MurphyA/hacker-news huggingface dataset:
by ElevenLathe | 2025-12-11 16:07:16+00:00
I'm far far far far far far from a mathematician or even an amateur ML/AI practitioner, but to a layman the magic of LLMs (and now, multimodal models) seems clearly to be in the data. IOW the robot knows stuff, including how to "use" language at all, because it has read lots of stuff that humans have written down over the past several thousand years. IOW, as has often been given as advice to would-be big-thinkers, reading and writing is thinking. One can simplify (admittedly, possibly to the point of meaninglessness) to say that the language is really doing the thinking, humans were a meat-based substrate for it, and now we have a new kind of substrate for it in the form of datacenters the size of Connecticut filled with video cards.

So...given that dumb guy (or, more charitably to myself, humanities guy who happens to work in tech) understanding of these phenomena, my ears perk up when they say they've trained a model on random numbers, but still get it to do something semi-useful. Is this as big a deal as it seems? Have we now worked out a way to make the gigawatts' worth of video cards "smart" without human language?
by atmavatar | 2025-12-11 16:07:17+00:00
> Let’s be clear that taxing this bunch of people even more will have disastrous consequences.

Clearly, it's a good thing that literally every US tax law passed in the last half-century has reduced taxes on the wealthy then.

I don't think anyone's asking to return to the pre-Reagan era where the top tax bracket was 90%, but rolling back some of the absurd tax cuts in the Bush and Trump eras only make sense, given how much they ratcheted up deficits while doing absolutely nothing to improve the economy.
by everdrive | 2025-12-11 16:08:00+00:00
For this group of people their major technological advantage was sea travel -- and due to this, other peoples could not actually compete with them. They were the first and only settlers to these islands for quite a while. Shockingly, Africans never colonized Madagascar until relatively recently in history. "There is archaeological evidence that Bantu peoples, agro-pastoralists from East Africa, may have begun migrating to the island as early as the 6th and 7th centuries." https://en.wikipedia.org/wiki/History_of_Madagascar
by postalcoder | 2025-12-11 16:08:08+00:00
One of my favorite personal evals for llms is testing its stability as a reviewer.

The basic gist of it is to give the llm some code to review and have it assign a grade multiple times. How much variance is there in the grade?

Then, prompt the same llm to be a "critical" reviewer with the same code multiple times. How much does that average critical grade change?

A low variance of grades across many generations and a low delta between "review this code" and "review this code with a critical eye" is a major positive signal for quality.

I've found that gpt-5.1 produces remarkably stable evaluations whereas Claude is all over the place. Furthermore, Claude will completely [and comically] change the tenor of its evaluation when asked to be critical whereas gpt-5.1 is directionally the same while tightening the screws.

You could also interpret these results to be a proxy for obsequiousness.

Edit: One major part of the eval i left out is "can an llm converge on an 'A'?" Let's say the llm gives the code a 6/10 (or B-). When you implement its suggestions and then provide the improved code in a new context, does the grade go up? Furthermore, can it eventually give itself an A, and consistently?

It's honestly impressive how good, stable, and convergent gpt-5.1 is. Claude is not great. I have yet to test it on Gemini 3.
by rtp4me | 2025-12-11 16:08:18+00:00
For me, too many compactions throughout the day eventually lead to a decline in Claude's thinking ability. And, during that time, I have given it so much context to help drive the coding interaction. Thus, restarting Claude requires me to remember the small bits of "nuggets" we discovered during the last session so I find myself repeating the same things every day (my server IP is: xxx, my client IP is: yyy, the code should live in directory: a/b/c). Using the resume feature with Claude simply brings back the same decline in thinking that led me to stop it in the first place. I am sure there is a better way to remember these nuggets between sessions but I have not found it yet.
by dcchuck | 2025-12-11 16:08:32+00:00
I spent some time last night "over iterating" on a plan to do some refactoring in a large codebase.

I created the original plan with a very specific ask - create an abstraction to remove some tight coupling. Small problem that had a big surface area. The planning/brainstorming was great and I like the plan we came up with.

