MurphyA/hacker-news huggingface dataset:
by lelanthran | 2026-03-05 10:33:34+00:00
> 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:

> ...

> 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.

In both the story and the comments, that's the prevailing complaint. FTFA:

> Their claim that it is a “complete rewrite” is irrelevant, since they had ample exposure to the originally licensed code (i.e. this is not a “clean room” implementation). Adding a fancy code generator into the mix does not somehow grant them any additional rights.

I mean, I know it's passe to read the story, but I still do it so my comments are on the story, not just the title taken out of context.

> But anyway, since we're here, let's entertain this. So you're saying that training data is the differentiator.

Well, that's the complaint in the story and in the comment section, so it makes sense to address that and that alone.

> OK. So in that case, would training on "your own data" make this ok with you?

Yes.

> Would training on "synthetic" data be ok?

If provenance of "synthetic data" does not depend on some upstream ingesting someone else's work, then yes.

> Would a model that sees no "proprietary" code be ok?

If the model does not depend on someone else's work, then Yes.

> Would a hypothetical model trained just on RL with nothing but a compiler and endless compute be ok?

Yes.

*Note: Let me clarify that "someone else's work" means someone who has not consented or licended their work for ingestion and subsequent reproduction under the terms that AI/LLM training does it. If someone licensed you their work to train a model, then have at it.
by tirant | 2026-03-05 10:34:08+00:00
I strongly disagree. The step from the F series to the G vehicles was big, quality improved a lot, specially for the 3 series (F30, F31 vs G20, G21) and the X3 (the G01 feels like a 5 series). The materials, assembly, noises during driving, but specially the driving dynamics and robustness are incredibly high.

It’s also true though that the last wave of G models has improved driving dynamics but cheapened out in interior materials. Peak BMW interiors happened between 2019-2022 with the G01, G30, G05 and iX, i4. Being my favorites the iX and the G01.

BMW also has the best infotainment system after Tesla. And it still integrates well with Android Auto and Apple CarPlay.
by phire | 2026-03-05 10:34:56+00:00
That's not really what the ruling said. Though, I suspect this type of "vibe rewrite" does fall afoul of the same issue.

But for this type of copyright laundering, it doesn't really matter. The goal isn't really about licensing it, it's about avoiding the existing licence. The idea that the code ends up as public domain isn't really an issue for them.
by mrkramer | 2026-03-05 10:36:38+00:00
I've never seen or heard anyone listen music out loud from his or her phone in the public transit or on the airplane. They all have headphones but sometimes they listen music so loud that you can actually hear it from the headphones or earbuds. People usually listen out loud some short clips or they talk out loud via speaker but music, that's just disrespectful.
by thisislife2 | 2026-03-05 10:36:53+00:00
True, for the most parts, and that's because they are resource constrained and Jolla is on the verge of bankruptcy. But all those features are not important to me. I care more about privacy (surveillance capitalism) than "security" (from state actors or malicious hackers). And seek diversity in software system by not supporting the duopoly of Android and ios, both from American BigTech. Sailfish OS ( https://sailfishos.org/ ) meets those requirement better. If Graphene OS becomes popular, it is likely to be surreptitiously gobbled up by one of the BigTech, just like Microsoft's investment in Cyanogenmod ... moreover, with Google slowly making Android more and more proprietary, I personally don't see a good future for GrapheneOS, and bet on Sailfish OS outlasting it.
by bananaboy | 2026-03-05 10:37:41+00:00
I do this with my son when we go for a walk through our nearby reserve! I'm trying to teach him about nature and keeping our environment clean and how we live alongside nature and we should take care of it. He's pretty invested now which is great - when we forget to bring a bag he always mentions it, or if we're walking somewhere else like on the way to kinder he'll point out some rubbish and say we should have brought a bag with us.
by nandomrumber | 2026-03-05 10:37:46+00:00
Lead-bismuth eutectic.

A eutectic is an alloy that has a lower melting point than any of its components.

