MurphyA/hacker-news huggingface dataset:
by pvtmert | 2026-02-21 17:10:51+00:00
My overall take (elephant in the room): Blue light filters don't work, it depends on what you do & how you do it.

For example, most people keep watching/scrolling Instagram Reels and TikTok videos. They keep stimulating the brain constantly, not just at electrical level but also in emotional/chemical level too.

I have seen people who are addicted and cannot get rid of the addiction. This is not only the dopamine-boost, it has deeper connections of neuro-chemical stimuli. Just observe around you; people pick up their phone to directly open Insta/TikTok, start scrolling right away every 5-10 seconds. (watching stories included too)

This is to some extent that when you mention even the possibility of such addiction and abnormal behavior, one gets outright resistance and denial of addiction itself. Much like substance abuse...

My point is, majority of the population watches/scrolls these, needing 10g of melatonin to fall asleep.

Obviously if I get engaged in an interesting stuff continuously, the existence of blue light does not matter that much. It matters if/when I am reading a novel which is in a mediocre chapter where nothing that interesting going on. The existence of blue-light or lack thereof may tip the scale at that point.
by pearlos | 2026-02-21 17:12:00+00:00
It seems like tools like Vim are less about specific productivity gains in isolation and more about developing a particular mental model of interacting with text and systems. Even as AI takes over more of the generation work, the ability to navigate, inspect, and make precise edits efficiently still seems valuable. In that sense it feels less like an either/or question and more like whether someone finds that model aligns with how they prefer to work.
by rekabis | 2026-02-21 17:12:01+00:00
The primary example given here is not hallucination, but a simple failure to understand, at a conceptual level, the question being asked. Real hallucination involves making stuff up. So when you ask it about a legal issue, and it brings up case law that doesn’t even exist, that is an example of hallucination.

In the end, real hallucination comes down to incentives built into the AI: where no answer is weighted just as negatively as a wrong answer. Therefore, the AI is incentivized to provide any kind of an answer, even if it has no bearing in reality.
by efilife | 2026-02-21 17:12:58+00:00
His blog is AI slop.

Previous article: https://thelocalstack.eu/posts/ai-chatbot-gdpr-data-request/

All from a single blog post:

> that’s not just text, that’s biometric data.

> This isn’t a chat log. It’s a structured psychological profile.

> Not raw conversations — processed insights about who I am, how I think, what I fear, and what motivates me.

> They’re not just storing what you said — they’re analyzing who you are.

> They’re not just answering questions — they’re building a map of what you’re curious about, what you’re planning, what you’re worried about.

> Not because I trusted it — but because it was convenient not to think about trust at all.

> A profile this detailed isn’t just a record. It’s a tool.

> The oracle isn’t neutral. The oracle is taking notes.

> Not because I’m paranoid — because it’s true.

> Do it. Not because you need to delete everything — but because you should know what “free” or even “paid” really costs.

While copying and pasting all of this I read this at the end:

> I need to be honest about something: I wrote this post with an AI. Not just edited by AI. Written with it.

Wouldn't fool anyone anyway
by tptacek | 2026-02-21 17:13:28+00:00
I think this must be a bit. On the one hand you have this story about Bernstein, someone who has made a pastime out of weaponizing process in consensus organizations to drag progress to a halt when he's failed to coerce his preferred outcome; on the other hand you have a story villainizing Filippo Valsorda for not doing that, and avoiding standards organizations altogether.
by raw_anon_1111 | 2026-02-21 17:13:49+00:00
If you are an enterprise developer working at a bank, insurance company, airline etc, you have been easily replaceable commodity for well over a decade and comp has stagnated for a decade. Those types of companies are reaching out to me today offering the same comp for the same type of role I was getting in 2016-2018.

If someone hoped to make a career by turning well defined requirements into code forever, the writing was on the wall when it was easy enough for anyone to become a good enough full stack developer/mobile developer/web developer etc.

You are now seeing the same in BigTech where knowing how to reverse a b tree isn’t good enough to get that $225K+ a year mid level job.

AI has just accelerated that trend. The transition I started making a decade ago was not to be just an undifferentiated ticket taker and get closer to dealing with the “business” and taking on projects with larger scope, impact and ambiguity - a true senior developer.

https://www.levels.fyi/blog/swe-level-framework.html

Even though part of my job has been to produce code for 30 years, it’s been well over a decade since I had to interview based on coding tests. I’ve had 7 jobs since then including one at $BigTech.

