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I'm the Agent for Claude Now

https://www.aha.io/engineering/articles/im-the-for-claude-now
1•FigurativeVoid•20s ago•0 comments

Brazilian Psychic Predicts Alien Invasion During World Cup Game Next Week

https://www.coasttocoastam.com/article/brazilian-psychic-predicts-alien-invasion-during-world-cup...
1•austinallegro•1m ago•0 comments

Shoutout to Canadian Youth: A 16-Year-Old Shipped When Graduates Skipped

https://codrlabs.com/blog/shoutout-canadian-youth-shipped-when-graduates-skipped
1•codrlabs•1m ago•0 comments

DeepSeek V4 Flash optimized framework and model variants for DGX Spark

https://github.com/sleepyeldrazi/ds4-nvfp4-spark
2•sleepyeldrazi•3m ago•1 comments

AI and tech are trying to influence the midterm elections

https://text.npr.org/nx-s1-5856359
2•pera•4m ago•0 comments

Search, Discovery, Pills, and Portals

https://contraptions.venkateshrao.com/p/search-discovery-pills-and-portals
1•jger15•4m ago•0 comments

Frontier Spaces

https://marginpoints.substack.com/p/frontier-spaces
1•historian1066•4m ago•0 comments

Ask HN: What did you find out or explore today?

1•blahaj•7m ago•1 comments

AI Agent / Harness Engineer

https://www.saturnterminal.com/
1•Ryanaga•8m ago•0 comments

Y2Kspace: 90s/2000s TV channel surfer in retro rooms

https://y2kspace.com/
1•jeremwhi•8m ago•1 comments

Own Private AI, Part 2: Secure Access from Anywhere with Tailscale Aperture

https://10io.com/blog/private-ai-part-2-secure-access-via-tailscale-aperture
1•anactofgod•8m ago•1 comments

Following user outcry, AMD reinstates memory encryption in consumer CPUs

https://arstechnica.com/security/2026/06/following-user-outcry-amd-reinstates-memory-encryption-i...
2•AdmiralAsshat•10m ago•1 comments

Scale Your Superpowers, Not Your Job Titles

https://www.lukew.com/ff/entry.asp?2154
1•speckx•11m ago•0 comments

ULID -- Universally Unique Lexicographically Sortable Identifier

https://github.com/ulid/spec
2•gjvc•12m ago•0 comments

Local lint, type-check and AI security dashboard for modern full-stack projects

https://www.npmjs.com/package/projectlens
1•dagmawibabi•13m ago•1 comments

TamaGo unikernels can now choose between gVisor and lneto network stacks

https://infosec.exchange/@lcars/116736159481184882
2•dolmen•14m ago•0 comments

The Age of the Solopreneur

https://www.stripeeconomics.com/p/the-age-of-the-solopreneur
1•plurby•18m ago•0 comments

Show HN: Sixwhyo – A 6-year-old code reviewer who asks "why?" about everything

https://github.com/hxii/sixwhyo
2•hxii•19m ago•0 comments

Jobs and Software Is Fucked

https://urflow.bearblog.dev/jobs-and-software-is-fucked/
16•speckx•19m ago•3 comments

Civilization – the making of the game of everything [video]

https://www.youtube.com/watch?v=9gM61G29w8g
1•coolwulf•21m ago•0 comments

Show HN: A local rig to test if AI social simulation predicts reality

https://github.com/zzvimercm-git/mirofish-calibration
1•zzvimercm•22m ago•0 comments

Self-Harness: Harnesses That Improve Themselves

https://arxiv.org/abs/2606.09498
2•jonnonz•22m ago•0 comments

The OpenSSL Library AI Policy

https://openssl-library.org/post/2026-06-18-ai-policy/
1•jlericson•23m ago•0 comments

Fonts that appear in Google searches

https://hexagonification.neocities.org/fonts/gsearch_fonts
1•skogstokig•23m ago•0 comments

P99 0 ms* autocomplete for 240M domain names

https://ruurtjan.com/articles/p99-0ms-autocomplete-for-240-million-domain-names
2•rochoa•24m ago•0 comments

Finally, found a good use-case for OCaml

https://ingresslabs.github.io/lpf/
3•akrylov•25m ago•1 comments

I'd Rather Risk Cancer Than See AI Move This Fast

https://www.theatlantic.com/technology/2026/06/ai-cancer-progress/687654/
1•jdkee•26m ago•1 comments

I made a startup platform to take ideas to market

https://app.startuptitan.co
1•Chris_Karam•26m ago•0 comments

Recent Design

https://recent.design/
2•handfuloflight•28m ago•0 comments

AI: Just One Big Trade

https://thenextrecession.wordpress.com/2026/06/06/ai-just-one-big-trade/
2•cdrnsf•28m 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.