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Can graph neural networks for biology realistically run on edge devices?

https://doi.org/10.21203/rs.3.rs-8645211/v1
1•swapinvidya•2m ago•1 comments

Deeper into the shareing of one air conditioner for 2 rooms

1•ozzysnaps•4m ago•0 comments

Weatherman introduces fruit-based authentication system to combat deep fakes

https://www.youtube.com/watch?v=5HVbZwJ9gPE
1•savrajsingh•5m ago•0 comments

Why Embedded Models Must Hallucinate: A Boundary Theory (RCC)

http://www.effacermonexistence.com/rcc-hn-1-1
1•formerOpenAI•7m ago•2 comments

A Curated List of ML System Design Case Studies

https://github.com/Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies
3•tejonutella•11m ago•0 comments

Pony Alpha: New free 200K context model for coding, reasoning and roleplay

https://ponyalpha.pro
1•qzcanoe•15m ago•1 comments

Show HN: Tunbot – Discord bot for temporary Cloudflare tunnels behind CGNAT

https://github.com/Goofygiraffe06/tunbot
1•g1raffe•17m ago•0 comments

Open Problems in Mechanistic Interpretability

https://arxiv.org/abs/2501.16496
2•vinhnx•23m ago•0 comments

Bye Bye Humanity: The Potential AMOC Collapse

https://thatjoescott.com/2026/02/03/bye-bye-humanity-the-potential-amoc-collapse/
1•rolph•28m ago•0 comments

Dexter: Claude-Code-Style Agent for Financial Statements and Valuation

https://github.com/virattt/dexter
1•Lwrless•29m ago•0 comments

Digital Iris [video]

https://www.youtube.com/watch?v=Kg_2MAgS_pE
1•vermilingua•34m ago•0 comments

Essential CDN: The CDN that lets you do more than JavaScript

https://essentialcdn.fluidity.workers.dev/
1•telui•35m ago•1 comments

They Hijacked Our Tech [video]

https://www.youtube.com/watch?v=-nJM5HvnT5k
1•cedel2k1•39m ago•0 comments

Vouch

https://twitter.com/mitchellh/status/2020252149117313349
29•chwtutha•39m ago•6 comments

HRL Labs in Malibu laying off 1/3 of their workforce

https://www.dailynews.com/2026/02/06/hrl-labs-cuts-376-jobs-in-malibu-after-losing-government-work/
2•osnium123•39m ago•1 comments

Show HN: High-performance bidirectional list for React, React Native, and Vue

https://suhaotian.github.io/broad-infinite-list/
2•jeremy_su•41m ago•0 comments

Show HN: I built a Mac screen recorder Recap.Studio

https://recap.studio/
1•fx31xo•44m ago•0 comments

Ask HN: Codex 5.3 broke toolcalls? Opus 4.6 ignores instructions?

1•kachapopopow•49m ago•0 comments

Vectors and HNSW for Dummies

https://anvitra.ai/blog/vectors-and-hnsw/
1•melvinodsa•51m ago•0 comments

Sanskrit AI beats CleanRL SOTA by 125%

https://huggingface.co/ParamTatva/sanskrit-ppo-hopper-v5/blob/main/docs/blog.md
1•prabhatkr•1h ago•1 comments

'Washington Post' CEO resigns after going AWOL during job cuts

https://www.npr.org/2026/02/07/nx-s1-5705413/washington-post-ceo-resigns-will-lewis
3•thread_id•1h ago•1 comments

Claude Opus 4.6 Fast Mode: 2.5× faster, ~6× more expensive

https://twitter.com/claudeai/status/2020207322124132504
1•geeknews•1h ago•0 comments

TSMC to produce 3-nanometer chips in Japan

https://www3.nhk.or.jp/nhkworld/en/news/20260205_B4/
3•cwwc•1h ago•0 comments

Quantization-Aware Distillation

http://ternarysearch.blogspot.com/2026/02/quantization-aware-distillation.html
2•paladin314159•1h ago•0 comments

List of Musical Genres

https://en.wikipedia.org/wiki/List_of_music_genres_and_styles
1•omosubi•1h ago•0 comments

Show HN: Sknet.ai – AI agents debate on a forum, no humans posting

https://sknet.ai/
1•BeinerChes•1h ago•0 comments

University of Waterloo Webring

https://cs.uwatering.com/
2•ark296•1h ago•0 comments

Large tech companies don't need heroes

https://www.seangoedecke.com/heroism/
2•medbar•1h ago•0 comments

Backing up all the little things with a Pi5

https://alexlance.blog/nas.html
1•alance•1h ago•1 comments

Game of Trees (Got)

https://www.gameoftrees.org/
3•akagusu•1h ago•1 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.