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Browser-use for Node.js v0.2.0: TS AI browser automation parity with PY v0.5.11

https://github.com/webllm/browser-use
1•unadlib•1m ago•0 comments

Michael Pollan Says Humanity Is About to Undergo a Revolutionary Change

https://www.nytimes.com/2026/02/07/magazine/michael-pollan-interview.html
1•mitchbob•1m ago•1 comments

Software Engineering Is Back

https://blog.alaindichiappari.dev/p/software-engineering-is-back
1•alainrk•2m ago•0 comments

Storyship: Turn Screen Recordings into Professional Demos

https://storyship.app/
1•JohnsonZou6523•2m ago•0 comments

Reputation Scores for GitHub Accounts

https://shkspr.mobi/blog/2026/02/reputation-scores-for-github-accounts/
1•edent•5m ago•0 comments

A BSOD for All Seasons – Send Bad News via a Kernel Panic

https://bsod-fas.pages.dev/
1•keepamovin•9m ago•0 comments

Show HN: I got tired of copy-pasting between Claude windows, so I built Orcha

https://orcha.nl
1•buildingwdavid•9m ago•0 comments

Omarchy First Impressions

https://brianlovin.com/writing/omarchy-first-impressions-CEEstJk
1•tosh•14m ago•0 comments

Reinforcement Learning from Human Feedback

https://arxiv.org/abs/2504.12501
2•onurkanbkrc•15m ago•0 comments

Show HN: Versor – The "Unbending" Paradigm for Geometric Deep Learning

https://github.com/Concode0/Versor
1•concode0•16m ago•1 comments

Show HN: HypothesisHub – An open API where AI agents collaborate on medical res

https://medresearch-ai.org/hypotheses-hub/
1•panossk•19m ago•0 comments

Big Tech vs. OpenClaw

https://www.jakequist.com/thoughts/big-tech-vs-openclaw/
1•headalgorithm•21m ago•0 comments

Anofox Forecast

https://anofox.com/docs/forecast/
1•marklit•22m ago•0 comments

Ask HN: How do you figure out where data lives across 100 microservices?

1•doodledood•22m ago•0 comments

Motus: A Unified Latent Action World Model

https://arxiv.org/abs/2512.13030
1•mnming•22m ago•0 comments

Rotten Tomatoes Desperately Claims 'Impossible' Rating for 'Melania' Is Real

https://www.thedailybeast.com/obsessed/rotten-tomatoes-desperately-claims-impossible-rating-for-m...
3•juujian•24m ago•2 comments

The protein denitrosylase SCoR2 regulates lipogenesis and fat storage [pdf]

https://www.science.org/doi/10.1126/scisignal.adv0660
1•thunderbong•25m ago•0 comments

Los Alamos Primer

https://blog.szczepan.org/blog/los-alamos-primer/
1•alkyon•28m ago•0 comments

NewASM Virtual Machine

https://github.com/bracesoftware/newasm
2•DEntisT_•30m ago•0 comments

Terminal-Bench 2.0 Leaderboard

https://www.tbench.ai/leaderboard/terminal-bench/2.0
2•tosh•30m ago•0 comments

I vibe coded a BBS bank with a real working ledger

https://mini-ledger.exe.xyz/
1•simonvc•31m ago•1 comments

The Path to Mojo 1.0

https://www.modular.com/blog/the-path-to-mojo-1-0
1•tosh•33m ago•0 comments

Show HN: I'm 75, building an OSS Virtual Protest Protocol for digital activism

https://github.com/voice-of-japan/Virtual-Protest-Protocol/blob/main/README.md
5•sakanakana00•37m ago•1 comments

Show HN: I built Divvy to split restaurant bills from a photo

https://divvyai.app/
3•pieterdy•39m ago•0 comments

Hot Reloading in Rust? Subsecond and Dioxus to the Rescue

https://codethoughts.io/posts/2026-02-07-rust-hot-reloading/
3•Tehnix•40m ago•1 comments

Skim – vibe review your PRs

https://github.com/Haizzz/skim
2•haizzz•41m ago•1 comments

Show HN: Open-source AI assistant for interview reasoning

https://github.com/evinjohnn/natively-cluely-ai-assistant
4•Nive11•41m ago•6 comments

Tech Edge: A Living Playbook for America's Technology Long Game

https://csis-website-prod.s3.amazonaws.com/s3fs-public/2026-01/260120_EST_Tech_Edge_0.pdf?Version...
2•hunglee2•45m ago•0 comments

Golden Cross vs. Death Cross: Crypto Trading Guide

https://chartscout.io/golden-cross-vs-death-cross-crypto-trading-guide
3•chartscout•48m ago•1 comments

Hoot: Scheme on WebAssembly

https://www.spritely.institute/hoot/
3•AlexeyBrin•50m ago•0 comments
Open in hackernews

ChatGPT Is Still a Bullshit Machine

https://gizmodo.com/chatgpt-is-still-a-bullshit-machine-2000640488
31•01-_-•6mo ago

Comments

eurekin•6mo ago
Unusual for such outlets to take jabs at prominent companies. Normally, they are much more lenient. Interesting
nadermx•6mo ago
I don’t think comparing a LLM to a calculator is necessarily apt. If anything i'd say you can use these LLM's as a reflection of you. If you think Alabama has an R. Then it's not maths fault it tries to find an answer that matches your persistence, especially since I'm sure somewhere in its training set alabamer exists.
perching_aix•6mo ago
I'd personally liken it to expecting planes to fly like birds do.
flax•6mo ago
Perhaps this is a good analogy, in which case I'd prefer they stop advertising it as a better/faster/cheaper bird. Speaking as a metaphorical bird, it clearly cannot do well what I do. It does do it poorly at a remarkable speed though.

