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Predicting model behavior before release by simulating deployment

https://openai.com/index/deployment-simulation/
1•0xedb•28s ago•0 comments

The feedback loops behind Kubernetes

https://planetscale.com/blog/the-feedback-loops-behind-kubernetes
1•CSDude•1m ago•0 comments

Hecate, Hardened Osint Platform

https://github.com/synchancybersecurity/Hecate
1•enkimecca•1m ago•0 comments

U.S. pulling ocean sensors a 'shock' for Canadian research as El Niño nears

https://www.timescolonist.com/local-news/us-pulling-ocean-sensors-a-shock-for-canadian-research-a...
1•ResearchAtPlay•2m ago•0 comments

PHP Through a Screen Reader: Small Syntax Choices That Matter

https://thephp.foundation/blog/2026/06/16/php-through-a-screen-reader-small-syntax-choices-that-m...
1•itafroma•2m ago•0 comments

Noctua introduces NL-LC1 all-in-one liquid coolers

https://www.noctua.at/en/news/noctua-introduces-nl-lc1-all-in-one-liquid-coolers
4•georgs_•3m ago•0 comments

Rabbit Hole: The Lorem Ipsum Mystery [video]

https://www.youtube.com/watch?v=kL1PDqzqhM4
1•luizfzs•3m ago•0 comments

Show HN: Next.js boilerplate with Better Auth, PostgreSQL and Shadcn/UI

https://github.com/mmilanovic4/forge
1•mmilanovic4•3m ago•0 comments

Tyler Cowen: A Dangerous Turn in AI Regulation

https://www.thefp.com/p/tyler-cowen-a-dangerous-turn-in-ai
1•paulpauper•4m ago•0 comments

How to Catch a Chess Cheater

https://www.uschess.org/index.php/June/How-To-Catch-A-Chess-Cheater-Ken-Regan-Finds-Moves-Out-Of-...
1•bookofjoe•4m ago•0 comments

Students Are Using a 'Backdoor' to Attend Their Dream Schools

https://www.wsj.com/us-news/education/college-admissions-alternative-enrollment-programs-communit...
1•paulpauper•4m ago•0 comments

Show HN: Ril: a parallel data streaming tool for Python

https://github.com/dannypesic/ril
1•dpesic•4m ago•0 comments

Can Online Activity Be Regulated? Evidence from Adult Websites

https://www.nber.org/papers/w35322
1•paulpauper•4m ago•0 comments

Nobody wants to tell me why they only listen to their own Suno slop

https://www.theverge.com/ai-artificial-intelligence/937059/nobody-wants-to-tell-me-why-they-only-...
1•thebigship•5m ago•0 comments

Claudity

https://danielmay.co.uk/posts/claudity/
1•speckx•5m ago•0 comments

Ask HN: Looking for mobile app ideas with real user demand

3•habeebmd•7m ago•0 comments

AI Consciousness:The Delusionals and the Philosopher's Bench

https://www.avidfayaz.com/writings/delusionals/the-delusionals-and-the-philosophers-bench
4•Avid_F•7m ago•0 comments

Show HN: Write Your GitHub Actions in TypeScript

https://github.com/dedalus-labs/hollywood
2•windsor•7m ago•1 comments

There's more than one way to be a 10x engineer

https://orischwartz.com/posts/theres-more-than-one-way-to-be-a-10x-engineer.html
1•fleaflicker•8m ago•0 comments

The Rivian R2's Radio Needs Cell Signal the Wilderness Doesn't Have

https://www.carscoops.com/2026/06/rivian-r2-fm-radio/
1•MBCook•9m ago•0 comments

Anyone give me a strong mobile app idea

2•habeebmd•9m ago•0 comments

Show HN: Dopamine – An MIT-Licensed Open-Source Cross-Platform Effects Library

https://github.com/10in30/dopamine/
1•jmckenty•9m ago•0 comments

Build your project Zig-style

https://fnordig.de/2026/06/16/build-your-project-zig-style/
1•caleb_thompson•10m ago•0 comments

When Intelligence Gets Cheap, What Becomes Valuable?

https://agonora.com/blog/when-intelligence-gets-cheap
5•mw67•10m ago•1 comments

Snap unveils $2,195 AR glasses as CEO Evan Spiegel bets on post-smartphone futur

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1•mmarian•12m ago•0 comments

Unlocking Extreme AMD Instinct Inference with Software-Hardware Co-Optimization

https://rocm.blogs.amd.com/software-tools-optimization/atom-inference-engine/README.html
1•mooreds•14m ago•0 comments

Prototypes Are Free. Proprietary Data Is Priceless

https://www.kpler.com/blog/data-is-still-king
3•mooreds•14m ago•0 comments

Superpowers 6

https://blog.fsck.com/2026/06/15/Superpowers-6/
2•arittr•15m ago•0 comments

Read the Lutnick Letter That Led Anthropic to Disable Mythos

https://www.bloomberg.com/news/articles/2026-06-16/read-the-lutnick-letter-that-led-anthropic-to-...
3•lesbarclays•16m ago•0 comments

What Is the Return on Tokens?

https://lesbarclays.substack.com/p/what-is-the-return-of-tokens
1•lesbarclays•18m 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.