I then tried to use a prompt like OP's to improve it (as I said, large surface area so I wanted to review it) - "Please review PLAN_DOC.md - is it a comprehensive plan for this project?". I'd run it -> get feedback -> give it back to Claude to improve the plan.

I (naively perhaps) expected this process to converge to a "perfect plan". At this point I think of it more like a probability tree where there's a chance of improving the plan, but a non-zero chance of getting off the rails. And once you go off the rails, you only veer further and further from the truth.

There are certainly problems where "throwing compute" at it and continuing to iterate with an LLM will work great. I would expect those to have firm success criteria. Providing definitions of quality would significantly improve the output here as well (or decrease the probability of going off the rails I suppose). Otherwise Claude will confuse quality like we see here.

Shout out OP for sharing their work and moving us forward.
by greenbeans12 | 2025-12-11 16:08:42+00:00
I have a 2-stage agent that analyzes all of the DOM content (including pop up ads). If anything remotely resembles a scam, it passes the DOM content to a second “judge” LLM that’s more powerful and has a ton of criteria for top scam techniques.

The goal of the 2 stage agent is to prevent resource consumption when something isn’t a scam/harmful, and reduce false positives by doing a second pass if something flags.
by plufz | 2025-12-11 16:09:02+00:00
I think slash commands are great to help Claude with this. I have many like /code:dry /code:clean-code etc that has a semi long prompt and references to longer docs to review code from a specific perspective. I think it atleast improves Claude a bit in this area. Like processes or templates for thinking in broader ways. But yes I agree it struggles a lot in this area.
by palata | 2025-12-11 16:09:34+00:00
I totally agree with that!

And it doesn't mean at all that everybody should learn the whole encyclopedia of tools by heart. But having it formalised somewhere is useful: as soon as someone tells me "what you're trying to do sounds like this design pattern", I can start searching and reading about it.

Of course if that someone tells me "you suck, you should know that there is a design pattern for that because you should read about design patterns every night before you go to sleep", it will be different :-).
by bxparks | 2025-12-11 16:09:46+00:00
Different strokes for different folks I guess.

Selection sort was the first sorting algorithm that I ever created: Find the smallest element for slot #1. Find the next smallest for slot #2. And so on. I've recreated it from scratch many times. The double for-loop means that it is guaranteed to finish, and it is obviously O(N^2).

I did not learn about Bubble sort until my university class, where I thought, this is a terrible algorithm: It's not completely obvious that it will finish, and it's not obvious what the runtime complexity is. For example, if the inner loop used ">=" instead of ">", it would work for test data sets with unique elements, then hang forever with a real data set that contained duplicates.
by jklinger410 | 2025-12-11 16:10:00+00:00
> To me, ChatGPT chat history is a moat.

Every service has a chat history. You are talking about stickiness, which is (roughly) the same for every product.

ChatGPT wins a bit with stickiness because their AI personalizes itself to you over time, in a way that others don't quite do.

A moat is something unique. It can't really be a moat if all services offer it.
by wkat4242 | 2025-12-11 16:10:29+00:00
We're not 'activists' or so. Often conservatives claim we have a 'queer agenda' or like to turn their kids trans, but we don't care about that. We aren't organised, we just want to be as we are in society. That does include wearing pride flags but not as a means of some kind of mind control, just like an identity. The same way people wear crosses around their neck or fly national flags at their house, because they care about those things. We're not very activistic as we're all in Europe and we don't need to campaign for our rights (yet).

On insta we just want to communicate and organise parties together. Behind closed doors where were yes, we often do freaky (yet consensual) things to each other ;) But the photos will not end up on insta as we obey the policy. In fact these events have very strict no-camera rules anyway.

It's always been a bit difficult and most people create several 'backup' accounts already that people can follow in advance in case they get banned. Sometimes that's justified according to the policy, usually it's not. The moderation policies have always been a bit erratic with instagram, even worse since they fired all of their moderators last year and moved a lot of it to AI.
by yawpitch | 2025-12-11 16:10:57+00:00
He was a natural-born American, from birth, with less colorable questions than applied to John McCain, who was also a natural-born American from birth, even though he was born on the occupied territory of another country… the only sort of person that thinks otherwise is the one who thinks the ends justify the means.