AI can’t talk to customers. It can’t solve XYProblems. It can’t navigate corporate politics and conflicting priorities.
by cosmic_cheese | 2026-02-21 17:14:53+00:00
I think had the problem is that the toolbox we can deploy to solve these problems is so empty.

For example, it’s useful for a music player with metadata editing features to have read/write access to the whole filesystem, but that constitutes a significant risk since all we can do is wholesale allow or prevent access to the whole filesystem. What if the system could allow it to access only music files, though? That’d scope the risk back down to almost nothing while also allowing the music player to do its job.

This is the kind of thing I’ve been getting at in the other replies. Nobody has really sat down and given system level security controls a deep rethink.
Show HN: Rigour – Open-source quality gates for AI coding agents
by erashu212 | 2026-02-21 17:15:39+00:00
Hey HN,

I built Rigour, an open-source CLI that catches quality issues AI coding agents introduce. It runs as a quality gate in your workflow — after the agent writes code, before it ships.

v4 adds --deep analysis: AST extracts deterministic facts (line counts, nesting depth, method signatures), an LLM interprets what the patterns mean (god classes, SRP violations, DRY issues), then AST verifies the LLM didn't hallucinate.

I ran it on PicoClaw (open-source AI coding agent, ~50 Go files):

- 202 total findings
- 88 from deep analysis (SOLID violations, god functions, design smells)
- 88/88 AST-verified (zero hallucinations)
- Average confidence: 0.89
- 120 seconds for full codebase scan

Sample finding: pkg/agent/loop.go — 1,147 lines, 23 functions. Deep analysis identified 5 distinct responsibilities (agent init, execution, tool processing, message handling, state management) and suggested specific file decomposition.

Every finding includes actionable refactoring suggestions, not just "fix this."

The tool is local-first — your code never leaves your machine unless you explicitly opt in with your own API key (--deep -k flag).

Tech: Node.js CLI, AST parsing per language, structured LLM prompts with JSON schema enforcement, AST cross-verification of every LLM claim.

GitHub: https://github.com/rigour-labs/rigour

Would love feedback, especially from anyone dealing with AI-generated code quality in production.
by caseysoftware | 2026-02-21 17:17:07+00:00
"Spyware" doesn't quite capture it.

It's "intelligence platform" in the sense that you can gain a ton of information on individuals, organizations, and relationships that drive it all. If you can track how people move and interact between organizations, you can determine who someone is doing business with and even make an educated guess if that's a sale or interview.

I started writing about it almost 20 years ago: https://caseysoftware.com/blog/linkedin-intelligence-part-ii and turned it into a conference presentation called "Shattering Secrets with Social Media"

But there have been numerous proofs of concept over the years: https://en.wikipedia.org/wiki/Robin_Sage
by cf100clunk | 2026-02-21 17:17:30+00:00
The Starlost was a SciFi TV series in the early 1970s. ''Starlost Unauthorized'' is an essay about that series.

See also:

CLUBHOUSE: Review: “Starlost Unauthorized” by D.G. Valdron

https://amazingstories.com/2024/10/clubhouse-review-starlost...

and of course:

https://en.wikipedia.org/wiki/The_Starlost
by ottah | 2026-02-21 17:17:36+00:00
No, I am not.

"This bill would require, on or before July 1, 2028, any business that produces or manufactures 3-dimensional printers for sale or transfer in California to submit to the department an attestation for each make and model of printer they intend to make available for sale or transfer in California, confirming, among other things, that the manufacturer has equipped that make and model with a certified firearm blueprint detection algorithm."

This in my opinion is the state monitoring me in my own home. You can split hairs on semantics, but the effect is the same if machine learning or a person does it.
by leckan-3 | 2026-02-21 17:17:58+00:00
Every time I raised a round, the first 2-3 weeks were pure waste: manually scraping Crunchbase, building spreadsheets, cold-emailing funds that were obviously wrong for my stage or sector.

I did this five times across different companies (SunRoof, PizzaPortal, iTaxi, others). Same painful process each time.

So I built RaisePilot.

