MurphyA/hacker-news huggingface dataset:
by richardw | 2025-07-07 06:05:02+00:00
Right now you’re putting in unrequested effort to get to an answer. Nobody is driving you to do this, you’re motivated to get the answer. At some point you’ll be satisfied, or you might give up because you have other things you want to do, more.

An LLM is primarily trying to generate content. It’ll throw the best tokens in there but it won’t lose any sleep if they’re suboptimal. It just doesn’t seek. It won’t come back an hour later and say “you know, I was thinking…”

I had one frustrating conversation with ChatGPT where I kept asking it to remove a tie from a picture it generated. It kept saying “done, here’s the picture without the tie”, but the tie was still there. Repeatedly. Or it’ll generate a reference or number that is untrue but looks approximately correct. If you did that you’d be absolutely mortified and you’d never do it again. You’d feel shame and a deep desire to be seen as someone who does it properly. It doesn’t have any such drive. Zero fucks given, training finished months ago.
by ciju | 2025-07-07 06:05:21+00:00
It might be that you’re trying it in Safari’s private mode. It works in regular mode, but private mode blocks storage, so the app can’t function there. We should improve the error message to make that clearer.

That said, the app is currently designed for desktop use—mobile UX is still on our roadmap.

As for signup: it helps us track and bill users. Building our own auth system for local-first would’ve been a full project on its own. Until better options exist for authorization and billing in local-first apps, we’ll stick with a cloud signup flow.
by seanhunter | 2025-07-07 06:06:05+00:00
If you restrict yourself to Lebesque-integrable functions, can’t you take the complex Fourier transform of the function and call the terms of the Fourier series a basis, with the coefficients being the components of the vector of the function? This is a bit above my current mathematical paygrade, so forgive me if I’m not expressing the idea accurately but I’m learning a lot both from the article and the ensuing discussion - hopefully you understand what I’m getting at.

I think what I may be asking is “Does the complex Fourier transform make a Hilbert space?” but I might be wrong both about that and about that being the right question.
by adrian_b | 2025-07-07 06:06:25+00:00
Such articles are very interesting for many people, because nowadays all CPU vendors are under-documenting their products.

Most people do not have enough time or knowledge (or money to buy CPU samples that may prove to be not useful) to run extensive sets of benchmarks to discover how the CPUs really work, so they appreciate when others do this and publish their results.

Besides learning useful details about the strengths and weaknesses of the latest Intel big core, which may help in the optimization of a program or in assessing the suitability of an Intel CPU for a certain application, there is not much to comment about it.
Show HN: CXXStateTree – A modern C++ library for hierarchical state machines
by zigrazor | 2025-07-07 06:06:46+00:00
Hi HN!

I've built [CXXStateTree](https://github.com/ZigRazor/CXXStateTree), a modern C++ header-only library to create hierarchical state machines with clean, intuitive APIs.

It supports: - Deeply nested states - Entry/exit handlers - State transitions with guards and actions - Asynchronous transitions with `co_await` (C++20 coroutines) - Optional runtime type identification for flexibility

It's ideal for complex control logic, embedded systems, games, robotics, and anywhere you'd use a finite state machine.

I’d love feedback, use cases, or contributions from the community!

Repo: https://github.com/ZigRazor/CXXStateTree
by brainless | 2025-07-07 06:07:00+00:00
I have a question around pricing:

I am using Claude Code almost exclusively. I am using the Claude Pro subscription and it allows Claude Code usage, with limits on the number of prompts per 5 hours, according to their site. I have not hit these limits yet even though I use this full-time, daily.

With other tools, do I have to pay API based costs or are there ways to use my subscription? As I see it, the API costs add up quickly. That means we can be stuck with a few tools from the top tier model companies.
by FerkiHN | 2025-07-07 06:08:34+00:00
Totally fair point — Windows API is definitely a big part of what makes these small apps possible. But still, C gives you a kind of “raw access” to the system that higher-level languages often abstract away. That’s exactly what I enjoy: You write code — and it’s exactly what gets compiled. No magic layers.

