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OpenDyslexic: A Typeface for Dyslexia

https://opendyslexic.org/
1•molp•43s ago•0 comments

Plotnine: Grammar of Graphics for Python

https://plotnine.org/
1•fanf2•45s ago•0 comments

Wacz-exhibitor – Proxy and wrapper for safely embedding Web Archives

https://github.com/harvard-lil/wacz-exhibitor
1•goodburb•2m ago•0 comments

GPT Image 2 – AI-Powered Image Generation Tool

https://gptimg2ai.net
1•danielmateo773•6m ago•0 comments

Valgrind-3.27.0 Is Available

https://sourceforge.net/p/valgrind/mailman/message/59324626/
1•paulf38•9m ago•0 comments

Crystal Now Has Official Linux ARM64 Builds

https://crystal-lang.org/2026/04/07/official-linux-arm64-builds/
2•TheWiggles•11m ago•0 comments

The AI revolution – spamming 680PRs in 442 GitHub repos in 21 days in April

https://github.com/SAY-5
1•ddorian43•13m ago•1 comments

The first neural interface that transforms your thoughts into text

https://sabi.com/
1•filippofinke•18m ago•0 comments

Indent Is All You Need

https://blog.est.im/2026/stdin-11
1•est•21m ago•0 comments

The arrogant superbanker whose hubris brought Britain to its knees

https://inews.co.uk/opinion/arrogant-superbanker-hubris-brought-britain-knees-4331457
1•robtherobber•22m ago•0 comments

Making the Rails Default Job Queue Fiber-Based

https://paolino.me/solid-queue-doesnt-need-a-thread-per-job/
1•earcar•23m ago•0 comments

The Dirty Little Secret of AI (On a 1979 PDP-11) [video]

https://www.youtube.com/watch?v=OUE3FSIk46g
1•KnuthIsGod•28m ago•0 comments

HappyHorse AI – AI-Powered Equestrian Training

https://www.runhappyhorse.net
1•danielmateo773•29m ago•1 comments

Master of chaos wins $3M math prize for 'blowing up' equations

https://www.scientificamerican.com/article/master-of-chaos-wins-usd3m-math-prize-for-blowing-up-e...
1•signa11•29m ago•0 comments

Why the Original Task Manager Was Under 80K and Insanely Fast [video]

https://www.youtube.com/watch?v=OyN4LGyPwxc
2•KnuthIsGod•29m ago•0 comments

Influencers Are Spinning Nicotine as a 'Natural' Health Hack

https://www.nytimes.com/2026/04/20/well/nicotine-health-maha.html
2•SockThief•30m ago•2 comments

Details that make interfaces feel better

https://jakub.kr/writing/details-that-make-interfaces-feel-better
1•dg-ac•31m ago•0 comments

Watch a 200 Pound, 14" Drive from the 80s Boot Unix [video]

https://www.youtube.com/watch?v=kpC_9EmStAE
1•KnuthIsGod•31m ago•0 comments

My billing system, it could be useful to some

https://github.com/peterretief/billing-v2
2•peter_retief•33m ago•1 comments

ConvertHook – White-label widget that shows where brands rank in ChatGPT

https://converthook.com
1•joefromcomkey•35m ago•0 comments

Palantir manifesto reads like the ramblings of a comic book villain

https://www.engadget.com/big-tech/palantir-posted-a-manifesto-that-reads-like-the-ramblings-of-a-...
1•robtherobber•35m ago•0 comments

SUSE and Nvidia reveal a turnkey AI factory for sovereign enterprise workloads

https://thenewstack.io/suse-nvidia-ai-factory/
1•CrankyBear•35m ago•0 comments

Curlew conservation scheme makes breakthrough in Fermanagh

https://www.rte.ie/news/ireland/2026/0421/1569263-curlew-conservation/
1•austinallegro•36m ago•0 comments

Modern Front end Complexity: essential or accidental?

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Show HN: WeTransfer Alternative for Developers

https://dlvr.sh/
3•mariusbolik•44m ago•0 comments

Keeping code quality high with AI agents

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1•locastica•45m ago•0 comments

The MACL Extended Attribute

https://eclecticlight.co/2026/04/21/the-macl-extended-attribute/
1•frizlab•47m ago•0 comments

Mother Earth Mother Board

https://efdn.notion.site/Mother-Earth-Mother-Board-WIRED-a8ff97e460bc4ac1b4a7b87f3503a55c
1•thunderbong•49m ago•0 comments

US recession probabilities implied by the yield curve

https://www.stlouisfed.org/on-the-economy/2023/sep/what-probability-recession-message-yield-spreads
1•latentframe•54m ago•1 comments

Show HN: AnyHabit – A minimalist habit tracker for Raspberry Pi and Docker

https://github.com/Sparths/AnyHabit
1•bebedi•56m 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•11mo 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•11mo ago
There are only 3 entries, am I correct?
ManuelSH•11mo ago
Yes, we are at very early stage. Looking for other physics experts to help increasing it.
somethingsome•11mo 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•11mo 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•11mo 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•11mo 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.