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A WhatsApp bug lets malicious media files spread through group chats

https://www.malwarebytes.com/blog/news/2026/01/a-whatsapp-bug-lets-malicious-media-files-spread-t...
1•iamnothere•1m ago•0 comments

GitHub Browser Plugin for AI Contribution Blame in Pull Requests

https://blog.rbby.dev/posts/github-ai-contribution-blame-for-pull-requests/
2•rbbydotdev•4m ago•1 comments

Cursor for UI Work

https://kittygiraudel.com/2026/02/03/cursor-for-ui-work/
2•speckx•4m ago•0 comments

Building AIs that do human-like philosophy

https://joecarlsmith.com/2026/01/29/building-ais-that-do-human-like-philosophy/
1•gmays•6m ago•0 comments

China Bans Retractable Door Handles on Cars as Safety Concerns Grow

https://www.wsj.com/business/autos/china-bans-retractable-door-handles-on-cars-as-safety-concerns...
1•impish9208•6m ago•1 comments

Show HN: WebRockets – Rust-powered WebSockets library for Python

https://github.com/ploMP4/webrockets
2•ploMP4•6m ago•0 comments

I Hate Fish

https://randsinrepose.com/archives/i-hate-fish/
2•digitallogic•7m ago•0 comments

Show HN: LLM Shield (Prompt Injection protection for developers)

https://glitchward.com/llm-shield
1•eyeskiller•7m ago•0 comments

China to See Solar Capacity Outstrip Coal Capacity This Year

https://e360.yale.edu/digest/china-solar-coal-2026
3•speckx•9m ago•0 comments

Strategies of cooperation and defection in five large language models

https://arxiv.org/abs/2601.09849
1•PaulHoule•9m ago•0 comments

A discussion about AI consciousness in Reddit

https://old.reddit.com/r/Moltbook/comments/1qutciy/consciousness/
1•yanivleven•9m ago•0 comments

Windows 11 adoption might have flatlined

https://www.windowscentral.com/microsoft/windows-11/windows-11s-growth-has-officially-hit-a-brick...
2•TechSquidTV•11m ago•0 comments

Show HN: Sandboxing untrusted code using WebAssembly

https://github.com/mavdol/capsule
2•mavdol04•11m ago•0 comments

How I fixed a small bug in an app I use daily

https://akshaychugh.xyz/writings/png/instapaper
2•akshay2603•14m ago•0 comments

Show HN: macOS bar for Claude Code skills performance

https://github.com/fernandezbaptiste/trode
3•jorkim32•14m ago•0 comments

Discovery Alert: An Ice-Cold Earth? Science

https://science.nasa.gov/universe/exoplanets/discovery-alert-an-ice-cold-earth/
3•JeanKage•14m ago•0 comments

GitHub: Competitive Intelligence and Monitoring List

https://github.com/Rainmaker-Ventures/awesome-competitive-intelligence-and-monitoring
2•mlukaszczyk•15m ago•1 comments

The Day the Music Died

https://en.wikipedia.org/wiki/The_Day_the_Music_Died
2•edent•16m ago•0 comments

Fungi as a Building Material: Kit Examines Innovative Materials

https://www.kit.edu/kit/english/202601-fungi-as-a-building-material-kit-examines-innovative-mater...
1•JeanKage•16m ago•0 comments

Show HN: govalid – Go validation without reflection (5-44x faster)

https://github.com/sivchari/govalid
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Show HN: Building a AI junior marketing team. tell me why this won't work

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3D-Printed Batteries Put Power in Every Nook and Cranny

https://spectrum.ieee.org/3d-printed-batteries
1•JeanKage•18m ago•0 comments

Floating-point accuracy visualization of Julia math functions

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1•darboux•19m ago•0 comments

Elon Musk joins his rocket and AI businesses into a single company

https://apnews.com/article/spacex-xai-musk-space-2079f03fa888652b7fe836afe8b670a1
1•makerdiety•19m ago•0 comments

Anthropic's Performance Take-Home: A 65x Optimization (For Dummies)

https://www.ikot.blog/anthropic-take-home-for-dummies
5•seeall•20m ago•1 comments

Show HN: EasyClaw – lightweight GUI installer for OpenClaw

https://easyclaw.com
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Cloudflare Is Down

1•ransom1538•21m ago•1 comments

StreetPack – Debut

https://github.com/TrishulaSoftware/StreetPack
1•trishulasoftwre•21m ago•1 comments

The Guardrail Problem

https://www.robpanico.com/articles/display/?entry_short=the-guardrail-problem
1•retrocog•22m 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•8mo 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•8mo ago
There are only 3 entries, am I correct?
ManuelSH•8mo ago
Yes, we are at very early stage. Looking for other physics experts to help increasing it.
somethingsome•8mo 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•8mo 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•8mo 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•8mo 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.