MurphyA/hacker-news huggingface dataset:
by casualscience | 2026-02-16 06:33:07+00:00
I see, so there's actually an additional for loop here, which is `sleep(n); check_all_conversations()`, that is not something claude code does for sure.

As far as the 'soul' file, claude does have claude.md and skills.md files that it can edit with config changes.

One thing I'm curious about is whether there was significant innovation around tools for interacting with websites/apps. From their wiki, they call out like 10 apps (whatsapp, teams, etc...) that openclaw can integrate with, so IDK if it just made interacting with those apps easier? Having agents use websites is notoriously a shitty experience right now.
by Lerc | 2026-02-16 06:33:29+00:00
It's comparatively few really

for instance yours comes out as

Analytical 45%, Cynical 30%, Pedantic 15%, Melancholic 10%

and mine is

Philosophical 35%, Hardware-Obsessed 25%, Analytically Pedantic 20%, Retro-Nostalgic 15%, Anti-Ad Skeptic 5%

You should consider gathering all of your analysis and pedantry into one easy to manage neurosis.

It's from https://hn-wrapped.kadoa.com
by Unearned5161 | 2026-02-16 06:33:45+00:00
There seems to be a lot of confusion in this thread around the human mind's processing of voice sounds.

As with most (all?) things we do, exposure is king. This is how we don't die from trying to process infinite dimensional reality. The brain compresses, it prunes. Things seem similar if you don't have much need to distinguish them.

Unless you've listened to hours of either NotebookLM or Greene, you simply won't be able to participate in the distinguishing of these voices with much ability.
by menaerus | 2026-02-16 06:34:35+00:00
> I hope that paid access to AI tools gives better results

You should get yourself a paid subscription. Honest advice. The difference between agentic workflow vs single-shot questions in free-tier services is night and day. Building context and letting the model have access to your code is the largest differentiator between "wtf, I don't need this" and "wtf".

> All that I see is that the AI systems outperform humans for various tasks only because they had access in their training data to much more information than most humans are allowed to access, because they do not have enough money to obtain such access

Humans cannot even theoretically read and consume the volume of data the models can do so it's not really about the money - it's more about the infinite amount of time humans would need to have and the extremely large cognitive load it would impose on them. How many people can even synthesize so much diverse topics at high and constant pace? None or very little.

Also, models are proven to generalize very well so having access to your codebase during the training phase is not necessary for them to provide you with the correct answers. Give it a try.

Models being able to generalize very well is one of the ways AI labs think they may reach the "AI systems will be better than any human at any cognitive task" goal. I am not convinced that this will be the only sauce needed but I am also not too skeptic about it too, given the speed at which AI capabilities unfolded, especially during the 2025.

I think we already reached the point where it's safe to say that "AI systems are better than many humans at most cognitive tasks". I can see it myself on the project I am currently working on. These are not the top-tier developers. And when I talk to the top-tier ones I have previously worked with, we share the similar sentiment. The only difference might be "AI systems are much faster than many humans at most congitive tasks".
by modeless | 2026-02-16 06:34:40+00:00
Revisiting this and I have to say the sheer number of demos on this page is incredible. I love this one in particular as I remember this classic scene from Veach's thesis: https://erichlof.github.io/THREE.js-PathTracing-Renderer/Bi-...

If you have a good GPU the default parameters underutilize it. This demo lets you crank up the "samples per pixel" parameter to get good quality in real time: https://erichlof.github.io/THREE.js-PathTracing-Renderer/Mul...
Show HN: Free Browser-Based Dev Tools (No Signup, Client-Side)
by maxxmini | 2026-02-16 06:34:42+00:00
I built 9 free browser-based developer tools, all hosted on GitHub Pages with zero cost. Includes JSON Formatter, Regex Tester, CSS Grid Generator, Color Palette Generator, Markdown Preview, Clipboard Manager, Password Generator, Unit Converter, and API Response Viewer. Everything runs client-side, no sign-ups, no tracking. Built as a weekend project to scratch my own itch.
by mcny | 2026-02-16 06:35:27+00:00
The big brands should be penalized for doing the burning or destroying themselves, enforcing such destruction through contract laws or any formal communication, or even through punishment by denying future contracts.