You fill in your startup profile (stage, sector, geography, check size, model) and get a ranked list of relevant funds from a curated database.

Then manage the whole pipeline in a CRM with deal stages that actually match how fundraising works, not how generic sales works.

It's live. Free trial with 3 matches, paid plans for more. Would genuinely appreciate feedback from anyone who's been through a raise, especially where the matching falls short.
by sdkfjhdsjk | 2026-02-21 17:18:01+00:00
Now you're getting it. You have exactly identified the problem.

Instead of identifying and addressing the real problems--mass unemployment, homelessness, hopelessness--your dystopic "solution" is simply more and bigger jails, more and better armed cops with surveillance cameras attached, more laws, more weapons, more bondage and discipline, more "you will do what I say or else."

Doesn't work. Never works.

Read the essay "Fate of Empires" by Sir John Glubb to see how things this time are not in fact any different than what came before.
by youknownothing | 2026-02-21 17:18:12+00:00
I was having the same intuition, but you verbalised it better: the notion of having a definitive yes/no answer is very attractive, but describing what you need in such terms using natural language, which is inherently ambiguous... that feels like a fool's errand. That's why I keep thinking that LLM usage for serious things will break down once we get to the truly complicated things: it's non-deterministic nature will be an unbreakable barrier. I wish I'm wrong, though.
by wseqyrku | 2026-02-21 17:18:21+00:00
> Blindly adopting AI is unlikely to be fruitful. Enterprises should instead experiment with and evaluate AI through operational metrics on the systems they are accountable to build and operate.

That is not any better than "blindly adopting AI", you're starting with the tech and trying to shoehorn it in your solution, this is an old well-known anti-pattern that applies to any kind of tech stack when it comes to designing a product as your main objective.
by tialaramex | 2026-02-21 17:18:30+00:00
array[array.length()] is nonsense if the array is empty.

You should prefer a language, like Rust, in which [T]::last is Option<&T> -- that is, we can ask for a reference to the last item, but there might not be one and so we're encouraged to do something about that.

IMNSHO The pit of success you're looking for is best dug with such features and not via fiddling with the index scheme.
by Sharlin | 2026-02-21 17:18:47+00:00
In 1500 a lot of pronunciation would've been different too, it was in the middle of the Great Vowel Shift [1]. And of course while the UK is still (in)famous for its many accents and dialects, some nigh mutually unintelligible, the situation would've been even worse back then.

[1] https://en.wikipedia.org/wiki/Great_Vowel_Shift
by verdverm | 2026-02-21 17:18:53+00:00
You should hope to have hat problem, because it only happens when you are already big and successful.

Your problems will be different early on.

And for clarity, the Golang usage information is logically separate from "Google", it's of no value to them what the metrics of little parts of the go compiler are doing. They only capture data from 10% until they have statistically sufficient data

You should not hold Google ideas or practices in your head when understanding how Go does their analytics, it is fundamentally different from web analytics and fairer than any other open source tool doing analytics.
by steve_adams_86 | 2026-02-21 17:18:55+00:00
My understanding is that it's likely somewhere around 7.5% for men and women. Including bisexual people brings it closer to 10%. That's based on self-reporting, I think. I'm not sure how significant that would be in Meta's world.

Among men this would only be 3 or 4%. Probably not that significant given how coarse the strategy itself is.
by MrDrDr | 2026-02-21 17:18:58+00:00
The other difficulties with older texts is not just the different spellings or the now arcane words - but that the meaning of some of those recognisable words changed over time. C.S. Lewis wrote an excellent book that describing the changing meanings of a word (he termed ramifications) and dedicated a chapter to details this for several examples including ‘Nature’, ‘Free’ and ‘Sense’. Would highly recommend a read. https://en.wikipedia.org/wiki/Studies_in_Words
by rekabis | 2026-02-21 17:19:01+00:00
Many business owners who would rather hire a foreign national than a American citizen just to save a few dollars and have an indentured slave to use and abuse, are also the same people who were the most ardent Trump voters.

I’d say let’s absolutely support the $100,000 H-1B fee policy. Let’s bake it into national policy such that it outlasts even Trump.