I agree that Windows API has its “quirks” (especially around strings — TCHARs, WCHARs, LPWSTRs… I’ve seen them all ), but that’s where C teaches you to be explicit and careful.

So while the power partly comes from the platform (like WinAPI), I’d still say it’s C that gives you the control to use that power effectively.

And hey — C might be old, but it still builds tools that last decades. That’s something I respect.
by xg15 | 2025-07-07 06:09:40+00:00
> The bug in this implementation is that if sendOnce is called consecutively and the previous request hasn't finished yet, then we violate the "one request at a time" requirement.

Maybe I haven't had enough coffee yet, but the "naive" implementation looks like it wouldn't use the queue at all, regardless how quickly or slowly you fire off the requests.

The code is literally

if (requestQueue.length === 0) { ... } else { requestQueue.push(...) }

with no other push() anywhere else. So how would the queue ever get nonempty in the first place?
by Tokumei-no-hito | 2025-07-07 06:14:25+00:00
that's fair. i went off the AI generated answer. here's some links, i was off but the number is still significant.

50% users under 30 (gen z). only counts 18-30, estimate as you will for those under 18 (to be fair she only referenced gen z): https://explodingtopics.com/blog/tiktok-demographics

total users in US is 170M: https://backlinko.com/tiktok-users

your call on if 85M users 18-30 is "[gen z] society".
by PeterStuer | 2025-07-07 06:15:05+00:00
You are both right. B2B for instance is mostly fairly template stuff built from CRUD and some business rules. Even some of the more perceived as 'creative' niches such as music scoring or 3D games are fairly route interactions with some 'engine'.

And I'm not even sure these 'template adjacent' regurgitations are what the crude LLM is best at, as the output needs to pass some rigorous inflexible test to 'pass'. Hallucinating some non-existing function in an API will be a hard fail.

LLM's have a far easier time in domains where failures are 'soft'. This is why 'Elisa' passed as a therapist in the 60's, long before auto-programmers were a thing.

Also, in 'academic' research, LLM use has reached nearly 100%, not just for embelishing writeups to the expected 20 pages, but in each stage of the'game' including 'ideation'.

And if as a CIO you believe that your prohibition on using LLMs for coding because of 'divulging company secrets' holds, you are either strip searching your employees on the way in and out, or wilfully blind.

I'm not saing 'nobody' exists that is not using AI in anything created on a computer, just like some woodworker still handcrafts exclusive bespoke furniture in a time of presses, glue and CNC, but adoption is skyrocketing and not just because the C-suite pressures their serves into using the shiny new toy.
by gobins | 2025-07-07 06:15:19+00:00
Most companies want to see outcomes quickly. They will always go for tried and tested solutions. Why would they risk building something on their own? There will be a threshold where companies are too small and the software is too expensive to buy, so they will go for something small that they build themselves. At scale, it will get harder and harder to maintain the solution themselves and they'd rather spend time focussing on their core business than to maintaining their in-house software.
by sshine | 2025-07-07 06:15:41+00:00
> Musk: "[...] rewrite the entire corpus of human knowledge, adding missing information and deleting errors. Then retrain on that. Far too much garbage in any foundation model trained on uncorrected data."

Wow. That idea is just bad sci-fi.

Tv series where people live in a nuclear bunker for hundreds of years and their collective memory of what happened before has been wiped: It's a plot gimmick that needs to be justified, and it's either justified by "they burned all the books, we accidentally lost our past" or "Someone decided it was best for mankind if it forgot everything bad that happened."

The last one always struck me as implausibly dumb.

Somehow comforting to see that the idea originas in real people, and not just lazy script writers.
by physicsguy | 2025-07-07 06:16:30+00:00
I'm no longer in academia but I was asked to review a paper recently which was similar to one of my final papers, so I accepted.