The receiver on the other end should defect and renege on their contract and sell the goods in the open market for pennies on the dollar. While they won't be able to bring it back to western countries, they should absolutely be able to sell them locally. It should be legal for them to renege on any illegal contracts.

At least that's how I see it.
by Taek | 2026-02-16 06:36:18+00:00
My understanding is that this is purely a strategic choice by the bigger labs. When OpenAI released Whisper, it was by far best-in-class, and they haven't released any major upgrades since then. It's been 3.5 years... Whisper is older than ChatGPT.

Gemini 3 Pro Preview has superlative audio listening comprehension. If I send it a recording of myself in a car, with me talking, and another passenger talking to the driver, and the radio playing, me in English, the radio in Portuguese, and the driver+passenger in Spanish, Gemini can parse all 4 audio streams as well as other background noises and give a translation for each one, including figuring out which voice belongs to which person, and what everyone's names are (if it's possible to figure that out from the conversation).

I'm sure it would have superlative audio generation capabilities too, if such a feature were enabled.
by gwern | 2026-02-16 06:37:25+00:00
I think there's still something missing here. This is a strange place for ChatGPT to confabulate quotes: extracting short quotes from a short text blog post is about easy as it gets these days. GPT-5.2 Pro can handle tens of thousands of words for me before I start to notice any small omissions or confabulations, and this was confabulating all that at just 1.5k words?

So since he says he was sick and his recollection cannot be trusted (I don't blame him, the second-to-last time I had COVID-19, I can barely remember anything about the worst day - which was Christmas Day), something seems to be missing. He may not have pasted in the blog post like he remembers. Or perhaps he got routed to a cheap model; it wouldn't surprise me if he was using a free tier, that accounts for a lot of these stories where GPT-5 underperforms and would explain a lot of stupidity by the GPT. Or didn't use GPT at all, who knows.
by cik | 2026-02-16 06:37:53+00:00
This is already how it works today. If there demand curve shows an increase in desire for the same items in another jurisdiction, rather then make more and ship for <x> location, they are reshipped from your geography, even store to store.

Secondly, disposal is one of two things:

1. Donation to a company that collects clothes, who in reality sell these clothes by the tonnage. Most of the clothing recyclers are companies of this nature.

2. Sale at a low value to the company above.
by casualscience | 2026-02-16 06:37:55+00:00
Hmm, whats stopping you from running claude code on a separate machine you can ssh into? I don't understand that point at all, I do that all the time.

Using a claude code instance through a phone app is certainly not something that is easy to do, so if there's like a phone app that makes that easy, I can see that being a big differentiator.
by qingcharles | 2026-02-16 06:38:39+00:00
I know someone who is one of the top-rated voiceover artists on Fiverr. Their voice appeared on a video recently I heard and it was definitely cloned from them (as it was not a project they would have worked on).

It's so easy to do now. You can just grab your favorite voiceover artist's demo reel and clone it from there. The chances of getting caught are slim, and what is the (poorly paid) artist going to do? Most of them will lack the resources to fund a protracted court case to sue some anonymous users in Tajikistan making AI slop videos en masse.
by da_chicken | 2026-02-16 06:38:55+00:00
Yeah, this seemed like a very long way to say, "Our RDBMS has system catalogs," as if it's 1987.

But then, they're also doing JOINs with the USING clause, which seems like one of those things that everybody tries... until they hit one of the several reasons not to use them, and then they go back to the ON clause which is explicit and concrete and works great in all cases.

Personally, I'd like to hear more about the claims made about Snowflake IDs.
by Etheryte | 2026-02-16 06:40:13+00:00
I think motivation really is the key term here. Magnus is a five-time world chess champion, in a complete league of his own even when everyone else was literally only prepping to defeat him. He held the world champion title for ten years and eventually just declined to defend it. And that's relatable, if you're at the absolute top for ten years and no one manages to put a dent to it, what else is there? I think most people would look for new challenges and ways to fulfill themselves after that.
Show HN: AI learning paths with YouTube playlists
by strewberry | 2026-02-16 06:40:24+00:00
Enter any topic and the app generates a structured study path — chapters, steps, and YouTube tutorials for each. You can explore it as an interactive knowledge graph or a step-by-step plan,
and export the tutorials into a YouTube playlist with one click.

