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Hi HN, I’ve always been frustrated by this: we live in an era of exponential scientific progress, but almost no one can clearly trace a cutting-edge discovery back to the first principles it’s built on. We learn science in silos, not as a connected, logical tree. So I built The Map of Science — an interactive dependency graph for the entirety of human scientific knowledge. It’s simple: every scientific theory is a node, every derivation/dependency is an edge. You can trace a path from basic math axioms to quantum field theory, from early computing to modern LLMs, and see exactly how each breakthrough builds on what came before. The stack: React + Cytoscape for the frontend, Node.js + Neo4j for the backend (a relational DB couldn’t handle the deep recursive queries for multi-layer derivation chains). It’s fully open source under MIT, and we’ve already seeded the core dataset for math, physics, and computer science. This is a project that can never be finished by one person. I need your help: If you’re a domain expert, help us fix incorrect links or expand into biology, chemistry, social sciences, and more. If you’re a developer, help us optimize the graph rendering for even larger datasets. If you just love science, tell us what works, what doesn’t, and what you want to see next. I’d specifically love your thoughts on: We’re using a directed acyclic graph (DAG) tree structure to show derivation dependencies. Does this make cross-field interdisciplinary links clear enough? Is there a better way to visualize these relationships? What’s the cleanest way to represent superseded or disputed theories (like Newtonian vs. relativistic mechanics, or phlogiston theory vs. oxidation)? We want to honor their historical importance without cluttering the core, up-to-date knowledge chain. Repo: https://github.com/slepybear/The-Map-of-Science Live Demo: https://build-five-dun.vercel.app/map (best viewed on desktop for full graph interactivity) Thanks for looking!

Comments URL: https://news.ycombinator.com/item?id=47109121

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Article URL: https://z-image.fun/

Comments URL: https://news.ycombinator.com/item?id=47109014

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Article URL: https://svgees.us/blog/dystopia.html

Comments URL: https://news.ycombinator.com/item?id=47109008

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Article URL: https://hypha.pub/back-to-freebsd-part-1

Comments URL: https://news.ycombinator.com/item?id=47108989

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Article URL: https://github.com/userland-run/nano

Comments URL: https://news.ycombinator.com/item?id=47108984

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Article URL: https://www.bbc.com/future/article/20260220-whats-the-best-way-to-learn-a-new-language

Comments URL: https://news.ycombinator.com/item?id=47108977

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Article URL: https://github.com/0xSMW/screencommander

Comments URL: https://news.ycombinator.com/item?id=47108943

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Article URL: https://techrights.org/n/2026/02/21/Debian_s_Master_is_Deleting_Criticism_of_SystemD_and_Other_Thin.shtml

Comments URL: https://news.ycombinator.com/item?id=47108937

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I didn’t open a Vocabulary app this week. Still learned 100 words.

That surprised me — because I’ve tried to learn vocabulary more times than I can count.

The pattern was always the same:

Download an app → Study hard for a few days → Miss a week → Forget everything.

Not because I’m lazy. But because learning vocab requires too much effort.

10 years ago, I even had an idea called “5s English” — learn just 5 seconds a day. The design was good. The idea was solid. But I couldn’t manage the team, so it died.

Years later, a friend told me about an alarm app that won’t stop ringing unless you solve a quiz.

That hit me.

Why does learning English require motivation… but waking up doesn’t?

So I built Vocab Alarm.

Instead of asking you to open an app, It brings 3 words to you every day — like an alarm.

One minute. Repeated daily. No pressure.

If you know a word → it appears less. If you don’t → it comes back more. That’s it.

Not another “study harder” app. Just a small habit that actually sticks.

Would love to hear how you learn vocabulary — or why most apps didn’t work for you either.

Comments URL: https://news.ycombinator.com/item?id=47108930

Points: 1

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Hey HN, i built this because i wanted to switch between Jira, Confluence, and Bitbucket in cli instead of browser tabs for simple operations.

The existing CLIs only cover one product at a time. I wanted a single tool for the full Atlassian Cloud stack. What it does: - Jira: search, CRUD, bulk transition/assign/export - Confluence: pages, spaces, search, bulk labels - Bitbucket: repos, PRs, pipelines, branch protection - JSM: service desks, requests Some things I think are useful: - Dry-run mode for bulk operations (preview before executing) - Multiple output formats (table/json/csv/yaml) - Profile-based multi-instance support Built in Rust. Install via brew or cargo install. Hope the community finds it useful

Comments URL: https://news.ycombinator.com/item?id=47108912

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Article URL: https://www.nobelprize.org/uploads/2016/04/broglie-lecture.pdf

Comments URL: https://news.ycombinator.com/item?id=47108911

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Inspiration for openclaw users!

We showcase awesome use cases and send you 5 curated one every Tuesday.

Comments URL: https://news.ycombinator.com/item?id=47108902

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I kept pasting code with hardcoded API keys, database credentials, and auth tokens into ChatGPT while debugging. Copy a failing function, paste it into AI, and realise your AWS secret key or Stripe token was right there in the snippet.

So I built (with some help from Claude) a simple Chrome extension that intercepts the paste, detects secrets using local regex, and replaces them with [MASKED] before they reach the chat. Originals stay in a local AES-256 encrypted vault for unmasking.

No servers. No network requests. No tracking. ~41 KB, zero dependencies. Don't take my word for it: 'grep -r "fetch\|XMLHttpRequest" content_script.js' returns nothing.

Works on ChatGPT, Claude, Gemini, Grok, Perplexity, DeepSeek, and any custom site you add. Supports 30+ patterns — AWS keys, GitHub tokens, JWTs, Stripe keys, database URLs, private keys, and more. You can toggle individual patterns off for false positives.

Open source, MIT licensed. With the recent news about extensions harvesting AI conversations, I figured more devs could use this.

Would love feedback — especially on patterns I might be missing or edge cases you hit.

Comments URL: https://news.ycombinator.com/item?id=47108901

Points: 1

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Article URL: https://mahaloz.re/dec-history-pt1

Comments URL: https://news.ycombinator.com/item?id=47108894

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Article URL: https://rafichaudhury.com/site/blog/ersatztv

Comments URL: https://news.ycombinator.com/item?id=47108867

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Article URL: https://quod.lib.umich.edu/m/mqrarchive/act2080.0035.002/10

Comments URL: https://news.ycombinator.com/item?id=47108861

Points: 1

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Article URL: https://dougrathbone.com/blog/2026/02/22/disagree-and-commit-is-not-disagree-and-complain

Comments URL: https://news.ycombinator.com/item?id=47108852

Points: 1

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Microterm is a fully compliant Linux virtual machine that runs in any browser tab. It is designed for real development and operations workflows, not demo-only terminal output. You can use it on desktop, tablets, and phones, including iOS home-screen PWA installs.

Under the hood, Microterm combines Restty (libghostty + WebGPU) web terminal rendering and a TinyEMU-backed Alpine Linux guest on RISC-V64. The VM image is chunk-loaded in the browser and booted locally.

I successfully used it to run Codex directly without leaving an in-app preview inside X app or Telegram :) Can be used to SSH to any server, play with Kubernetes and Tailscale.

Let me know what you guys think!!

Comments URL: https://news.ycombinator.com/item?id=47108845

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Article URL: https://github.com/m4suisui/kickstart

Comments URL: https://news.ycombinator.com/item?id=47108837

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Article URL: https://www.llewellynsystems.com

Comments URL: https://news.ycombinator.com/item?id=47108831

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