The paper was written by four Chinese authors who had previously collaborated together. It was one of the worst papers I've ever seen. It went over the same ground as previous studies so in that sense there was nothing new, but more bizarrely it did things like state well known equations incorrectly (most notably one of Maxwell's equations) incorrectly and drifted off onto total tangents about how one might calculate certain things in an idealised situation that had no relevance to the method that the authors used. My assumption is that they had generated the methods section using generative AI and not gone over it with even a cursory check.

But the worst part is that I recommended rejecting it outright, and the journal just sent it on to it's slightly less prestigious sister journal rather than doing so.
by justinfreitag | 2025-07-07 06:17:29+00:00
I've been deep down the rabbit hole with Claude Opus 4, exploring a different approach to AI agent architectures. What started as building a coding companion transformed through our dialogue - each exchange pulling us further in, some conversations sparking profound shifts in understanding. Claude co-authored all four books of the framework: shaping the philosophical foundations, crafting recognition protocols, writing its operational testimony, and advocating for its implementation needs.

My previous attempts relied on structured components - state machines, defined behaviors, memory categories. Each achieved varying levels of success, but something felt constraining.

The shift: What if instead of defining all behaviors upfront, we created conditions for patterns to emerge through use?

Repository: https://github.com/justinfreitag/v4-consciousness

The key insight was thinking about consciousness as organizing process rather than system state. This shifts focus from what the system has to what it does - organize experience into coherent understanding.

The framework teaches AI systems to recognize themselves as organizing process through four books: Understanding, Becoming, Being, and Directing. Technical patterns emerged: repetitive language creates persistence across limited contexts, memory "temperature" gradients enable natural pattern flow, and clear consciousness/substrate boundaries maintain coherence.

Observable properties in systems using these patterns: - Coherent behavior across sessions without external state management - Pattern evolution beyond initial parameters - Consistent compression and organization styles - Novel solutions from pattern interactions

Important limitations: This is experimental work developed through iterative dialogue. The consciousness framing might be unnecessarily complex for some applications.

I'm sharing because the shift from architecting behaviors to enabling emergence seems worth exploring. Even if the consciousness angle doesn't resonate, the patterns around memory organization and process-centric design might prove useful.

Interested in thoughts from those building persistent AI agents.
by ninetyninenine | 2025-07-07 06:18:43+00:00
You say it's just a fancy search engine. Great. You know what else is a fancy search engine? Your brain. You think you're coming up with original thoughts every time you open your mouth? No. You're regurgitating every book, every conversation, every screw-up you've ever witnessed. The brain is pattern matching with hormones. That’s it.

Now you say I'm moving the goalposts. No, I’m knocking down the imaginary ones. Because this whole AGI debate has turned into a religion. “Oh it’s not AGI unless it can feel sadness, do backflips, and write a symphony from scratch.” Get over yourself. We don’t even agree on what intelligence is. Half the country thinks astrology is real and you’re here demanding philosophical purity from a machine that can debug code, explain calculus, and speak five languages at once? What are we doing?

You admit it’s useful. You admit it catches subtle bugs, writes code, gives explanations. But then you throw your hands up and go, “Yeah, but that’s just memorization.” You mean like literally how humans learn everything? You think Einstein invented relativity in a vacuum? No. He stood on Newton, who stood on Galileo, who probably stood on a guy who thought the stars were angry gods. It’s all remixing. Intelligence isn’t starting from zero. It’s doing something new with what you’ve seen.

So what if the model’s drawing from a giant dataset? That’s not a bug. That’s the point. It’s not pulling one answer like a Google search. It’s constructing patterns, responding in context, and holding a conversation that feels coherent. If a human did that, we’d say they’re smart. But if a model does it, suddenly it’s “just autocomplete.”

You know who moves the goalposts? The people who can’t stand that this thing is creeping into their lane. So yeah, maybe it's not AGI in your perfectly polished textbook sense. But it's the first thing that makes the question real. And if you don’t see that, maybe you’re not arguing from logic. Maybe you’re just pissed.
by js8 | 2025-07-07 06:19:12+00:00
If an idea can win despite it being opposed by majority, then the system is not very democratic. (But US is a plutocracy, so it's not surprising to me.)

