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Scientists Find a 'Ghostly Green' Star, and That's Not the Only Crazy Color

https://www.cnet.com/science/space/white-dwarf-star-color-variability/
1•rbanffy•2m ago•0 comments

Atom Echo on your own ESPHome build: push to talk, a doorbell, no internet

https://blog.jacq.cc/guides/atom-echo-own-firmware/
1•xx__yy•2m ago•0 comments

How AI is creating a lopsided US economy

https://www.abc.net.au/news/2026-10-19/ai-stock-market-concentration-data/107261078
1•tys-•2m ago•0 comments

Show HN: CanaryGuard – A <0.1ms deterministic AI prompt firewall with $5 bounty

https://canaryguard-402.onrender.com/bounty.html
1•kurox_real•3m ago•0 comments

Documents: Police officer gave her Flock login to her ICE agent husband

https://www.wjcl.com/article/savannah-police-officer-ice-agent-flock-access/74135816
1•DeepLogin•4m ago•0 comments

The Weak Points in AI Bonds Are Becoming Clearer

https://www.wsj.com/finance/investing/the-weak-points-in-ai-bonds-are-becoming-clearer-12f09cc6
1•AnodicElegy•7m ago•0 comments

I have a thing for fast trains

https://chrispattle.com/blog/i-have-a-thing-for-fast-trains
1•pattle•9m ago•0 comments

Celebrating 35 Years of Linux: The Open Source Engine Powering Global Innovation

https://www.linuxfoundation.org/blog/celebrating-35-years-of-linux-the-open-source-engine-powerin...
1•theanonymousone•9m ago•0 comments

Training a Chess Reasoning Agent

https://blog.lukesalamone.com/posts/chess-reasoning-llm/
1•alexmolas•10m ago•0 comments

What's on That Access Port?

https://danielmangum.com/posts/whats-on-that-access-port/
1•hasheddan•13m ago•1 comments

Speeding up code review with `small-change`

https://lethain.com/small-changes/
1•alexmolas•14m ago•0 comments

Russian milsat closes from 200 miles to 3 miles of US satellite aiding Ukraine

https://www.tomshardware.com/tech-industry/space/russian-military-satellite-closes-from-200-miles...
1•NordStreamYacht•15m ago•0 comments

Show HN: Tailgate – easy self hosted Tailscale

https://tailgate.latchlabs.dev/
1•redmalang•19m ago•0 comments

A detailed look at the Sally Rooney and the Faber book withdrawal

https://emptycity.substack.com/p/a-detailed-look-at-the-sally-rooney
1•AndrewDucker•19m ago•0 comments

Do You Trust Apple?

https://stratechery.com/2026/do-you-trust-apple/
1•swolpers•20m ago•1 comments

Gnome OS Preview – Adrian's Blog

https://blogs.gnome.org/adrianvovk/2026/10/16/gnome-os-preview/
1•rbanffy•21m ago•0 comments

Rebuilding the API edge for AI Agents

https://engineering.monday.com/rebuilding-monday-api-edge-for-agents/
1•michalbu•21m ago•0 comments

How to download Claude artifacts as PDF [video]

https://www.youtube.com/watch?v=otUsURxeG4Q
2•quysala12•21m ago•0 comments

Show HN: Instant MS Access data on the Web [video]

https://www.youtube.com/watch?v=wR-50zZNG6s
1•msaccess•25m ago•0 comments

Show HN: Gsearch – Real Google Search for AI Agents, via a Real Firefox (MCP)

https://github.com/RayenMlayeh/gsearch
1•rayenmlayeh•32m ago•0 comments

Mastodon 5.0: A Closer Look

https://blog.joinmastodon.org/2026/10/5.0-a-closer-look/
3•robin_reala•33m ago•0 comments

1-Click Remote Code Execution in Discord via Twitch Embed

https://bugcrowd.com/disclosures/63864b55-10d6-4e82-a619-192b8c0c99ad/1-click-remote-code-executi...
1•joshcsimmons•33m ago•0 comments

vLLM Agentic API

https://vllm-project.github.io/agentic-api/
1•ggcr•38m ago•0 comments

Meta's Algorithms Under Scrutiny

https://www.analyticsinsight.net/news/metas-algorithms-under-scrutiny-what-is-meity-asking
3•rustoo•40m ago•0 comments

The Photoshop clone that hurts GIMP

https://en.andros.dev/blog/b31f82ad/the-photoshop-clone-that-hurts-gimp/
3•andros•43m ago•2 comments

Is This the First Time Anyone Printed, 'Garbage In, Garbage Out'? (2016)

https://www.atlasobscura.com/articles/is-this-the-first-time-anyone-printed-garbage-in-garbage-out
1•SerCe•49m ago•1 comments

Timestral: Mistral release time-series foundation models

https://mistral.ai/news/timestral/
3•groar•50m ago•0 comments

I Teach at a Business School. It's Time to Shut Them Down

https://www.nytimes.com/2026/10/18/opinion/business-school-mba-harvard-cornell-cambridge.html
1•dkobia•51m ago•0 comments

Possible wreckage of Amelia Earhart's plane likely to be trees, say researchers

https://www.bbc.com/news/articles/cmq5n8x106jdo
2•sohkamyung•57m ago•0 comments

Deploy a Django app with PostgreSQL for free, with VS Code in the browser

https://portal.uppcoder.com/guides/deploy-django-postgresql
1•johnwebsson-doo•58m 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.