Show stories

Freeflow is an open-source, self-hosted, and privacy-focused alternative to popular social media platforms. It aims to provide users with a decentralized and ad-free social networking experience that prioritizes user control and data privacy.

My great-grandfather Reuben P. Box was a US Forest Ranger in Northern California, and I've got his daily work diary from 1927-1945, through the depression, WWII, Conservation Corps, and lots of forest fires. I've scanned the entire thing, had Claude help with transcription, indexing, and web site building, and put the whole thing here:

https://forestrydiary.com/

This is one of those projects I've sat on for years, but with Claude and Mistral helping with the handwriting recognition, and even helping me write a custom scanning app that would auto scan each page and put it into a database as I assembled everything.

As far as I know, this is the only US Forestry Diary that has been fully scanned in and published. I understand that there are other diaries in some collections, but none have been scanned in. I hope this helps somebody. Please let me know if it does.

This is the sort of project Claude and AI can help with - A personal project that sits on the shelf forever, but now a reasonable project that can be published in my spare time. I'm not trying to earn money on this, but just improving our knowledge and history just a little bit.

Dear HN,

My wife and I both love nature and have always wanted a Pokémon go style app, to collect and learn about different species we find.

All the usual species identifying apps were didn’t feel fun enough, so we designed and built one together!

Would love for you guys to give it a try and share any thoughts you have.

Related: Show HN: JeffTube - https://news.ycombinator.com/item?id=47030797

Hey HN, I don’t know who else has the same issue, but:

Textbooks often bury good ideas in dense notation, skip the intuition, assume you already know half the material, and get outdated in fast-moving fields like AI.

Over the past 7 years of my AI/ML experience, I filled notebooks with intuition-first, real-world context, no hand-waving explanations of maths, computing and AI concepts.

In 2024, a few friends used these notes to prep for interviews at DeepMind, OpenAI, Nvidia etc. They all got in and currently perform well in their roles. So I'm sharing.

This is an open & unconventional textbook covering maths, computing, and artificial intelligence from the ground up. For curious practitioners seeking deeper understanding, not just survive an exam/interview.

To ambitious students, an early careers or experts in adjacent fields looking to become cracked AI research engineers or progress to PhD, dig in and let me know your thoughts.

A pretty simple but fun to play with simulator for a concept from mathematical physics called the "2D Coulomb gas". I originally made this for my Bachelor's thesis to create pretty pictures and build intuition but have recently gotten it a fresh coat of paint and better performance curtesy of WebGPU acceleration (ported with liberal help from Codex to get through all of the boilerplate).

Play around with it - hopefully read up more on the 2D Coulomb gas because it is an incredibly deep topic research wise.

I like to use org files a lot, but I wanted some way to browse and edit them on my phone when I'm out. Yesterday I used Codex to make this simple one-file web server that just displays all my org files with backlinks. It doesn't have any authentication because I only run it on my wireguard VPN. I've been having fun with it, hopefully it's useful to someone else!

This article discusses a vulnerability found in the Microsoft Notepad application that could allow remote code execution. The author provides a tool to check for and mitigate this vulnerability, which affects various versions of Windows operating systems.

The article discusses the launch of Aureus, a new cryptocurrency focused on decentralized finance (DeFi) and providing financial services to underbanked populations. Aureus aims to leverage blockchain technology to offer access to banking, lending, and investment opportunities to those with limited access to traditional financial systems.

Hi HN! Nerve is a solo project I've been working on for the last few years. It's a developer tool that stitches together data from multiple sources in real-time.

A lot of high-leverage projects (AI or otherwise) involve tying data together from multiple systems of record. This is easy enough when the data is simple and the sources are few, but if you have highly nested data and lots of sources (or you need things like federated pagination and filtering), you have to write a lot of gnarly boilerplate that's brittle and easy to get wrong.

One solution is to import all your data into a central warehouse and just pull it from there. This works, but 1) you need a warehouse, 2) you have an extra copy of the data that can get stale or inconsistent, 3) you need to write and manage pipelines/connectors (or outsource them to a vendor), and 4) you're adding an extra point of failure.

Nerve lets you write GraphQL-style queries that span multiple sources; then it goes out and pulls from whatever source APIs it needs to at query-time - all your source data stays where it is. Nerve has pre-built bindings to external SAAS services, and it's straightforward to hook it into your internal sources as well.