No sign-up required to try it.

Stack: Python/FastAPI, OpenAI Responses API (streaming), Cytoscape.js for the graph, vanilla JS, Cloud Run.

Demo: https://www.youtube.com/watch?v=b4hUfTcJdbQ
by vasco | 2026-02-16 06:41:01+00:00
When a chess player means "no prep" it probably still means more prep than any normal person would consider reasonable, because what would require you to sit down and take notes, move pieces and memorize, they can just do in their head getting coffee by now. So yeah they recognize almost all the patterns, it's just harder justify spending 1 month on an opening you won't even be able to use, but they still know how to play certain patterns.
by da_chicken | 2026-02-16 06:41:45+00:00
That's quite expensive. Most systems that need this sort of data will instead implement some form of audit log or audit table. Which is still quite expensive.

At the record level, I've seldom seen more than an add timestamp, and add user id, a last change timestamp, and a last change user id. Even then, it covers any change to the whole row, not every field. It's still relatively expensive.
by globular-toast | 2026-02-16 06:42:35+00:00
> Most houses weren’t equipped with AC when they were built because it was rarely needed. Now it’s a must for between good third and half of the summer

This is something that's scared me ever since I learnt about air conditioning and how it works in the 90s when I was like 10.

Air con heats up the outside, so air cons are fighting with each other to cool down their respective buildings. So, more air con, using even more power, all heating up the outside a little bit more. The snowball effect is going to be enormous.

I guess I thought as a 10 year old that some adults would have this under control. Or maybe I realised, even back then, that the only thing really separating adults from children is big bodies and that you don't get told off for being greedy any more.
by Steegi | 2026-02-16 06:42:49+00:00
I've been implementing these trust boundaries for the last several months. Here's what breaks in practice and what held up.

The five patterns come from an actual runtime and governance system we're building at Lambda-Phi (Argos for the execution layer, Daedalus for orchestration). We tried the naive model first. It failed in the same ways OpenClaw is failing publicly.

A few things I want to preempt:

"Allowlists are brittle." Agreed. That's why command gating is one layer in a stack, not the whole answer. The broker, workspace isolation, and trace logging all exist because no single layer is sufficient. Defense in depth is not a new idea. It's under-applied in agent runtimes.

"Your broker can still be manipulated." Also true. The broker accepts only typed actions with a fixed schema (not free-form instructions), uses exec-style invocation (no sh -c), enforces per-integration scoping (audience, workspace, rate, cost), never returns secrets in responses, and emits audit events for every action. It's not magic. It's a trust boundary that reduces the blast radius of model compromise. If your alternative is "give the model the API key directly," the broker is strictly better.

"Why not just use VMs?" VMs are fine. The invariant is: scoped workspace + controlled egress + policy-gated side effects. The isolation tech matters less than whether you enforce those properties. Containers, VMs, or hardware isolation all work if the boundaries are real.

"Default bind is loopback, not 0.0.0.0." Correct. The article's hardening section reflects this. Many incidents come from widening the bind, port-forwarding, or deploying on a VPS without a firewall. Default-safe configs don't help if you deploy them unsafely.

The threat model template and command-gating policy starter I mention at the end are drafts I'm happy to share. If they help you build better agent infra on your own, that's a good outcome.

Happy to go deep on threat model boundaries and failure modes. I'm not going to debate OpenClaw drama.
I built a tool to find users on Reddit. It found me 40 users in a week
by timjayas | 2026-02-16 06:43:36+00:00
I was spending 3 hours every day manually searching Reddit for people asking about problems my SaaS solves.

