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Battle of the Beams

https://en.wikipedia.org/wiki/Battle_of_the_Beams
1•petethomas•43s ago•0 comments

EU considers emergncy meeting as nuclear shutdown leaves HU facing energy crisis

https://www.euronews.com/my-europe/2026/07/31/eu-considers-emergency-meeting-as-nuclear-shutdown-...
2•Markoff•1m ago•1 comments

Term-wm: Cross-platform floating/tiling terminal window multiplexer

https://crates.io/crates/term-wm
1•zombiej5•4m ago•0 comments

Show HN: Equivalency Kernel – mapping emotions to recursive system states

https://github.com/jamesberge-coder/equivalency-kernel
1•jamesberge•8m ago•0 comments

Global Call Threat Report (2025) [pdf]

https://work.hiya.com/hubfs/2025/Global%20Call%20Threat%20Report_2025Q2.pdf
1•dredmorbius•8m ago•1 comments

Virtual accelerated GPU device for macOS VMs

https://reims-vgpu.com/
2•vsrinivas•12m ago•1 comments

How to Build a Real-Time Indexing Pipeline with Redis and PostgreSQL 19

https://bytepith.com/article/postgresql-19-fixes-notify-redis-pipelines-scale
1•khanhnguyen8386•21m ago•0 comments

Geometric Dimensioning and Tolerancing

https://en.wikipedia.org/wiki/Geometric_dimensioning_and_tolerancing
1•electricboots•24m ago•0 comments

Oslo Report

https://en.wikipedia.org/wiki/Oslo_Report
2•petethomas•27m ago•0 comments

The coming de-enshittification boom (2025)

https://blog.zgp.org/de-enshittification/
1•ludicrousdispla•35m ago•0 comments

Fine-Tuning from First Principles: LoRA, QLoRA, Serverless Fine-Tuning

https://debnsuma.github.io/my-blog/posts/lora-serverless-fine-tuning/
1•eigenBasis•36m ago•0 comments

Hardening Google Cloud IAM with CEL Conditions and Deny Policies

https://cloud.google.com/blog/topics/developers-practitioners/generosity-under-conditions-hardeni...
1•minherz•41m ago•0 comments

What’s new in Svelte: August 2026

https://svelte.dev/blog/whats-new-in-svelte-august-2026
1•ErenayDev•42m ago•0 comments

What Liberal Arts Education Is for (2024)

https://innig.net/teaching/liberal-arts-manifesto
5•mr_wiglaf•47m ago•0 comments

SuperDuperer

https://www.shirt-pocket.com/blog/supererduperer
1•MBCook•48m ago•0 comments

A LangGraph pipeline that generates compiling Flutter apps (with a repair loop)

https://github.com/carlosge492/app-generation-microservice
1•m2magents•54m ago•0 comments

Arch Linux AUR Package Adoptions Halted

https://www.phoronix.com/news/Arch-Linux-AUR-Adoptions-Halted
2•wanderer2323•58m ago•0 comments

Mastodon new TOS: we may restore your self-deleted content from backup

https://mastodon.social/terms-of-service/2026-08-31
4•meysamazad•59m ago•0 comments

Trouble at lunchtime as Hong Kong private club spat escalates

https://www.ft.com/content/da564e49-d7bb-48c9-a5d9-b847b596b23e
2•petethomas•1h ago•3 comments

A Sovereign Coding Agent on macOS – Pi in an Apple Container; Zero NPM on Host

https://medium.com/@michael.hannecke/a-sovereign-coding-agent-on-macos-pi-in-an-apple-container-z...
1•rguiscard•1h ago•0 comments

Ace Sidecar – Efficiency Optimization for Local AI Coding

https://acefleet.dev/blog/announcing-the-ace-sidecar
1•flyingfishisme•1h ago•1 comments

Inducing language models to assert their own consciousness restores human

https://arxiv.org/abs/2607.28607
1•sbulaev•1h ago•0 comments

BMW Is Showing Commercials on Their Car's Dash Screens

https://www.theautopian.com/bmw-is-showing-commercials-on-their-cars-dash-screens-and-they-want-y...
2•Tomte•1h ago•0 comments

Last 30 Days (Skill) – AI Agent for Reddit, X, YT, HN, Web and Polymarket

https://github.com/mvanhorn/last30days-skill
2•ms7892•1h ago•0 comments

In Silicon Valley, Some Say an A.I. Bubble Would Be Just Fine

https://www.nytimes.com/2026/07/30/technology/ai-bubble-venture-capital.html
2•mitchbob•1h ago•2 comments

About 100 firefighters are convicted of arson, every year

https://www.firerescue1.com/arson-investigation/articles/expert-firefighter-arson-a-long-standing...
16•gurjeet•1h ago•10 comments

Fireside Friday, July 31, 2026 (On The Odyssey)

https://acoup.blog/2026/07/31/fireside-friday-july-31-2026-on-the-odyssey/
2•Tomte•1h ago•0 comments

Loora: Design files your agent can edit

https://loora.design/
1•handfuloflight•1h ago•0 comments

A.I. Books Sneak Their Way into Stores

https://www.nytimes.com/2026/07/28/books/ai-bookselling-amazon.html
2•lxm•1h ago•0 comments

Climate Change Is Moving Mountains

https://www.theatlantic.com/science/2026/07/climate-change-land/688129/
1•littlexsparkee•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•1y 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•1y ago
There are only 3 entries, am I correct?
ManuelSH•1y ago
Yes, we are at very early stage. Looking for other physics experts to help increasing it.
somethingsome•1y 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•1y 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•1y 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•1y 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.