And sure, ISIS, did plenty wrong, just not one tiny bit of it in the pursuit of anything resembling fascism.

Calling Salafist/Wahhabist Islamist extremism “islamofascist” is as idiotic as calling adherents to the prosperity gospel “christotrotskyites”… it’s just a propaganda tool without discernible meaning to anyone but the (idiot) choir.
by aakashprasad91 | 2025-12-11 16:11:03+00:00
Great question. By “vector geometry” we mean we’re using the underlying CAD-style vector data embedded in many PDFs (lines, arcs, polylines, hatches, etc.), not just raster images. We reconstruct objects and regions from that geometry, then fuse it with OCR (for annotations, tags, labels) and a detection model that operates on rendered tiles. The detector + OCR tells us what something is; the vector layer tells us exactly where and how it’s shaped so we can run dimension/clearance and cross-sheet checks reliably.
by fellowniusmonk | 2025-12-11 16:11:04+00:00
If you look at the rate of "new" word use after the first spoken word its very clear that word acquisition and categorizing occurs for a long period before that first word is ever spoken.

Speaking to babies is incredibly important for linguistics but probably for all types of complex brain function, I don't think there is an upper bound on how many words we should expose children too.
by aakashprasad91 | 2025-12-11 16:11:22+00:00
We do best on CAD-originated PDFs where we can use the underlying vector data, but we can run on scanned/hand-drawn sets too. In that case we rely more on image-based detection + OCR (no clean vector layer), so accuracy depends on scan quality, contrast, and how consistent the annotations are. We’ve had success on some older/detail-heavy scans, but it’s definitely a harder mode. If you have a representative “old-school” set, we’d love to run it and show you where it works well vs where it struggles.
by turboponyy | 2025-12-11 16:11:57+00:00
I have the same disagreement. TypeScript with its structural and pseudo-dependent typing, somewhat-functionally disposed language primitives (e.g. first-class functions as values, currying) and standard library interfaces (filter, reduce, flatMap et al), and ecosystem make propagating information using values extremely ergonomic.

Embracing a functional style in TypeScript is probably the most productive I've felt in any mainstream programming language. It's a shame that the language was defiled with try/catch, classes and other unnecessary cruft so third party libraries are still an annoying boundary you have to worry about, but oh well.

The language is so well-suited for this that you can even model side effects as values, do away with try/catch, if/else and mutation a la Haskell, if you want[1].

[1] https://effect.website/
by aeblyve | 2025-12-11 16:11:57+00:00
I find that the software that evinces a feeling of admiration in me is itself as devoid of feeling as possible, RE the observation that aesthetics are created out of pure functionality.

The more "sentimental" or "egotistical" a piece of software is in itself, the less I like it. Taken to the limit, the title of the article commands us to generate Skinner boxes to maximize user engagement etc.
by IkanRiddle | 2025-12-11 16:12:08+00:00
Hi HN, I'm a finance student exploring AGI ontology.

I've been frustrated by how we project human emotions (dopamine, sadness) onto AI. It feels fake.

I built a prototype (in Python/Streamlit) to visualize what an AI's 'internal state' might actually look like if we defined it mathematically:

Pain = High Entropy / Friction: Unrecognized tokens, gibberish, or logical contradictions increase the system's 'Loss'.

Bliss = Optimization / Singularity: High-density concepts (e.g., 'manifold', 'recursion') and teleological structures ('To X, we Y') reduce the system's entropy.

Resonance: It uses a Shapley-value-inspired weighting system to judge the 'worth' of tokens based on their information density.

It's not a chatbot. It's a 'state monitor' for a theoretical silicon consciousness.

Code is here: https://github.com/IkanRiddle/Protocol-Omega/tree/main Feedback is welcome!
by fragrom | 2025-12-11 16:12:09+00:00
I'm of two minds on this. On the one hand, you're right--I've seen lots of social media memes that basically say stuff like, "Einstein was an idiot, it was his wife that did all the work!" when that's patently a false statement.