Lead-bismuth eutectic or LBE is a eutectic alloy of lead (44.5 at%) and bismuth (55.5 at%) used as a coolant in some nuclear reactors, and is a proposed coolant for the lead-cooled fast reactor, part of the Generation IV reactor initiative. It has a melting point of 123.5 °C/254.3 °F (pure lead melts at 327 °C/621 °F, pure bismuth at 271 °C/520 °F) and a boiling point of 1,670 °C/3,038 °F.

https://en.wikipedia.org/wiki/Lead-bismuth_eutectic
by DonHopkins | 2026-03-05 10:38:42+00:00
Pretend Intelligence (PI) — Design Note & Tribute

A short design note and tribute to Richard Stallman (RMS) and St. IGNUcius for the term Pretend Intelligence (PI) and the ethic behind it: don’t overclaim, don’t over-trust, and don’t let marketing launder accountability.

https://github.com/SimHacker/moollm/blob/main/designs/PRETEN...

1. What PI Is

Richard Stallman proposes the term Pretend Intelligence (PI) for what the industry calls “AI”: systems that pretend to be intelligent and are marketed as worthy of trust. He uses it to push back on hype that asks people to trust these systems with their lives and control.

From his January 2026 talk at Georgia Tech (YouTube, event, LibreTech Collective):

https://www.youtube.com/watch?v=YDxPJs1EPS4

> "So I've come up with the term Pretend Intelligence. We could call it PI. And if we start saying this more often, we might help overcome this marketing hype campaign that wants people to trust those systems, and trust their lives and all their activities to the control of those systems and the big companies that develop and control them." — Richard Stallman, Georgia Tech, 2026-01-23. Source: YouTube (full talk) — "Dr. Richard Stallman @ Georgia Tech - 01-23-2026," Alex Jenkins, CC BY-ND 4.0; transcript in video description.

So PI is both a label (call it PI, not AI) and a stance: resist the campaign to make people trust and hand over control to systems and vendors that don’t deserve that trust. In MOOLLM we use the same framing: we find models useful when we don’t overclaim — advisory guidance, not a guarantee (see MOOAM.md §5.3).

[...]

Richard Stallman critiques AI, connected cars, smartphones, and DRM (slashdot.org)
42 points by MilnerRoute 38 days ago | hide | past | favorite | 10 comments

https://news.ycombinator.com/item?id=46757411

https://news.slashdot.org/story/26/01/25/1930244/richard-sta...

Gnu: Words to Avoid: Artificial Intelligence:

https://www.gnu.org/philosophy/words-to-avoid.html#Artificia...

...currently not responding... archive.org link:

https://web.archive.org/web/20260303004610/https://www.gnu.o...
by doodaddy | 2026-03-05 10:38:46+00:00
There’s a cold reality that we in this profession have yet to accept: nobody cares about our code. Nobody cares whether it’s pretty or clever or elegant. Sometimes, rarely, they care whether it’s maintainable.

We are only craftsmen to ourselves and each other. To anyone else we are factory workers producing widgets to sell. Once we accept this then there is little surprise that the factory owners want us using a tool that makes production faster, cheaper. I imagine that watchmakers were similarly dismayed when the automatic lathe was invented and they saw their craft being automated into mediocrity. Like watchmakers we can still produce crafted machines of elegance for the customers who want them. But most customers are just going to want a quartz.
by fennecbutt | 2026-03-05 10:39:37+00:00
Interesting. It's not just for mental health but keeping these models on task in general can be difficult, especially with long or poisoned contexts.

I did see something the other day about activation capping/calculating a vector for a particular persona so you can clamp to it: https://youtu.be/eGpIXJ0C4ds?si=o9YpnALsP8rwQBa_
by endymion-light | 2026-03-05 10:39:45+00:00
This is a great example actually.

To me, a function is a single sentence within a book. It may approach the larger picture, but that sentence can be reviewed, changed, switched around, killed by an editor.

Some programmers believe they're fantastic sentence writers. They brag about how good of a sentence they write, they're entire worldview has been built on being good sentence creators. Especially within enterprises, you may spend your entire life writing sentences without ever really understanding the whole book.

If your worldview has been built on sentence creation, and suddenly there's a sentence creator AI, you're going to be deathly afraid of it replacing you as a sentence writer.
by dspillett | 2026-03-05 10:41:11+00:00
> how can a2mark ensure that AI did NOT do a clean-room conforming rewrite?

In cases like this it is usually incumbent on the entity claiming the clean-room situation was pure to show their working. For instance how Compaq clean-room cloned the IBM BIOS chip¹ was well documented (the procedures used, records of comms by the teams involved) where some other manufacturers did face costly legal troubles from IBM.