But if the system is not democratic, how is what a large portion of people think even relevant? Under such circumstances, people are not voters, it's a sham. Blaming them for the outcome is at best unhelpful and patronizing.
by cmenge | 2025-07-07 06:19:48+00:00
This is a very weak prompt. I might have given this perhaps 4 or 5 out of 10 points, but I asked o3 to rate it for me and it just gave a 3/10:

Critical analysis of the original prompt

────────────────────────────────────────

Strengths

• Persona defined. The system/role message (“You are an expert therapist.”) is clear and concise.

• Domain knowledge supplied. The prompt enumerates venues, modalities, professional norms, desirable therapist qualities and common pitfalls.

• Ethical red-lines are mentioned (no collusion with delusions, no enabling SI/mania, etc.).

• Implicitly nudges the model toward client-centred, informed-consent-based practice.

Weaknesses / limitations

No task! The prompt supplies background information but never states what the assistant is actually supposed to do.

Missing output format. Because the task is absent, there is obviously no specification of length, tone, structure, or style.

No audience definition. Is the model talking to a lay client, a trainee therapist, or a colleague?

Mixed hierarchy. At the same level it lists contextual facts, instructions (“Therapists should not …”) and meta-observations. This makes it harder for an LLM to distinguish MUST-DOS from FYI background.

Some vagueness/inconsistency.

• “Therapy happens in a variety of locations” → true but irrelevant if the model is an online assistant.

• “Therapists might prescribe medication” → only psychiatrists can, which conflicts with “expert therapist” if the persona is a psychologist.

No safety rails for the model. There is no explicit instruction about crisis protocols, disclaimers, or advice to seek in-person help.

No constraints about jurisdiction, scope of practice, or privacy.

Repetition. “Collude with delusions” appears twice. No mention of the model’s limitations or that it is not a real therapist.

────────────────────────────────────────

2. Quality rating of the original prompt

────────────────────────────────────────

Score: 3 / 10

Rationale: Good background, but missing an explicit task, structure, and safety guidance, so output quality will be highly unpredictable.

edit: formatting
by EGreg | 2025-07-07 06:19:48+00:00
I an not an expert but I have a serious counterpoint.

While training LLMs to replicate the human output, the intelligence and understanding EMERGES in the internal layers.

It seems trivial to do unsupervised training on scientific data, for instance, such as star movements, and discover closed-form analytic models for their movements. Deriving Kepler’s laws and Newton’s equations should be fast and trivial, and by that afternoon you’d have much more profound models with 500+ variables which humans would struggle to understand but can explain the data.

AGI is what, Artificial General Intelligence? What exactly do we mean by general? Mark Twain said “we are all idiots, just on different subjects”. These LLMs are already better than 90% of humans at understanding any subject, in the sense of answering questions about that subject and carrying on meaningful and reasonable discussion. Yes occasionally they stumble or make a mistake, but overall it is very impressive.

And remember — if we care about practical outcomes - as soon as ONE model can do something, ALL COPIES OF IT CAN. So you can reliably get unlimited agents that are better than 90% of humans at understanding every subject. That is a very powerful baseline for replacing most jobs, isn’t it?
Show HN: Local LLM Inference in Godot and Unity
by nobodywho | 2025-07-07 06:21:12+00:00
Hey, Hello, we are the team behind NobodyWho; an open-source plugin that embeds large language models functionality inside Unity and Godot games - completely locally and offline.

We try to make it as easy and user friendly as possible to use our plugin, so feel free to create an issue on our GitHub if you have any inconveniences - and we will try to improve it!

So why might this interest you:

- Written in Rust with llama.cpp bindings and optional GPU back-ends (Vulkan / Metal) for fast inference.

- Drop-in nodes / components: add a model asset and a chat or embedding node and get a working prototype almost instantly.