The process sucked:

Click through 50+ threads
Read hundreds of comments
Find maybe 5 good opportunities
Miss everything posted after I stopped searching

So I built an AI that does it for me in 20 minutes.
How it works:
You give it your website. Then it monitors 24/7, scores every conversation for buying intent, and emails you the best opportunities each morning.
It also does a power scan which finds you high google ranking post

First week results:
50+ relevant conversations found
40+ users
$350 revenue
Just 20 minutes a day

The controversial part:
Before anyone says "you're ruining Reddit" this isn't a spam bot. It finds opportunities. It generates AI replies but you still need to be helpful and authentic. It just saves you from manually reading 1000+ posts to find 5 good ones.

Technical challenges:
Reddit's API is deliberately limited (they want ad revenue). So I index public posts, use LLMs for intent detection and built roadmap that guides you so you don't spam yourself into a shadowban.
You can get the 3-day free trial on RedLeads.app

Happy to answer questions about the AI scoring, Reddit's quirks, or growth tactics.
by jrowen | 2026-02-16 06:44:04+00:00
It's telling me that I should rather focus on getting viral/lucky to get a shot at "success". Maybe I should network better to get "successful". I shouldn't be focusing on writing good code or good enough agents.

All of this is true and none of it is new. If your primary goal is to make lots of money then yes you should do exactly that. If you want to be a craftsman then you'll have to accept a more modest fortune and stop looking at the relative handful of growth hacker exits.
by fourthrigbt | 2026-02-16 06:44:17+00:00
Doesn’t sound like you paid all that much attention when learning ML. The curse of dimensionality doesn’t say that every problem has
some ideal model size, it says that the amount of data needed to train scales with the size of the feature space.
So if you take an LLM, you can make the network much larger but if you don’t increase the size of the input token vocabulary you aren’t even subject to the curse of dimensionality.
Beyond that, there’s a principle in ML theory that says larger models are almost always better because the number of params in the model is the dimensionality of the space in which you’re running gradient descent and with every added dimension, local optima become rarer.
by jiggawatts | 2026-02-16 06:44:33+00:00
That too! It's pretty obvious that he's being taken advantage of by everyone he meets. If this was happening to some kindly grandpa in an old folks home, you'd call it elder abuse.

It was most obvious with the $10 trillion Ukraine minerals deal, which was nonsense cooked up by a senator to "sell" Trump on the merits of allying with Ukraine long-term.

Russia tried this approach too. Their offer is $12 trillion dollars -- of course it's more than what Ukraine supposedly had on the table -- a laughable amount considering their entire GDP is only $2 trillion! Even if they gave the USA something crazy like 10% of their gross domestic production (most of which is not exportable!) this would take 60 years of ruinous payments.

You can only throw a number like this at someone if you're absolutely certain that they're totally innumerate and won't laugh in your face.

Think about the second-order implications of this: multiple people in the Whitehouse or Congress are confident in their knowledge that Trump can't tell the difference between a billion and a trillion, and/or has no idea about the size of another country's economy.[1]

Just to clarify: This is not "my opinion" about his numeracy, or lack thereof! This is the opinion of multiple senior staff who have his ear.

[1] Think back to my point about Trump's world view being "dated" to the 1970s and 80s: Back then, Russia's GDP was on par with the United States -- they were roughly equal superpowers! That's where he gets his intuition from, his ballpark numbers, relative strength, etc... THAT is why he treats Putin as an equal instead of a tinpot dictator that just happens to have nukes.
by wavemode | 2026-02-16 06:44:42+00:00
> expert opinions can be the slowest to update on the news that their specific domain may have, in hindsight, have been the wrong horse. It's the quote about it being difficult to believe something that your income requires to be false, but instead of income it can be your whole legacy or self concept

Not sure I follow. Are you saying that AI researchers would be out of a job if scaling up transformers leads to AGI? How? Or am I misunderstanding your point.
by hackyhacky | 2026-02-16 06:45:59+00:00
> It took one September.

It's the classic "slowly, then suddenly" paradigm. It took decades to get to that one September. Then years more before we all had internet in our pocket.

> The reason the internet became so accessible is because Moore was generally correct.