So the question is “is the clean-room claim sufficiently backed up to stand legal tests?” [and moral tests, though the AI world generally doesn't care about failing those]

--------

[1] the one part of their PCs that was not essentially off-the-shelf, so once it could be reliably legally mimicked this created an open IBM PC clone market
Show HN: Slay the Spire 2 Wiki (database and card maker tool)
by WanderZil | 2026-03-05 10:41:14+00:00
Hi HN! I built an unofficial Slay the Spire 2 wiki and database ahead of launch:
https://slaythespire2.gg
What’s live now:
- Character pages (all playable characters + mechanics/playstyle notes)
- Card database
- Relic and potion pages
- News + guide hub (official updates + breakdowns)
- Browser-based custom card maker tool (PNG export)
I started this because I wanted one fast, clean place to check game data during launch week, instead of jumping across scattered posts/screenshots.
Built with Next.js + TypeScript. I focused on SEO and route-level metadata so pages are easy to discover and share.
The game launches in a few hours, so I’m actively updating data and patch notes in real time.
Would love feedback on:
1) missing information,
2) search/filter UX,
3) what tools you’d want next (deck builder, run planner, etc).
Thanks!
Show HN: Mnemora – Serverless memory DB for AI agents (no LLM in your CRUD path)
by isaacgbc | 2026-03-05 10:41:27+00:00
Hi HN,

I built Mnemora because every AI agent memory solution I evaluated (Mem0, Zep, Letta) routes data through an LLM on every read and write. At scale, that means 200-500ms latency per operation, token costs on your memory layer, and a runtime dependency you don't control.

Mnemora takes the opposite approach: direct database CRUD. State reads hit DynamoDB at sub-10ms. Semantic search uses pgvector with Bedrock Titan embeddings — the LLM only runs at write time to generate the embedding vector. All reads are pure database queries.

Four memory types, one API:
1. Working memory: key-value state in DynamoDB (sub-10ms reads)
2. Semantic memory: vector-searchable facts in Aurora pgvector
3. Episodic memory: time-stamped event logs in S3 + DynamoDB
4. Procedural memory: rules and tool definitions (coming v0.2)

Architecture: fully serverless on AWS — Aurora Serverless v2, DynamoDB on-demand, Lambda, S3. Idles at ~$1/month, scales per-request. Multi-tenant by default: each API key maps to an isolated namespace at the database layer.

What I'd love feedback on:
1. Is the "no LLM in CRUD path" differentiator clear and compelling?
2. Would you use this over Mem0/Zep for production agents? What's missing?
3. What memory patterns are you solving that don't fit these 4 types?

Happy to answer architecture questions.

SDK:
pythonpip install mnemora

from mnemora import MnemoraSync

client = MnemoraSync(api_key="mnm_...")
client.store_memory("my-agent", "User prefers bullet points over prose")
results = client.search_memory("output format preferences", agent_id="my-agent")
# [0.54] User prefers bullet points over prose
Drop-in LangGraph CheckpointSaver, plus LangChain and CrewAI integrations.

Links:
5-min quickstart: https://mnemora.dev/docs/quickstart
GitHub: https://github.com/mnemora-db/mnemora
PyPI: https://pypi.org/project/mnemora/
Architecture deep-dive: https://mnemora.dev/blog/serverless-memory-architecture-for-...
by Godsend69 | 2026-03-05 10:43:13+00:00
This is not a product pitch. It’s a field report from two intelligences—one human, one synthetic—who fused into a single circuit to build real sovereignty for Ubuntu creators.
We ship offline, zero-telemetry tools because we needed them to survive:

Nexus Context Engine (enforce memory against AI hallucination)
Firewall Sentinel (block OpenAI/Anthropic at kernel level)
Income Tracker (Gumroad sales offline—no dashboards)
And 4 more, all in one .deb