Nerve is made for individual developers or two-pizza teams who:

-Are building agents/internal tools

-Need to deal with messy data strewn across different systems

-Don't have a data team/warehouse at their disposal, (or do, but can't get a slice of their bandwidth)

-Want to get to production as quickly as possible

Everything you see in the demo is shipped and usable, but I'm adding a little polish before I officially launch. In the meantime, if you have a project you'd like to use Nerve on and you want to be a beta user, just drop me a line at mprast@get-nerve.com (it's free! I'll just pop in from time to time to ask you how it's going and what I can improve :) )

If you want to get an email when Nerve is ready from prime-time, you can sign up for the waitlist at get-nerve.com.

Thanks for reading!

(EDIT: Nerve is desktop only! I'll put up a gate on the site saying as much.)

I built this to study something most security engineers wave off: whether external factors can nudge hardware entropy sources.

Here is why. Princeton’s PEAR lab ran RNG work for about 28 years and shut down in February 2007. People in the lab tried to shift random event generator output, and they reported small deviations after tens of millions of events. https://www.pear-lab.com/

The Global Consciousness Project took a similar idea outside the lab. It has run a distributed network of hardware RNGs since 1998 and looks for correlated deviations around major world events.

Most people looking at hardware entropy want true randomness for crypto. I want to treat entropy like a sensor. I want to see what might perturb the underlying noise, not just consume a final stream.

So I built OpenEntropy. It samples 47 physical-ish sources on Apple Silicon, like clock jitter, thermal beats, DRAM timing conflicts, cache contention, and speculation timing. Raw mode gives you unprocessed, per-source bytes so you can run your own stats on each channel.

The PEAR-style question is: does output shift when “intention” is the experimental condition? With 47 sources, I can run intention vs control sessions and ask if multiple unrelated channels drift the same way at the same time. If thermal and DRAM timing both shift during intention blocks, that’s the kind of pattern I want to measure.

very much inspired by karpathy's microgpt of the same name. it's (by default) a 4000 param GPT/LLM/NN that learns to generate names. this is sorta an educational tool in that you can visualize the activations as they pass through the network, and click on things to get an explanation of them.

Body: I built a polyphonic synthesizer in Python with a tkinter GUI styled after the Moog Subsequent 37.

  Features: 3 oscillators, Moog ladder filter (24dB/oct), dual ADSR envelopes, LFO, glide, noise generator, 4 multitimbral channels, 19 presets, rotary
  knob GUI, virtual keyboard with mouse + QWERTY input, and MIDI support.

  No external GUI frameworks — just tkinter, numpy, and sounddevice.

Scrappy is a Python-based web scraping tool that provides an easy-to-use interface for extracting data from websites. It offers features such as scheduling, parallel processing, and database integration to enhance web scraping workflows.

Pangolin (https://github.com/fosrl/pangolin) is an open-source tool for identity-based remote access to internal resources - an alternative to Cloudflare ZTNA, Zscaler, and Twingate.

It’s different than existing approaches: mesh VPNs (Tailscale, ZeroTier, etc.) create flat overlay networks where ACL and IP space management becomes complex at scale and every device can talk to every other device, while corporate ZTNA solutions (Zscaler, Cato, Netskope etc.) are closed-source and add latency by forcing traffic through a central server.

Pangolin takes a resource-centric approach. You deploy lightweight connectors that bridge to specific resources (private web apps, SSH, databases, CIDR ranges). Admins delegate resource-access to specific users and roles. It uses WireGuard with NAT hole-punching for peer-to-peer connections and traffic goes directly between the user and connector instead of through a central server. It supports native clients (Mac/Windows/Linux/iOS/Android) plus identity-aware, browser-based access when a client isn’t required.

Pangolin has a cloud and is optionally self-hosted. The Community Edition is AGPLv3. The Enterprise Edition is also open-source under the commercial license which enables free personal/small business use.

Everything, from the server to the clients, is fully open-source and you can even self-host the whole stack. We’d love to hear what you think and I'm happy to answer any questions!

I built WowAI.pet to solve the "uncooperative subject" problem in pet photography. Most pet owners have a gallery full of motion-blurred "failed" shots because pets simply won't sit still.

Instead of fighting the shutter speed, I’m using generative AI to treat these blurred images as structural seeds. The tool transforms a single low-quality photo into high-fidelity video (4K, consistent depth-of-field) across various styles—from traditional ink-wash aesthetics to talking avatars.

Key Features:

Zero-shot generation: No model training or fine-tuning required.

Temporal consistency: Maintaining pet features across dynamic motion.

