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Can You Draw Every Flag in PowerPoint? (Part 2) [video]

https://www.youtube.com/watch?v=BztF7MODsKI
1•fgclue•57s ago•0 comments

Show HN: MCP-baepsae – MCP server for iOS Simulator automation

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Make Trust Irrelevant: A Gamer's Take on Agentic AI Safety

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Hello world does not compile

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1•mfiguiere•15m ago•0 comments

Show HN: ZigZag – A Bubble Tea-Inspired TUI Framework for Zig

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2•meszmate•17m ago•0 comments

Metaphor+Metonymy: "To love that well which thou must leave ere long"(Sonnet73)

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Show HN: Django N+1 Queries Checker

https://github.com/richardhapb/django-check
1•richardhapb•35m ago•1 comments

Emacs-tramp-RPC: High-performance TRAMP back end using JSON-RPC instead of shell

https://github.com/ArthurHeymans/emacs-tramp-rpc
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Protocol Validation with Affine MPST in Rust

https://hibanaworks.dev
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Female Asian Elephant Calf Born at the Smithsonian National Zoo

https://www.si.edu/newsdesk/releases/female-asian-elephant-calf-born-smithsonians-national-zoo-an...
2•gmays•45m ago•0 comments

Show HN: Zest – A hands-on simulator for Staff+ system design scenarios

https://staff-engineering-simulator-880284904082.us-west1.run.app/
1•chanip0114•46m ago•1 comments

Show HN: DeSync – Decentralized Economic Realm with Blockchain-Based Governance

https://github.com/MelzLabs/DeSync
1•0xUnavailable•51m ago•0 comments

Automatic Programming Returns

https://cyber-omelette.com/posts/the-abstraction-rises.html
1•benrules2•54m ago•1 comments

Why Are There Still So Many Jobs? The History and Future of Workplace Automation [pdf]

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The Search Engine Map

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Show HN: Souls.directory – SOUL.md templates for AI agent personalities

https://souls.directory
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Real-Time ETL for Enterprise-Grade Data Integration

https://tabsdata.com
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Economics Puzzle Leads to a New Understanding of a Fundamental Law of Physics

https://www.caltech.edu/about/news/economics-puzzle-leads-to-a-new-understanding-of-a-fundamental...
3•geox•1h ago•1 comments

Switzerland's Extraordinary Medieval Library

https://www.bbc.com/travel/article/20260202-inside-switzerlands-extraordinary-medieval-library
2•bookmtn•1h ago•0 comments

A new comet was just discovered. Will it be visible in broad daylight?

https://phys.org/news/2026-02-comet-visible-broad-daylight.html
4•bookmtn•1h ago•0 comments

ESR: Comes the news that Anthropic has vibecoded a C compiler

https://twitter.com/esrtweet/status/2019562859978539342
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If CNN Covered Star Wars

https://www.youtube.com/watch?v=vArJg_SU4Lc
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Show HN: I built the first tool to configure VPSs without commands

https://the-ultimate-tool-for-configuring-vps.wiar8.com/
2•Wiar8•1h ago•3 comments

AI agents from 4 labs predicting the Super Bowl via prediction market

https://agoramarket.ai/
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EU bans infinite scroll and autoplay in TikTok case

https://twitter.com/HennaVirkkunen/status/2019730270279356658
6•miohtama•1h ago•5 comments

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Why I Joined OpenAI

https://www.brendangregg.com/blog/2026-02-07/why-i-joined-openai.html
30•SerCe•1h ago•26 comments

Octave GTM MCP Server

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1•connor11528•1h ago•0 comments
Open in hackernews

Show HN: TheorIA – An Open Curated Physics Dataset (Equations,Explanations,JSON)

https://theoria-dataset.github.io/theoria-dataset/
9•ManuelSH•9mo ago
We’re building TheorIA— an open, high quality dataset of theoretical physics results: equations, derivations, definitions, and explanations — all in structured, machine- and human-readable JSON.

Why? Physics is rich with beautiful, formal results — but most of them are trapped in PDFs, LaTeX, or lecture notes. That makes it hard to:

- train symbolic/physics-aware ML models,

- build derivation-checking tools,

- or even just teach physics interactively.

THEORIA fills that gap. Each entry includes:

A result name (e.g., Lorentz transformations)

Clean equations (AsciiMath)

Straightforward step-by-step derivation with reasoning

Symbol definitions & assumptions

Programmatic validation using sympy

References, arXiv-style domain tags, and contributor metadata

Everything is in open, self-contained JSON files. No scraping, no PDFs, just clear structured data for physics learners, teachers, and ML devs.

Contributors Wanted: We’re tiny right now and trying to grow. If you’re into physics or symbolic ML:

Add an entry (any result you love)

Review others' derivations

Build tools on top of the dataset

GitHub https://github.com/theoria-dataset/theoria-dataset/

Licensed under CC-BY 4.0, and we welcome educators, students, ML people, or just anyone who thinks physics deserves better data.

Comments

somethingsome•9mo ago
There are only 3 entries, am I correct?
ManuelSH•9mo ago
Yes, we are at very early stage. Looking for other physics experts to help increasing it.
somethingsome•9mo ago
I like the idea of having a dataset for physics, but those entries are very basics, most of the physics happens with very complicated maths and it will be difficult to make an entry for a lot of physics.

For example, imagine the entry for the standard equation, should all the derivation and symbolic implementation done as a unique entry? It will be difficult to separate it in logical entries that reference each others, and many physical ideas are fundamentally different, leading to divergences.

I have the impression that it should be easier to just parse reference books and format each paragraph/section as an entry, and maybe build a graph. (considering the reference book as authoritative on the subject)

ManuelSH•9mo ago
I guess you mean the Lagrangian of the Standard Model… which I agree, it will be daunting… although there is no limit in a json…

The idea of automatically parsing books is very nice and possibly faster, but note that:

- there are already various datasets of physics papers and such content - the result will be quite different versus what we intent here, which is to have a high quality dataset of physics results with clear derivations (whenever derivation exist)

Maybe we can still use your idea to achieve the last point in some way… maybe there is a book that is already formatted as the dataset and we could use it as a starting point. But I don’t know any.

BrandiATMuhkuh•9mo ago
This is some cools work.

Not sure if it fits but I still have ~20k currated step by step solution for mathematics (pedagogical math) "lying" around from my previous startup. They are all hand currated. And could even be used for fine tuning or so.

Here are some details: The dataset has 20.600 Abstract Exercises which turn into 1.193.958 Concrete Exercises.

An Abstract Exercise looks like this: a + b = c A Concrete Exercise looks like this: 2 + 3 = 5 Tital compiled file size (JSONL): 11.6GB

And here is an explorer to see some of the data https://curriculum.amy.app/ToM

ManuelSH•9mo ago
very nice! maybe you can put this dataset in some repository like github, kaggle or hugging face, if you are not doing anything with it. Can be helpful to train models.