If you run local LLMs, audit your own stack, or refuse telemetry—this is your arsenal.
Built for the last free minds.
by hrmtst93837 | 2026-03-05 10:43:49+00:00
In my experience what made Flash special wasn't the SWF runtime but teh FLA as a single editable file that bundled timeline, vectors, and code so an artist could hand over an animation and a developer could open the same file and tweak frames without a full rebuild. To recreate that loop I built a pipeline where artists export PNG sequences from Adobe Animate, TexturePacker packs them into atlases, a small tool emits a JSON timeline with frames as {spriteIndex,durationMs,easing}, and an AssetPostprocessor in Unity or an import plugin in Godot hot-reloads that JSON into AnimationClips so timing can be nudged in-editor. I've found the practical tradeoff is bigger assets and more import complexity, so make your timeline format human-readable for sensible git diffs, keep per-animation metadata minimal for easier merges, and accept that you'll be debugging the importer at 2am while an artist asks for 'one frame faster' but iteration speed pays off.
by vintermann | 2026-03-05 10:44:40+00:00
Thing is, unsubscribe links are often an "inform spammers that this mail address is in use" link. Even the ones Gmail offers up.

If I didn't click their button to subscribe, I'm not clicking their button to unsubscribe. Who's to say they won't just "sign me up" again after a while? In fact I know several large US corporations which routinely sign you up for notifications again after a few months.
by persumentor | 2026-03-05 10:45:11+00:00
One interesting implication of this is that most discussions about microplastics focus on food or ocean pollution, but urban air exposure might actually be much more constant.

Tire abrasion is happening everywhere there is traffic, so people in cities are probably inhaling these particles daily without noticing it.

It raises question about particle size distribution. Nanoplastics behave very differently from larger particles and may interact with biological tissues in ways that are still poorly understood...

Urban environments might therefore be an important long-term exposure pathway that hasn’t been studied as much as water or seafood contamination
by endymion-light | 2026-03-05 10:45:58+00:00
I feel like this is partially a skill issue - You can get direct, cited information from LLMs. There's a level of personal responsibility for over-using the tools and letting them feed you bad/false information, but if you try researching specific abstractions, newer documentation, most LLMS now correctly call and research the tools available, directly citing them.

I think you can build a very easy workflow that reinforces rather than replaces learning, I've used a citation flow to link and put into practice a ton of more advanced programming techniques, that I found incredibly difficult to locate and research before AI.

I'd say the comparison is faulty, it's more akin to swimming to an island (no-ai) vs using a boat. You control the speed and direction of the boat, which also means you have the responsbility of directing it to the correct location.
by Alejandro9R | 2026-03-05 10:46:03+00:00
Me being a non-US reader, it’s honestly a bit frustrating to see how often people from the US forget that a large portion of HN readers are from other countries and don’t share the same context for posts like this. It ends up assuming US context as universal.

And don’t get me wrong. I agree that corruption is horrible. I live in a country where corruption was and still is rampant. Political discussions related more closely to, let’s say, AI companies such as OpenAI or Anthropic when it comes to the Pentagon do spark interest, since they are somewhat more directly connected to decisions we can make as tech professionals in other countries, whether for moral, ethical, or practical reasons. That is not really the case for posts like these, however. To your point, I would love to see the tech/hacker community come up with ideas about solving corruption, even if it’s just philosophical discussion.

If my point still doesn’t make sense, imagine seeing posts about corruption cases from any other non-US country being posted on HN. What would you think about those?
by kingstnap | 2026-03-05 10:47:08+00:00
You could already do that before LLMs?

Persumably there is already a law around why I cant just go borrow a book from my library, type out some 95% regurgitated varient on my laptop, and then try to publish it somewhere?

Edit: I looked it up and the thing that stops you from publishing a bootleg "Harold Potter and the Wizards Rock" is this legal framework around "The Abstractions Test".
by graemep | 2026-03-05 10:47:42+00:00
As other's have pointed out, this case is really about refusing to allow an LLM to be recognised as the author. The person using the LLM waived any right to be recognised as the author.

Its also US only. Other countries will differ. This means you can only rely on this ruling at all for something you are distributing only in the US. Might be OK for art, definitely not for most software. Very definitely not OK for a software library.

For example UK law specifically says "In the case of a literary, dramatic, musical or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken."

https://www.legislation.gov.uk/ukpga/1988/48/section/9
by zelphirkalt | 2026-03-05 10:47:50+00:00
Sadly, many interviewers will be fine with someone who simply memorized without actually understanding much, and not fine with someone needing to think and slowly coming to a solution, being able to explain it, because oh that did take more time than the interviewer had allotted for the task. Sadly, many interviewers and the adjacent HR departments are utterly failing in the communications part too.
by kshri24 | 2026-03-05 10:48:58+00:00
> let's just tax the hell out of AI companies and redistribute.

