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Call for Interpreters: Translate 39C3

https://events.ccc.de/en/2025/11/24/39c3-call-for-interpreters/
1•doener•29s ago•0 comments

Your brain changes at 9, 32, 66, and 83

https://www.popsci.com/health/brain-changes-aging/
1•geox•5m ago•0 comments

Best GPUs for Deep Learning – The Right 6-Card Comparison

1•EVAN1098•12m ago•0 comments

Best GPUs for Deep Learning – The Right 6-Card Comparison

1•EVAN1098•14m ago•0 comments

HunyuanOCR

https://curateclick.com/blog/hunyuan-ocr-guide
1•czmilo•15m ago•0 comments

Viewing old hintbooks without a red gel viewer

https://boredzo.org/blog/archives/2025-11-24/viewing-old-hintbooks-without-a-red-gel-viewer
1•ingve•16m ago•1 comments

Could Virtual Reality Help Doctors Learn Empathy?

https://nautil.us/could-virtual-reality-help-doctors-learn-empathy-1249812/
2•fleahunter•19m ago•1 comments

Nano Banana Pro Cloud – Free Trial – 20 styles, 500 prompts

https://nanobananapro.cloud
1•paidx•20m ago•1 comments

Malware Hiding in a Fake System32 Directory Using NTFS Trailing-Space Trick

https://medium.com/@omar.k.alsahily/uncovering-a-fake-system32-directory-a-deep-dive-into-ntfs-pa...
1•CriticalLY•20m ago•1 comments

Beyond JSON: Converting Spring AI Tool Response Formats to Toon, XML, CSV, YAML

https://spring.io/blog/2025/11/25/spring-ai-tool-response-formats
1•tsenturk•21m ago•0 comments

Kubernetes Configuration Good Practices

https://kubernetes.io/blog/2025/11/25/configuration-good-practices/
1•clarkmaxwell•22m ago•0 comments

Super fast aggregations in PostgreSQL 19

https://www.cybertec-postgresql.com/en/super-fast-aggregations-in-postgresql-19/
1•clarkmaxwell•23m ago•0 comments

Praise Amazon for raising this service from the dead

https://www.theregister.com/2025/11/24/praise_amazon_for_reviving_codecommit_corey_quinn/
2•LorenDB•30m ago•0 comments

Faciemo

https://faciemo.web.app
2•bogdartysh•32m ago•0 comments

Mae West jailed; court sees trial as vindication of city's morals (1927)

https://nytimes.com/1927/04/20/archives/mae-west-jailed-with-2-producers-leading-lady-in-sex-timo...
2•thomassmith65•32m ago•2 comments

The chemical attack that forced the Northern line's extraordinary repair

https://www.ianvisits.co.uk/articles/the-hidden-chemical-attack-that-forced-the-northern-lines-ex...
1•ianvisits•32m ago•0 comments

Teens Are Saying Tearful Goodbyes to Their AI Companions

https://www.wsj.com/tech/ai/character-ai-teen-access-mental-health-4ec02a43
2•JumpCrisscross•32m ago•0 comments

Ethiopian volcano erupts after 12000 years

https://www.theguardian.com/world/2025/nov/24/ethiopian-volcano-hayli-gubbi-erupts-first-time-120...
3•ls-a•34m ago•0 comments

Aligning VMware migration with business continuity

https://www.technologyreview.com/2025/11/25/1128173/aligning-vmware-migration-with-business-conti...
1•fleahunter•35m ago•0 comments

Everfind helps you find what ever you looking for

https://everfind.ai/
1•ruak83•36m ago•0 comments

Show HN: PassVault – A secure, lightweight, and offline Android password manager

https://github.com/jksalcedo/PassVault
1•jksalcedo•36m ago•0 comments

Show HN: How I think tabs should be managed in a terminal

https://v0.app/chat/iterm-next-demo-gShY36OWRB7
1•novoreorx•39m ago•0 comments

Show HN: Pingora with Edward and Noah from Cloudflare (Netstack.fm Podcast Ep15)

https://netstack.fm/#episode-15
1•gdcbe•39m ago•0 comments

Blogging Gets Serious in 2001 with Warblogs and Movable Type – Cybercultural

https://cybercultural.com/p/blogs-rss-2001/
1•janandonly•42m ago•0 comments

Can We Trust AI as Customer Support?

1•adipm_tech•43m ago•0 comments

'The narwhals stop calling': how noise from ships is silencing wildlife, Arctic

https://www.theguardian.com/environment/2025/nov/25/shipping-noise-arctic-whales-narwhals-sound-q...
1•sipofwater•44m ago•0 comments

Study: The development of carbon-neutral data centres in space [pdf]

https://www3.ntu.edu.sg/CorpComms2/Research%20Papers/Nature%20Electronics_Wen%20Yonggang_Space%20...
2•giuliomagnifico•47m ago•0 comments

The Welch Labs Illustrated Guide to AI

http://www.welchlabs.com/resources/ai-book
1•m-hodges•48m ago•0 comments

Curious gravitational wave may hint at primordial black holes

https://www.science.org/content/article/curious-gravitational-wave-may-be-hint-primordial-black-h...
1•negativelambda•52m ago•0 comments

How the Kreb's cycle powers life and death – Nick Lane [video]

https://www.youtube.com/watch?v=vBiIDwBOqQA
1•zeristor•52m 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•6mo 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•6mo ago
There are only 3 entries, am I correct?
ManuelSH•6mo ago
Yes, we are at very early stage. Looking for other physics experts to help increasing it.
somethingsome•6mo 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•6mo 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•6mo 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•6mo 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.