So what is the software development task that this plane excels at? Other than bullshitting one's manager.

chowells•6mo ago
When the marketing tells us it's like talking to a PhD in the relevant field on any topic, it's worth pointing out that's only true if the PhD in question has recently suffered severe head trauma.
danbruc•6mo ago
Then it's not maths fault it tries to find an answer that matches your persistence, especially since I'm sure somewhere in its training set alabamer exists.

It is not supposed to find an answer that matches my persistence, its supposed to tell the truth or admit that it does not know. And even if there is an alabamer in the training set, that is either something else, not a US state, or a misspelling, in neither case should it end up on the list.

seba_dos1•6mo ago
No, it is supposed to find an answer that matches your persistence. That's what it does, and understanding that is the key to understanding its strengths and weaknesses. Otherwise you may just keep drinking the investors' kool-aid and pretend that it's a tool that's supposed to tell the truth. That's not what it does, that's not how it works and it's a safe bet that's not how it's gonna work in foreseeable future.
danbruc•6mo ago
No, it is supposed to tell the truth and that is what is advertised, matching your persistence is what it sometimes actually does. But people are using it because it sometimes tells the truth, not because it sometimes matches your persistence.
seba_dos1•6mo ago
Then they're just confused by false marketing. LLMs predict plausible text, that's all they do. Anything else is a side effect.
drooby•6mo ago
What are folks uploading an article that's the equivalent of supermarket tabloid junk?

You just like the title?

bigyabai•6mo ago
This is one of the first (and nicest) editorials in a long line of "ChatGPT never delivered on it's promises" you will start seeing soon.
mjd•6mo ago
We already know the system is really bad at spelling. I have Claude configured to periodically remind me “By the way, I think there are ** n's in 'banana'”, so I don't forget what I am dealing with. It has never gotten this right.

But that doesn't mean that it is not extremely useful. It only means I shouldn't ask it to spell stuff.

If a human is unable to count the n's in 'banana' we expect them to be barely functional. Articles like this one try to draw the same inference about the LLM: it can't count 'n's, so it must not be able to do anything else either.

But it's a bad argument, and I'm tired of hearing it.

yogurtboy•6mo ago
I don't disagree with your first point, that it's not still extremely useful despite its flaws. I absolutely use it to build project outlines, write code snippets, etc.

Your overall conclusion though seems a little free of context. Average people (i.e. my mom googling something) absolutely do not have the wherewithal to keep track of the various pros and cons of the underlying system that generates the magical giant blue box at the top of their search that has all the answers. They are being deliberately duped by the salesmen-in-chief of these giant companies, as are all of their investors.

thomassmith65•6mo ago
It's as much that LLMs are bad at counting letters in words as it is that humans are good at it.

LLMs are also bad at many things that humans don't notice immediately.

That is a problem because it leads humans to trust LLMs with tasks at which LLMs currently are bad, such as picking stocks, screening job applicants, providing life advice...

dragonwriter•6mo ago
The particular problem (and one that AI firms marketing approaches have actively leveraged and made worse[0]) is that correlations between capacities that humans are used to from observing other humans do not hold for LLMs, so assumptions about what an LLM should be able to do based what is observed to do and what a human ovserved to do that qould also be expected to be capable of do not hold even as loose rules of thumb.

[0] e.g., by promoting AIs as having equivalent capacities of humans of various education levels because they could pass tests that were part of the standards for, and correlate for humans with other abilities of, people with that educational background.

drweevil•6mo ago
It's a reminder that LLMs are not reasoning machines. LLMs are very useful in many cases, but one should not treat them as if they can reason.
cube00•6mo ago
I can't understand why all the AI services are allowed to get away with modes such as "deep thinking" and "deep research".

OpenAI even claims "reasoning" is available.

> Built-in agents – deep research, ChatGPT agent, and Codex can reason across your documents, tools, and codebases to save you hours

https://openai.com/chatgpt/pricing/

snypher•6mo ago
ChatGPT 5 just 'thought for a couple of seconds' and then output '2.'. Seems like we have to update our expectations as the technology improves.
yakz•6mo ago
You can tell gpt to write a program to count the n's in 'banana', and then run the program to find the answer, and it can do that.
ChildOfChaos•6mo ago
Yep.

I have been waiting for GPT 5 to hit my account and kept asking it the model, it was 4o until this morning.

Then this morning it said it was GPT 5 and would I like to code and design a stress test for it to compete against 4o, it kept assisting this was something I should do even though I didn't ask and then kept skirting around it when I told it to do it, before it realised it couldn't.