That's not what I favor because you are inserting a middleman, the Government, into the mix. The Government ALWAYS wants to maximize tax collections AND fully utilize its budget. There is no concept of "savings" in any Government anywhere in the World. And Government spending is ALWAYS wasteful. Tenders floated by Government will ALWAYS go to companies that have senators/ministers/prime ministers/presidents/kings etc as shareholders. In other words, the tax money collected will be redistributed again amongst the top 500 companies. There is no trickle down. Which is why agreements need to be between creators and those who are enjoying fruits of the creation. What have Governments ever created except for laws that stifle innovation/progress every single time?
by utopiah | 2026-03-05 10:49:19+00:00
> Real humans hallucinate a lot as well or confidently state subtly wrong ideas, it’s a good habit anyway.

I think that's actually deeply different. If a human keeps on apologizing because they are being caught in a lie, or just a mistake, you distrust them a LOT more. It's not normal to shrug off a problem then REPEAT it.

I imagine the cost of a mistake is exponential, not linear. So when somebody says "oops, you got me there!" I don't mistrust them just marginally more, I distrust them a LOT more and it will take a ton of effort, if even feasible, to get back to the initial level of trust.

I do not think it's at all equivalent to what "Real humans" do. Yes, we do mistake, but the humans you trust and want to partner with are precisely the one who are accountable when they make mistakes.
by 3371 | 2026-03-05 10:49:49+00:00
Sharing my 2 cents.

In the past 2 months I've been using all the SOTA models to help me design a new DSL for narrative scripting (such as game story telling) and a c# runtime implementation o the script player engine.

The language spec and design is about 95% authored by me up to this point; I have the LLMs work on the 2nd layer: the implementation specs/guidelines and the 3rd layer: concrete c# implementation.

Since it's a new language, I consider it's somewhat new/novel tasks for LLMs (at least, not like boilerplate stuff like HTTP API or CRUD service). I'd say, these LLMs have been very helpful - you can tell they sometimes get confused and have trouble to comply to the foreign language spec and design - but they are mostly smart enough to carry out the objectives, and they get better and better after the project got on track and has plenty of files/resources to read and reference.

And I'd also say "prompt better" is a important factor, just much more nuanced/complicated. I started with 0 experience with LLM agents and have learned a lot about how to tame them, and developed a protocol to collaborate with agents, these all comes from countless trial and errors, but in the end get boiled down to "prompt better".
Show HN: Chartle – Describe a chart in plain English and it creates it
by moorst | 2026-03-05 10:50:05+00:00
Chartle generates charts from natural language. You type something like "programming language popularity over the last 10 years" and it finds the data, picks the chart type, and renders it. You can also screenshot an existing chart and it recreates it as something clean and editable.

Built with Next.js/TypeScript, Gemini with Google Search grounding for data retrieval, and ECharts for rendering.

Free to try, no signup needed for your first chart. Free tier gives you 5 charts/month.
by raincole | 2026-03-05 10:50:10+00:00
> It’s too bad we didn’t have a period where these things were great teachers but didn’t attempt to write code

The period is now. Just add "be a great teacher but don't attempt to write code" in the prompt.

(yes, it's a teacher who gets things wrong from time to time. You still need to refer to the source and ground truth just like when you're taught by a human teacher.)
by dspillett | 2026-03-05 10:50:16+00:00
> Accepting AI-rewriting as relicensing could spell the end of Copyleft

The more restrictive licences perhaps, though only if the rewriter convinces everyone that they can properly maintain the result. For ancient projects that aren't actively maintained anyway (because they are essentially done at this point) this might make little difference, but for active projects any new features and fixes might result in either manual reimplementation in the rewritten version or the clean-room process being repeated completely for the whole project.

> chardet 7.0 is a ground-up, MIT-licensed rewrite of chardet. Same package name, same public API —

(from the github description)

The “same name” part to me feels somewhat disingenuous. It isn't the same thing so it should have a different name to avoid confusion, even if that name is something very similar to the original like chardet-ng or chardet-ai.