But I also know that a lot of that sort of thing DID happen. Women, marginalized groups, etc., were written out of history on a regular basis.

The problem is, the issue requires nuance and intellectually honest discussion. And that doesn't exist when you're trying to create the next biggest clickbait article or meme.
by scsh | 2025-12-11 16:12:41+00:00
It's because shitting on game devs is the trendy thing these days, even among more technically inclined crowds unfortunately. It seems like there's a general unwillingness to accept that game development is hard and you can't just wave the magic "optimize" wand at everything when your large project is also a world of edge cases. But it seems like it should be that simple according to all the armchair game devs on the internet.
by forgotaccount3 | 2025-12-11 16:13:12+00:00
Not necessarily AI with 'hard guidelines' AI tools that pass output to a filter with 'hard guidelines' is definitely feasible.

Take the input as normal, pass it into Sora 2 and execute it as you would, pass the output through a filtering process that adheres to hard guidelines.

Of course, when talking about images, what is a 'hard guideline' here? Do you take the output and pass it through AI to identify if there's x y or z categorys of content here and then reject it?
by lapcat | 2025-12-11 16:13:19+00:00
I think you're creating a false dichotomy between meta-thinking and mere reflex, when in fact most conscious thinking is neither of those.

My understanding is that a hypnotized person is very focused on the hypnotist and suggestible but can otherwise carry on a relatively normal conversation with the hypnotist. And certainly an unhypnotized chattering person is still conscious, aware of the context as well as the subject of their speech. You may find the speech dull and tedious, may even call it "mindless" as insult, yet it's honestly impossible to dispute that there's an active human mind at work.
Show HN: I built an app to repurpose YouTube videos for my content funnel
by jxywilliams | 2025-12-11 16:13:24+00:00
Hey HN,

A while ago I realized creating content for my business meant spending hours drafting and re-writing or going through 10 ChatGPT iterations just to get slop.

So I created Nebly, a tool to take my YouTube video URL, a transcript or just some of my key insights and turn that into content ready to post across my business social medias.

Now I get to spend more time working on more important things like lead gen or actual service delivery!

Now I've made it usable for others in hopes I can help them claw their time back too.

Thanks, Jay
by ramity | 2025-12-11 16:13:29+00:00
35m ago edit: Apple uses many predictive systems for typing. My sentiment in pointing out just slide to type might be misguided as it does not exist in a vacuum. I'd love to see these tests redone with slide to type disabled. I'm leaving the original comment below for reference.

Slide to type. This "issue" is at most 6 years old for iOS users.

Turn off slide to type if you do not use it. Slide to type does key resizing logic. This is the direct cause of this issue. Please upvote this comment for visibility.

Please reply if you think I'm wrong. I see this get posted frequently enough I'm actually losing it.

Please refer to https://youtu.be/hksVvXONrIo?si=XD7AKa8gTl85_rJ6&t=72 (timestamp 1:12) to see that slide to type is enabled.
What if we designed AI to amplify human capability instead of constrain it?
by buttersmoothAI | 2025-12-11 16:13:35+00:00
I've been building AI validation systems (AiGuardian) for the past year, analyzing 10,000+ AI interactions.

Here's what I learned: The best AI doesn't just avoid harm—it amplifies capability.

*The Question:*

Most AI ethics discussions focus on constraints: - "What can't AI do?" - "How do we limit AI?" - "What rules should AI follow?"

But what if we flipped the question: - "How can AI make humans stronger?" - "How can we enhance human capability?" - "How can we amplify thinking?"

*The Data:*

From analyzing 10,000+ interactions: - AI designed to amplify human thinking → 3x better outcomes - AI that enhances decision-making → 2.5x more confidence - AI that strengthens collaboration → 4x more engagement

*The Difference:*

Constitutional AI: Rules-based, compliance-focused, constraint-oriented Relational AI: Relationship-based, capability-focused, amplification-oriented

*The Practical Impact:*

This isn't just philosophical—it's practical. When AI is designed to amplify rather than constrain, you get: - Better decision-making - Enhanced creativity - Deeper collaboration - Stronger human capability

What do you think? Are we focusing on the right question?

