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Mag 7 Senior Software Engineer Pay Distributions

https://old.reddit.com/r/dataisbeautiful/comments/1p48sip/oc_mag_7_senior_software_engineer_total/
1•zuhayeer•47s ago•0 comments

Flavanols in cocoa protect blood vessel function following uninterrupted sitting

https://www.birmingham.ac.uk/news/2025/flavanols-in-cocoa-can-protect-blood-vessel-function-follo...
1•giardini•2m ago•0 comments

A Year Without Caffeine

https://bryanalexander.org/personal/a-year-without-caffeine/
1•andsoitis•2m ago•0 comments

Mastering iOS App Clips and App Clip Experiences for Customer Acquisition

https://medium.com/@gauravharkhani01/mastering-ios-app-clips-f011b0e1e940
1•RyanShook•4m ago•0 comments

Sega Master System: Program Walkthroughs

https://bumbershootsoft.wordpress.com/2025/11/22/sega-master-system-program-walkthroughs/
1•ibobev•4m ago•0 comments

780k Windows users downloaded this Linux distro in a month

https://www.xda-developers.com/780000-windows-users-downloaded-this-linux-distro-in-a-month/
1•giardini•5m ago•0 comments

A monopoly ISP refuses to fix upstream infrastructure

https://sacbear.com/xfinity-wont-fix-internet/
2•vedmed•6m ago•0 comments

Sampling a Disk, Vogel's Method

https://www.4rknova.com//blog/2017/01/01/vogel
1•ibobev•7m ago•0 comments

TRS-80 Breakout.BAS

https://basic-code.bearblog.dev/trs-80-breakout/
1•ibobev•7m ago•0 comments

Fair Screen – Detect Cluely/Interview Coder Kind of Interview Cheating Tools

https://fairscreen.co/
1•anantha2024•11m ago•1 comments

Show HN: Dream Decoder AI – Jungian dream analysis with 3D visualization

1•brandonmillsai•12m ago•0 comments

NTSB report: Decryption of images from the Titan submersible camera [pdf]

https://data.ntsb.gov/Docket/Document/docBLOB?ID=18741602&FileExtension=pdf&FileName=Underwater%2...
1•bmurray7jhu•17m ago•0 comments

Rare earths: Federal backing and tech advances U.S. catch up to China

https://www.npr.org/2025/11/21/nx-s1-5601696/rare-earths-china-trump-pentagon
2•andsoitis•19m ago•0 comments

The corrupt culture of sports gambling

https://www.nationalreview.com/magazine/2026/01/the-corrupt-culture-of-sports-gambling/
1•hhs•21m ago•0 comments

What rituals from the past teach us about panic and anxiety

https://psyche.co/ideas/what-rituals-from-the-past-teach-us-about-panic-and-anxiety
1•herbertl•23m ago•0 comments

What If Aliens Don't Actually Do Science?

https://lithub.com/what-if-aliens-dont-actually-do-science/
2•bookofjoe•27m ago•0 comments

The pedant's progress through history

https://www.spectator.co.uk/article/the-pedants-progress-through-history/
1•hhs•28m ago•0 comments

Mechanical power generation using Earth's ambient radiation

https://news.ycombinator.com/submit
1•worik•28m ago•0 comments

Letting coding agents access runtime output (my current approach)

https://foundinglean.substack.com/p/the-best-improvement-ive-made-to
1•dsmurrell•29m ago•0 comments

Automatic Alt Text Generation

https://github.com/alexander-turner/alt-text-llm
1•Turn_Trout•29m ago•0 comments

Preserving Time for Focused Work

https://rfd.shared.oxide.computer/rfd/0083
1•lwhsiao•30m ago•0 comments

PasLLM: An Object Pascal inference engine for LLM models

https://github.com/BeRo1985/pasllm
3•nor-and-or-not•35m ago•1 comments

X begins rolling out the 'About this account' feature to users' profiles

https://techcrunch.com/2025/11/21/x-begins-rolling-out-the-about-this-account-feature-to-users-pr...
4•paulatreides•38m ago•1 comments

Nuclear Energy

https://ourworldindata.org/nuclear-energy
1•andsoitis•40m ago•1 comments

AWS Security Incident Response now provides agentic AI-powered investigation

https://aws.amazon.com/blogs/security/accelerate-investigations-with-aws-security-incident-respon...
1•dan_l2•44m ago•0 comments

The Fatal Trap UBI Boosters Keep Falling Into

https://thereader.mitpress.mit.edu/the-fatal-trap-ubi-boosters-keep-falling-into/
2•pseudolus•52m ago•1 comments

https://kaausia45-jpg.itch.io/eidos-ai-prototype-ide

https://kaaussia45-jpg.itch.io/eidos-ai-powered-game-prototyping-environment
2•symbol_reasoner•52m ago•1 comments

Seekdb, an open source AI native search database

https://github.com/oceanbase/seekdb
2•cloudsql•56m ago•0 comments

G20 summit adopts declaration despite US boycott, opposition

https://www.reuters.com/sustainability/climate-energy/g20-leaders-meet-south-africa-seeking-agree...
1•geox•58m ago•1 comments

The silver bullet fallacy

https://timharford.com/2025/11/the-silver-bullet-fallacy/
1•hhs•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•6mo 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•6mo ago
There are only 3 entries, am I correct?
ManuelSH•6mo ago
Yes, we are at very early stage. Looking for other physics experts to help increasing it.
somethingsome•6mo 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•6mo 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•6mo 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•6mo 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.