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Loneliness Is for Cowards

https://www.wsj.com/opinion/free-expression/loneliness-is-for-cowards-2c85af34
1•regera•2m ago•0 comments

Winners of the smartphone boom think they know what the next big tech gadget is

https://www.cnn.com/2026/03/02/business/tech-gadgets-smartphone-glasses
1•breve•2m ago•0 comments

Clawed – On Anthropic and the Department of War

https://www.hyperdimensional.co/p/clawed
1•huey77•2m ago•0 comments

Red Hat introduces its first out and out AI platform

https://thenewstack.io/red-hat-introduces-its-first-out-and-out-ai-platform/
1•CrankyBear•3m ago•0 comments

Nodebox, a free open-source Webcontainer alternative

https://scelar.com/blog/introducing-nodepod
1•R1ck404•3m ago•1 comments

Photons that aren't actually there influence superconductivity

https://arstechnica.com/science/2026/02/photons-that-arent-actually-there-influence-superconducti...
1•ViktorRay•4m ago•0 comments

The Case for Apolitical Tech Spaces

https://minor.gripe/posts/2026-03-02-the_case_for_apolitical_tech_spaces/
1•ai_critic•6m ago•0 comments

How long do electric vehicle batteries last?

https://www.npr.org/2026/03/02/nx-s1-5706658/electric-vehicle-battery-lifespan
1•toomuchtodo•7m ago•1 comments

Fix broken link in request-changes blog post using public sample-calculator PR

https://gitauto.ai/blog/how-to-request-changes
1•nishiohiroshi•7m ago•0 comments

How a pacemaker for the brain could help Parkinson’s patients

https://www.cnn.com/health/how-a-pacemaker-for-the-brain-could-help-treat-parkinsons-spc
1•breve•11m ago•0 comments

GH Action analyzes changes, checks behavior change and generates Playwright test

https://github.com/autospec-ai/playwright
1•cport1•13m ago•0 comments

France Floats Nuclear Deployment Across Europe

https://www.wsj.com/world/europe/france-floats-nuclear-deployment-across-europe-056a5cbc
3•JumpCrisscross•14m ago•1 comments

BlackTape – open-source music discovery built on MusicBrainz and Discogs

3•Blacktape•14m ago•0 comments

Crypto Is Pointless. Not Even the White House Can Fix That.

https://www.nytimes.com/2026/02/26/opinion/crypto-trump-bitcoin-clarity-genius.html
4•bookofjoe•15m ago•1 comments

What every CS major should know

https://matt.might.net/articles/what-cs-majors-should-know/
2•azhenley•15m ago•0 comments

Show HN: OctopusGarden – An autonomous software factory (specs in, code out)

https://github.com/foundatron/octopusgarden
3•foundatron•18m ago•1 comments

"Contact sales for complete package dimensions"

https://crackhead.technology/contact-sales-for-dimensions/
2•luu•18m ago•0 comments

Show HN: Pinhead – Adding 2FA to Your CLI (Linux, FreeBSD, OpenBSD, NetBSD)

2•voidbrainvoid•19m ago•0 comments

Recovering from DNS Outages in Distributed Systems

https://singh-sanjay.com/2026/02/18/dns-the-silent-killer-of-distributed-systems.html
2•singhsanjay12•19m ago•3 comments

Netflix's wake-up in Trump's Washington

https://www.politico.com/news/2026/03/02/netflixs-wake-up-in-trumps-washington-00807853
2•petethomas•20m ago•0 comments

Spotify's take on ADRs is great, but how do you enforce them at scale?

5•iamalizaidi•26m ago•0 comments

Lenovo's new AI assistant ad portrays humans as useless

https://www.neowin.net/news/report-lenovos-new-ai-assistant-ad-portrays-humans-as-useless/
1•bundie•27m ago•1 comments

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

https://arxiv.org/abs/2602.24286
2•petethomas•30m ago•0 comments

Ask HN: How did you figure out what research field you were passionate about?

2•aabiji•31m ago•0 comments

Readeck – open-source, self-hosted read-it-later app with full content archiving

https://codeberg.org/readeck/readeck
1•Curiositry•31m ago•0 comments

Show HN: OmniGlass – Executable AI screen snips with kernel-level sandboxing

https://github.com/goshtasb/OmniGlass
1•goshtasb•35m ago•0 comments

AP to provide Kalshi its gold standard elections data ahead of primaries

https://www.ap.org/media-center/press-releases/2026/ap-to-provide-kalshi-its-gold-standard-electi...
1•mikhael•35m ago•2 comments

Show HN: StrategicConsult – Game theory augmented AI for decision making

https://negotiatecash.com/
1•npc0•37m ago•0 comments

Make it Shitty [video]

https://www.youtube.com/watch?v=T4Upf_B9RLQ
1•g0ld3nrati0•39m ago•0 comments

Show HN: BridgeBase – one control plane for TigerBeetle,Redis,MySQL,ClickHouse

https://bridgebase.dev
1•amustaque97•41m 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.