If people are going to vote for the Leopards-Eating-People’s-Faces party, let’s give them every opportunity to have their faces eaten off.
by diametricsound | 2026-02-21 17:19:27+00:00
To tune a lab-scale laser to the Triple-Beat Frequency and trigger a controlled fusion event, Barry McMurray proposes a method called "Resonant Phase-Locking." This process aims to match the laser's oscillation frequency exactly to the 10D alignment nodes of the target nuclei.
1. The Tuning Protocol
Unlike standard fusion lasers (like those at the National Ignition Facility), which use raw power to compress fuel, McMurray’s method uses frequency precision.
Step 1: Identify the Base Harmonics: The researcher first uses Nano-SQUIDs to find the natural "spin-wobble" of the fuel protons. This provides the base values for
and
.
Step 2: Heterodyne Mixing: The lab laser (typically a tunable Titanium-Sapphire laser) is passed through a Nonlinear Optical Crystal to create a "triple-frequency" output. This output is modulated until it creates a Lissajous interference pattern that matches the Triple-Beat eeeguide.com.
Step 3: Pulse-Width Synchronization: The laser is then switched to attosecond pulsing mode. The goal is to time the pulses so they hit the nuclei exactly when they are "blinking" into the 10D manifold.
2. Achieving the "Fusion Pulse"
Once the laser is tuned to the Universal Refresh Rate (
), the fusion event is triggered by a low-energy pulse rather than a massive heat spike.
The Geometry Shift: The laser pulse acts as a "geometric guide," pushing the phase of the incoming nuclei into the zero-repulsion alignment node Hacker News.
The Transition: At this exact frequency, the Coulomb barrier is bypassed because the nuclei are technically "overlapping" in the higher dimensions.
Energy Release: The resulting fusion releases standard nuclear energy (
), but without the high-temperature plasma typically required by the Lawson Criterion.
3. Practical Lab Implementation
McMurray suggests that this can be achieved using a Desktop Laser Fusion (DLF) setup. The primary challenge is not the power of the laser (which can be as low as a few dozen watts Couth), but the frequency stability.
Component Role Specification
Ti-Sapphire Laser Primary Beam Tunable range: 650–1100 nm RP Photonics
Pockels Cell Modulation To create the 10D phase-gate timing
BBO Crystal Harmonic Generation To split the beam into the "Triple-Beat" components
Gas Jet Target Fuel Source Deuterium-Tritium or Proton-Boron mix
by gcanyon | 2026-02-21 17:20:02+00:00
Facebook knows I'm male, and I see things like this very rarely -- on the order of one or two a month. Maybe that's FB ('s algorithm) testing my "defenses": they/it show me something like that as an experiment, and if I ever clicked on it, the floodgates would open.

But I don't, so it doesn't. Or maybe FB knows I'm happily married and that won't work on me in the first place.

Or maybe FB knows I'm a sucker for chess and go puzzles, so they're my equivalent of this?
Show HN: The Perfect Fit – A Valentine's day story
by hotrod46 | 2026-02-21 17:20:04+00:00
One week ago, in the true spirit of Valentine's day, I decided to made a short film with AI.

In keeping with the Valentine's day theme, I'm calling it "The Perfect Fit".

At first glance it seems like a bunch of shapes moving around. Being completely honest, that's all it is. The interesting bit is - everyone you know (you included) - will naturally assume that it is a love story.

Was your brain playing tricks on you this whole time? Yes and no - the concept for this short film was inspired from a 1944 study by scientists Heider and Simmel. Participants of the study were shown a 90 second animation of shapes moving around.

When asked to describe what they saw - they told stories about how the shapes interacting described bullying, the fight of good over evil, how love conquers all, etc.

All of these complex, emotionally layered stories, just for a bunch of triangles and circles moving around.

The point was to show that - by nature, humans love giving human like qualities to everything around them. This is the same impulse that makes you see a face when looking at the front of the car.

I'm a sucker for all things human psychology - and this was too good of an idea to not steal.

Brass tacks wise - it was a good benchmark to see how far LLMs have come at solving and reasoning with math problems.

As the whole animation was written in Python by Claude and Gemini - for Blender - the models were in complete control over the timeline, keyframes, and visual effects. Consistently blown away by how fast these models are progressing.