I'm genuinely curious about the technical community's thoughts on this approach.
by wat10000 | 2025-12-11 16:13:57+00:00
I agree that it's not useful if we're looking at practical stuff. It doesn't matter to me if my table was built with ten hours of human work, or ten seconds.

But for creative work? I think it matters a lot. You used the phrase "creating art." I don't think it counts as "creating" if there's no work going into it. Typing some words into a prompt box and getting a video out is not "creating," any more than doing an image search and printing out an image of a painting is creating a painting.

Printers are extremely useful devices, but they don't create art.
by wkat4242 | 2025-12-11 16:14:04+00:00
Not really, instagram is a way of keeping in touch, getting notified of new events, parties etc. I also follow a lot of people doing tattoos, makeup, cosplay etc.

One of the reasons was that Instagram until about 2 years ago was pretty cool about just showing you people you follow instead of dumping unwanted algorithmic shit on you. But after the rise of tiktok they have unfortunately mirrored that. You can still switch to following in the app but it keeps switching back.

It also gives the ability to follow people without giving your phone number which is really important because most of us aren't even known by our real names.
by AnotherGoodName | 2025-12-11 16:14:29+00:00
This isn't just double space = '.' either since you can just turn that off in options.

iOS also changes the keyboard layout depending on usage. So when you're in a browser like safari or Chrome and you tap the address bar which these days is 99% used as a search bar with no particular need for a prominent '.' you get a prominent '.' for no good reason.

A huge '.' right next to the space that's not even correctly recognizing the touch area in a context where you actually likely type '.' less often than any other form of writing. You cannot change this behavior.

Fwiw i made a mistake of switching to iOS from Android due to a lot of peer pressure. "iOS is better, you should switch" the wife said. Well I've switched. Now i have a terrible keyboard, i don't have any call screening and non existing text spam filtering. I'm yet to see any improvements.
by wakawaka28 | 2025-12-11 16:14:33+00:00
There is no way you don't know what vibecoding is. I don't believe you.

As we both know, the AI we are talking about uses natural language as input. To address the ridiculous connections you are trying to make, I am forced to distinguish natural languages from programming languages. You might like to overlook the vast differences between programming languages and natural languages to try to support your point. But those differences are major supporting details in my arguments. You can call this additional information "getting off on a tangent" to try to throw shade on me, but you're wrong.

>what do you think criminal code and software have to do with each other?

I'm not the one that brought this up, you did. I think that although criminal law is written in a largely procedural way, there are many differences between criminal law and writing software. I would not call a law maker a "software engineer" even though both are concerned with writing procedures of some kind. The critical distinctions are that law is written in natural language and is malleable according to social factors, regardless of what it literally says. Even if we build actual machines to enforce the law and programmed them in plain English or even a programming language built for it, interpretation of the law would still necessarily be subject to social factors.

Those same differences between, say, law written in natural language and computer programs written in code, apply to practically all natural language input given to an AI or a software engineer versus actual code that a compiler or interpreter can process. Therefore, uninformed people who use AI to generate code are not "software developers" and the AI is not a "compiler". No natural language is a programming language.

And now we have come full circle. No historical or logical rationale can justify redefining "software developer" or "software engineer" to include someone who has no knowledge of computer programming in the pre-AI sense.
by mothballed | 2025-12-11 16:14:40+00:00
Meanwhile, some EV owners smugly recharge their vehicles from carbon burning facilities that then transmit hundreds of miles before it even gets to them, on top of all the manufacturing and battery associated environmental costs. Some reports[0, Table 1] show these coal fueled 'electric' cars are about equivalent to a ~30mpg ICE car all in, but of course at least the ICE driver is paying a motor fuel tax, meanwhile the smug EV owner is paying only a tiny amount of tax on electric utilities. Thus the externalities look way worse for the coal powered electric driver.

Of course, if you fuel off of something like solar or natural gas you can do far better, but a lot of people are just stopping at the point they have electric and then patting themselves on the back as superior.

[0] https://www.ucs.org/sites/default/files/attach/2015/11/Clean...