Can you explain how Moore's law is relevant to the rise of the internet? People didn't start buying couches online because their home computer lacked sufficient compute power.

> I see no advances in LLMs that suggest any form of the same exponential processes exist.

LLMs have seen enormous growth in power over the last 3 years. Nothing else comes close. I think they'll continue to get better, but critically: even if LLMs stay exactly as powerful as they are today, it's enough to disrupt society. IMHO we're already at AGI.

> The difference is companies fought _against_ the internet

Some did, some didn't. As in any cultural shift, there were winners and losers. In this shift, too, there will be winner and losers. The panicked spending on data centers right now is a symptom of the desire to be on the right side of that.

> because companies do not want to pay fair value for labor.

Companies have never wanted to pay fair value for labor. That's a fundamental attribute of companies, arising as a consequence of the system of incentives provided in capitalism. In the past, there have been opportunities for labor to fight back: government regulation, unions. This time that won't help.

> If I'm wrong I can learn how to write prompts in a week.

Why would you think that anyone would want you to write prompts?
by menaerus | 2026-02-16 06:46:09+00:00
> So at inference time, it does not “learn” in the training sense

It learns because it remembers the context. The larger the context, the better the capabilities of the model are. I mean just give it a try and see for yourself - start building a feature, then next feature, then the next one etc. Do it in the same "workspace" or "session" and after few days, one or two weeks of writing code with the agent, you will notice that it somehow magically remembers the stuff and builds upon that context. It becomes slower too.

"Re-learning" is something different and it may not be even needed.
by hi_hi | 2026-02-16 06:46:28+00:00
Going from punch cards to terminals also "completely changed my life and the way I write code and run my business"

Firefox introducing their dev debugger many years ago "completely changed my life and the way I write code and run my business"

You get the idea. Yes, the day to day job of software engineering has changed. The world at large cares not one jot.
by bogtap82 | 2026-02-16 06:47:22+00:00
It was renamed many times. It was also called "clawdis" at one point, and prior to that "warelay," when it was simply a Whatsapp gateway for Claude Code. It was already gaining some momentum at that point but wouldn't reflect as search results for "Clawdbot," and especially wouldn't be visible on Google Trends when most of the conversation was on X/Github.
by alexhans | 2026-02-16 06:47:52+00:00
Git is a beautiful piece of software but it does expose complexity in a very by programmers for programmers kind of way.

I've successfully gotten many non tech roles to use git but there's usually a lot missed in the nuances and power that is in their reach, but not quite adopted.

The learn git branching site/game [1] has always been an awesome resource but you'd like something like that UX be almost part of the initial usage. Intuitive defaults, progressive learning at the right times, etc.

Nowadays, if you can get your users to use an agent CLI like Claude/Codex/OpenCode then it's easier to have that last experience but the more git itself uses accesible abstractions the easier it should be.

[1] - https://learngitbranching.js.org/?locale=en_US
by hysan | 2026-02-16 06:48:11+00:00
While I commend Ars and the author for taking responsibility, I am a bit off put by the wording used for the retraction on the original article: https://arstechnica.com/ai/2026/02/after-a-routine-code-reje...

> Following additional review, Ars has determined that the story “After a routine code rejection, an AI agent published a hit piece on someone by name,” did not meet our standards. Ars Technica has retracted this article. Originally published on Feb 13, 2026 at 2:40PM EST and removed on Feb 13, 2026 at 4:22PM EST.

Rather than say “did not meet our standards,” I’d much prefer if they stated what was false - that they published false, AI generated quotes. Anyone who previously read the article (which realistically are the only people who would return to the article) and might want to go back to it as a reference isn’t going to have their knowledge corrected of the falsehoods that they read.
by adw | 2026-02-16 06:48:39+00:00
Top players who stay active tend to stay above 2600 for a long time. Short was continually active and while not at his peak was in the top 100 well into his fifties. Mickey Adams is still in the top 100 at 54. Korchnoi was world class into his 70s. Vasyl Ivanchuk, at 56, nearly won Tata Steel Challengers. If a player falls off hard in their fifties it’s generally in part “not wanting to try as hard”.