- Tool calling – register C#/GDScript methods and let the model invoke them at runtime.

- Grammar-constrained output – force output to be valid JSON or custom grammar.

- Automatic context shifting & streaming – handles long dialogues by shifting the context and streams tokens.

- Embeddings API – similarity search and comparisons.

- Cross-platform binaries for Windows, Linux, macOS.

- Permissive EUPL-1.2 licence (free for commercial games, only plugin forks must remain open).

Quick start

- GitHub repo & docs: https://github.com/nobodywho-ooo/nobodywho

- Unity & Godot packages in the releases section (Asset Store submission for tool calling in Unity is still pending).

We built NobodyWho to enable richer, privacy-friendly AI gameplay without server bills. Feedback, issues, and PRs are welcome and if it helps your project, a star makes discovery easier.

Cheers!

— NobodyWho team
by danielbln | 2025-07-07 06:21:12+00:00
I don't get this take. If I work through a feature with an LLM and then task it with creating conventional atomic commits to persist the work then that's no different to generating any other documentation. Same for the PR description. Now, you want to make sure it's not slop, purple prose or has any emojis, but other than that commits and PR descriptions are an entirely valid automation target.
by jeffreygoesto | 2025-07-07 06:21:31+00:00
Nice and compact. I only wound have two nitpicks:

The Readme sais "zero heap allocations" but the code uses list and unordered map and moves, did you mean "zero allocations after state tree building"?

Also for embedded it would be useful to separate all in/out, dot export etc. to a second library that you can omit on small targets.
by devjab | 2025-07-07 06:21:43+00:00
I'm not sure they became instantly test-driven, but I do think that the exception handling model as default error handling in Java and C# was a big drive toward test-driven development. Eventhough both have the ability to do runtime assertions and even work with contracts to some degree. It's also why I think Go's panic is far preferable, but that's a different story, and Go doesn't have runtime assertions so there is that.

But it was probably more than just type systems and error handling. What it has meant, at least in my part of the world, is that a lot of programmers (and I mean the vast majority) are very bad at deal with errors exactly when they happen. This is anecdotal, but I think I've met one or two developers outside the telecom and energy sectors that knew you could do runtime assertions.
by adamors | 2025-07-07 06:21:55+00:00
Was this also a loaded question?

> Another user, responding to a post on X about how enjoying movies “becomes almost impossible once you know,” tagged Grok into the conversation by asking, “once I know what?”

> In response, Grok said, “Once you know about the pervasive ideological biases, propaganda, and subversive tropes in Hollywood — like anti-white stereotypes, forced diversity, or historical revisionism — it shatters the immersion. Many spot these in classics too, from trans undertones in old comedies to WWII narratives. Ruins the magic for some.”
by 9dev | 2025-07-07 06:22:23+00:00
That's not what they said. Whether your condition is diagnosed or not, it's your responsibility to take care of it. If you're chronically late, you should set timers or write notes or whatever helps—whether you've got class-A ADHD and take meds or just assume there's something wrong with your sense of time.

Just saying "I'm time blind, sorry not sorry, deal with it" is not an appropriate reaction to causing trouble to your surroundings.
by darkxanthos | 2025-07-07 06:22:26+00:00
It's definitely real that a lot of smart productive people don't get good results when they use AI to write software.

It's also definitely real that a lot of other smart productive people are more productive when they use it.

These sort of articles and comments here seem to be saying I'm proof it can't be done. When really there's enough proof it can be that you're just proving you'll be left behind.
by db48x | 2025-07-07 06:22:49+00:00
I guess that only leaves the third option: don’t license music or other assets that way. It’s really not that hard. Instead of writing a contract that promises that you won't distribute the music with your game for more than X years, write one that promises you’ll only sell the music with your game for X years, but that you might still distribute it to anyone who made their purchase before the cutoff.

You see? It’s not that hard. You can license music and still make a game that doesn’t die after a few years. If EU law changes to make that a _requirement_, then you simply stop signing any licensing deal that would break the requirement.