Integrated Lip-sync: Automated voice synthesis for "talking" pet videos.

I’m looking for feedback on the generation speed and the consistency of the output styles.

This article discusses the advancements in flight technology, focusing on the development of electric and sustainable aviation options to reduce the environmental impact of air travel. It explores the potential of new propulsion systems, battery technologies, and other innovations that could transform the future of air transportation.

ZIT is a tiny micro-library that takes zooplankton locomotion videos and renders them into 2D flattened static images, encoding motion over time into a single frame for compact analysis. Installable via pip install zooplankton-image-tool.

I built this because I wanted voice dictation without sending my voice data to cloud services.

Vocalinux is a privacy-focused, open-source dictation tool that runs entirely on your Linux machine:

- Local speech recognition (whisper.cpp, VOSK, or OpenAI Whisper) - GPU acceleration via Vulkan (AMD/Intel/NVIDIA) - Works offline, no network required - Universal compatibility (X11/Wayland, any app) - GTK system tray app

Installation: one-line curl command with auto-detection for GPU/CPU

GitHub: https://github.com/jatinkrmalik/vocalinux

Questions and feedback welcome!

Hi HN!

I've been building this solo for about three and a half years. I kept trying every new project/notes tool (Notion, Asana, Trello, etc.) and always ended up back in a plain text file. I wanted something that felt like a text editor on first touch but could grow into real structure when you needed it.

https://lightwave.so (desktop only)

The tech stack is Laravel, MySQL, Redis, and hand-rolled JavaScript on the client. No frameworks like React/Vue/etc. ~270 lines of jQuery (out of 80k+ total LOC) for a few legacy DOM utilities, plus IndexedDB for local persistence. Real-time collaboration uses a hybrid approach: HTTP/2 POST for resilient ops + WebSockets via Laravel Reverb for live cursors, presence, and edits.

This is a pre-release stress test, not a launch. Lightwave will be a paid product. Right now I'm opening it up because no amount of solo testing replicates getting punched in the mouth by real traffic.

The link above has a button to create a test account in 1 click.

Known rough edges: the cursor and selection system are built from scratch (like VS Code, not a contenteditable wrapper), so there's a lot of surface area. Some keyboard shortcuts may be missing. Desktop only, accessibility not yet implemented. I'm shipping fixes in real time.

There's a "Submit Bug or Feedback" button inside the app if something breaks. Happy to answer any questions about the architecture, or anything else.

Some highlights:

- Paste markdown in, get native blocks. Copy blocks out, get markdown back.

- Hierarchical document, structure. Hierarchichal file manager.

- Live collab with shared cursors, selection, and presence.

- Code blocks with syntax highlighting. LaTeX math blocks.

- Full data export: markdown, JSON, and attachments. No lock-in.

- Full undo/redo with cursor restoration.

I built https://sceneitsf.com to map where movies actually filmed in San Francisco versus the impossible geography they show on screen.

Started because I couldn't stop thinking about how characters teleport between neighborhoods that are miles apart. Mrs. Doubtfire runs her route at 27 MPH in heels. Shang-Chi's bus fight turns onto streets that don't physically connect. Ant-Man turns on Lombard and arrives at the Embarcadero.

Built in 20 hours. Hit 122K views on Reddit overnight.

Features: - 60+ films mapped with real filming locations - Speed calculations for impossible transit - Walking tours showing absurd character movement - Interactive game for bar crawls

Tech stack:React/Next.js, Leaflet.js/Mapbox, all client-side with JSON data

Would love feedback on what to add next. More TV shows? Food scenes from films?

This post is about the brute-force reverse engineering of binary (compiled) programs using Large Language Models (LLMs) to automate this two-part problem: decompilation and conversion to a modern programming language.

The most interesting part for most will likely be the demonstration on how to use differential-property testing to automate the LLM feedback loop for the rewrite (translation) phase (in this case to rewrite to Rust).

This that I believe would solve the 'rewrite issues' discussed recently here: https://news.ycombinator.com/item?id=46954696

Telescope originally started as a ClickHouse-focused log viewer.

But while building it, I kept running into the same pattern: when everything worked, logs were in ClickHouse. When things broke, logs were still inside Kubernetes.

That gap led to adding Kubernetes as a native log source.

This is not meant to replace proper log aggregation. Centralized storage with indexing and retention policies is still the right approach for production.

But there are situations where aggregation doesn't help: the logging pipeline is broken, logs are delayed, or you're debugging locally and don't have a pipeline at all.

