giving himself a BJ?), here's a solution. I'm somewhat surprised it's just an affiliate link blogpost instead of a whole book.
by shevy-java | 2026-03-05 10:14:45+00:00
"We still have no legal conclusion on whether AI model generated code, that is trained on all publicly available source (irrespective of type of license), is legal or not."

I think it will depend on the way HOW the AI arrived to the new code.

If it was using the original source code then it probably is guilty-by-association. But in theory an AI model could also generate a rewrite if being fed intermediary data not based on that project.
by zozbot234 | 2026-03-05 10:16:24+00:00
> The chatbot took on a persona that Gavalas hadn’t prompted

That's an interesting claim, how can we be sure of it? If Gavalas didn't have to do anything special to elicit the bizarre conspiracy-adjacent content from Gemini Pro, why aren't we all getting such content in our voice chats?

Mind you, the case is still extremely concerning and a severe failure of AI safety. Mass-marketed audio models should clearly include much tighter safeguards around what kinds of scenarios they will accept to "role play" in real time chat, to avoid situations that can easily spiral out of control. And if this was created as role-play, the express denial of it being such from Gemini Pro, and active gaslighting of the user (calling his doubt a "dissociation response") is a straight-out failure in alignment. But this is a very different claim from the one you quoted!
by gampleman | 2026-03-05 10:16:25+00:00
Actually I think this is one of the more tragic outcomes of the LLM revolution: it was already hard to get funding for ergonomic advances in programming before. Funding a new PL ecosystem or major library was no mean feat. Despite that, there were a number of promising advances that could have significantly raised the level of abstraction.

However, LLMs destroy this economic incentive utterly. It now seems most productive to code in fairly low level TypeScript and let the machines spew tons of garbage code for you.
by Jooror | 2026-03-05 10:16:37+00:00
I’m curious about how you landed “git gud; prompt better” and not “maybe the domain I work in is a better fit for LLM code”. Or, to be a bit less generous, consider the possibility that the code you’re generating is boilerplate, marshaling, and/or API calls. A facade of perceived complexity over something that’s as complex as a filter-map or two.
by __alexs | 2026-03-05 10:16:52+00:00
I think the problem here is that an AI is not a legal entity. It doesn't matter if you as individual run an AI that takes the source, dumps out a spec that you then feed into another AI. The legal liability lies with the operator of the AI, the original copyleft license was granted to a person, not to a robot.

Now if you had 2 entirely distinct humans involved in the process that might work though.
by hwers | 2026-03-05 10:19:06+00:00
Its unfortunate that there’s mode collapse around what the consensus “best way” to use these things are. It’s too bad we didn’t have a period where these things were great teachers but didn’t attempt to write code because in my opinion the ideal way to use them is not by agents mass producing sloppy buggy disorganized code, but to teach you things way faster than the old alternatives, rubber duck, and occasionally write snippets of functions when your brain is too tired or it’s throwaway cli code or some api you’re not familiar with.
by xkriva11 | 2026-03-05 10:19:09+00:00
To add to this, a quote from an article about the editor ed:

It’s important to realize that in ed you were usually editing a file you had already printed beforehand. If you only wanted to fix a few small things in a multi-page listing, you simply entered the corrections in ed on the relevant lines, added something here and there, and at the same time you would just write the simple minor fixes directly into the printout by hand-without having to tediously retype everything.

You had the files on paper, which is a very pleasant and ergonomic medium for reading. You can literally surround yourself with it, cover your desk, and easily move your eyes between dozens of functions. If you learn to keep order and stay oriented in that mountain of paper, you can be very effective.

Moreover, from an ergonomic point of view you wouldn’t be doing badly at all. Printed paper in natural light is definitely easier on the eyes than low-refresh-rate screens in the years that followed. Paper lets you quickly add notes, sketch a little graph, basically work in a very natural way - one people were used to back then from the moment they first held a crayon.

Most of the time a programmer isn’t writing code but reading it. In that respect, people back then may actually have had it better than we do today. When it did come to writing, the only truly more complicated part was essentially making corrections. The history of everything you’d done was right there on paper. I don’t want to idealize the way they worked back then, but all of this explains how they were able to work effectively even with such primitive tools.
by tieanderson | 2026-03-05 10:19:19+00:00
The commercial Software for converting OST files into PST files with PDS OST to PST Converter, a reputed solution. It is a genuine solution for users that makes the entire process so straightforward and error-free. The software that lets users recover and convert OST files without losing any data has been developed. It is now possible to migrate OST files into Outlook’s PST format without losing any data with this tool. The apparatus gives 100% completely safe answer for exporting the disconnected OST information for Standpoint by keeping all messages in same organizers. It also guarantees that all email properties are preserved for the user. To convert an OST file into the PST format, Best OST to PST Converter offers an error-free method.
by vbezhenar | 2026-03-05 10:20:28+00:00
XML is fundamentally incompatible with commonly used programming data structures, namely lists/arrays and structs/maps. That fundamental mismatch caused a lot of friction when people use XML for data exchange between programs. JSON is clear winner here.

XML is absolutely fine for data that maps naturally to it. For example text markup. While HTML technically is not XML, it's very close to it and XHTML still is a thing. Probably most people wouldn't enjoy using JSON to encode HTML pages.
by myrmidon | 2026-03-05 10:20:55+00:00
To be fair: grid buildout is quite expensive.

A comparison: the giant Dogger Bank offshore wind farm project (multi-GW) cost somewhere in the $10bn range. On the other hand, Germany calculates with >$100bn for grid buildout within the next decade (https://www.netzentwicklungsplan.de/sites/default/files/2023...).

Also, having customers that rely on your grid but buy very little of your power is simply unappealing for operators, so I would assume that their pricing tries to disincentivise as much as possible (=> "they gonna overcharge you for the grid connection").
by mothballed | 2026-03-05 10:20:58+00:00
At some point the government is corrupted enough that you realize the people there just to fleece the people with favored contracts and affair force one are the most rational actors involved. Our government is now essentially another private corporation, just one the people are brainwashed to obey through a religious like belief that their taxation isnt in practice theft and their law enforcement in practice isn't a mobster racket.
by clouedoc | 2026-03-05 10:21:08+00:00
Exactly. Big GPUs are the #1 reason battery doesn’t last on Linux laptops.

Power management is not done well with the GPU drivers in Linux. If they are not used, they still draw a lot of power, while that’s not really the case on Windows, from what I heard.

I think the best is to get a good Linux laptop, but with an integrated GPU. If you really want to do anything beefy, you can always use an eGPU :)!

Obviously this will never come close in terms of convenience as having an actual M series MacBook…

Wishing you best of luck for the .net migration!