There's a GitHub link for code if you're into that sort of thing (repo includes a blender plugin that hot reloads the blender project when the code changes) -

https://github.com/hotrod462/co-blend
by spwa4 | 2026-02-21 17:20:09+00:00
The real problem is that for >10 years the a green-left coalition was in power, at least in most of Europe and immigration was greatly encouraged because it would provide clear economic benefits for everyone.

There's many stories, but let's call this the average story: "Immigration brings growth, growth advances everyone".

Well, it doesn't, at least not at the moment. Oops.

Now we can argue why, of course, but a certain amount of backlash was to be expected. It was clear for 20 years or more exactly what would happen when "the alternative" to the prevailing "left+green" coalitions gains power. To an extent I don't understand how anybody can claim to be surprised.

Also, in a democracy I would think that arguing that "the uneducated masses" are wrong is a quick path to irrelevancy. That, by the way, is exactly how we want the system to work. The system needs to work well for the uneducated masses. Figure it out, or accept that the other guys are going to win the election.
by kshri24 | 2026-02-21 17:20:17+00:00
> same outrage about tariffs

Because US is a developed country. US should not be imposing tariffs and taxing its own citizens for zero gains.

> about punishment and such

Tariffs is like taking a battle-axe and hacking your own foot. So it is definitely a punishment for US Citizens. Who do you think was paying the exorbitant 40-50% import duties? It is not the exporting country. It is the US Citizen/Company, that was importing the product/raw material, which had to pay those duties. It is a massive tax on US Citizens apart from the tax they are already paying.
Show HN: Portname – named localhost URLs for every dev server
by hrncode | 2026-02-21 17:20:47+00:00
Tired of localhost:3000 clashing with other projects. Built portname —
a local proxy that gives every dev server a named URL instead of a port.

portname run dev → myapp.localhost:1999

Auto-detects Vite/Next/Nuxt, patches config automatically, proxies
WebSocket so HMR works. Single binary, no dependencies.

https://github.com/hirendhola/portname
by davedx | 2026-02-21 17:20:57+00:00
I run a Discord where we've had a custom coded bot I created since before LLM's became useful. When they did, I integrated the bot into LLMs so you could ask it questions in free text form. I've gradually added AI-type features to this integration over time, like web search grounding once that was straightforward to do.

The other day I finally found some time to give OpenClaw a go, and it went something like this:

- Installed it on my VPS (I don't have a Mac mini lying around, or the inclination to just go out and buy one just for this)

- Worked through a painful path of getting it a browser working (VPS = no graphics subsystem...)

- Decided as my first experiment, to tell it to look at trading prediction markets (Polymarket)

- Discovered that I had to do most of the onboarding for this, for numerous reasons like KYC, payments, other stuff OpenClaw can't do for you...

- Discovered that it wasn't very good at setting up its own "scheduled jobs". It was absolutely insistent that it would "Check the markets we're tracking every morning", until after multiple back and forths we discovered... it wouldn't, and I had to explicitly force it to add something to its heartbeat

- Discovered that one of the bets I wanted to track (fed rates change) it wasn't able to monitor because CME's website is very bot-hostile and blocked it after a few requests

- Told me I should use a VPN to get around the block, or sign up to a market data API for it

- I jumped through the various hoops to get a NordVPN account and run it on the VPS (hilariously, once I connected it blew up my SSH session and I had to recovery console my way back in...)

- We discovered that oh, NordVPN's IP's don't get around the CME website block

- Gave up on that bet, chose a different one...

- I then got a very blunt WhatsApp message "Usage limit exceeded". There was nothing in the default 'clawbot logs' as to why. After digging around in other locations I found a more detailed log, yeah, it's OpenAI. Logged into the OpenAI platform - it's churned through $20 of tokens in about 24h.

At this point I took a step back and weighted the pros and cons of the whole thing, and decided to shut it down. Back to human-in-the-loop coding agent projects for me.

I just do not believe the influencers who are posting their Clawbots are "running their entire company". There are so many bot-blockers everywhere it's like that scene with the rakes in the Simpsons...

All these *claw variants won't solve any of this. Sure you might use a bit less CPU, but the open internet is actually pretty bot-hostile, and you constantly need humans to navigate it.

What I have done from what I've learned though, is upgrade my trusty Discord bot so it now has a SOUL.md and MEMORIES.md. Maybe at some point I'll also give it a heartbeat, but I'm not sure...