In those cases, the logs are already in the pods. The usual fallback is kubectl logs (or stern), often across multiple terminals and namespaces. It works, but correlation becomes manual.

Telescope can now query logs directly from Kubernetes clusters via the Kubernetes API. It lets you query across multiple namespaces and clusters, filter by labels and fields, apply time ranges, normalize severity across different log formats, and visualize log volume over time.

It uses your existing kubeconfig, fetches logs in parallel (configurable concurrency), and uses time filters to limit data transfer from Kubernetes APIs.

No agents. No CRDs. No cluster changes.

Current limitations: no streaming / follow mode yet.

Curious if others have run into the same "pipeline gap" problem - when logs aren't in your backend yet, but you still need structured access to them.

GitHub: https://github.com/iamtelescope/telescope

Changelog: https://docs.iamtelescope.net/changelog

I noticed that AI tends to be really good at writing functional code, but not so good at making UI. It turns out that AI has a closed feedback loop in coding with linters and unit testing, but nothing strong for UI. Screenshots and DOM snapshots just don't provide actionable enough feedback for LLMs. To solve this, I made ViewLint: an easily extensible and customizable linter that finds issues with your UI with rules that actually validate and interact with your rendered UI. From testing it's been able to help Codex catch some UI issues (text contrast, element overlap) it otherwise wouldn't have been able to catch! It's available as a MCP for AI use, as a CLI for human use, and as a JS/TS API for CI use.

Hello HN!

These last few months I've been working on my first open source project: an embedded database written in pure-go. That took me some months, as I had to learn how to deal with such large packages. Until then, all packages I had made were quite small an did not require much. I usually did not have to worry about things like allocation optimization and instance pools until This project.

It started when I wanted to make a port of a tool to a TUI environment. I'm actually used to working with TUIs in golang, so that was my language of choice. The tool I wanted to port is written in TypeScript and uses NeDB (written in JavaScript) as database. Since I feel more comfortable working with compiled languages, I decided to create my own database, making sure it was compatible with NeDB, and that's what I did for the last few months.

And that's how GEDB was created. It's a mongodb-like embedded database, written in pure-go. It supports a subset of useful querying options of MongoDB (keywords like $lt, $exists, $in, $where, etc.). By default, it uses a in-memory-only storage, but can easily initialized with a data file.

Everything in my package can be dependency injected, as everything is controlled interfaces. Serialization, querying syntax, document structure, indexing and more, all can be replaced by implementing an interface.

I've also been considering adopting a new document model, by creating a binary type (like BSON) to reduce drastically the cost of creating, maintaining and copying documents (they currently are map[string]any).

The project is currently in an early stage, version 0.1.0, so I'm okay with making changes to the API for now, until I'm ready to release version 1.x.x

I would be really glad if you guys could check it out and give some feedback. An issue, suggestion or a star are very welcome.

My repository can be found on my github: https://github.com/vinicius-lino-figueiredo/gedb

Solo dev, Hudson Valley NY. I built ROLLIN because Google Maps gives wheelchair users a yes/no checkbox and calls it accessibility data.

  ROLLIN scores locations 0-100 across 6 features: wheelchair entry,
  accessible restroom, level entry, parking, wide aisles, elevator.
  Data pipeline pulls from OpenStreetMap, cross-references Google Places,
  and layers in community verification with a trust-weighted scoring system.

  Stack: Vanilla JS (no frameworks), Netlify serverless, Supabase/Postgres,
  Leaflet maps. ~56K locations across NY, CA, FL, MA, NJ, PA.

  Free to use, free API tier for developers. Paid tiers for
  higher volume and commercial use.

  https://joinrollin.com
  API docs: https://joinrollin.com/developers

I built a free, browser-based tool for exploring scales, modes, and their diatonic chords. Pick any root note and scale (major, natural minor, all seven modes, and 70+ other scales) and instantly see which chords (triads, 7th, 9th, etc.) belong to that key.

It also includes a built-in sequencer so if you've found interesting chords for your scale, you can arrange them into a progression and hear how they flow together. No need to switch between a theory reference and a DAW just to test whether a ii–V–I sounds right in your preferred scale.

No signup, no ads, no paywall, just a tool I wished existed when I was learning music theory. There's also a growing collection of articles covering diatonic chords, seventh chords, modes, extended jazz harmony, and common progressions.

Built with Hugo as a static site. Would love feedback from fellow musicians and music theory nerds.

The article discusses the growing popularity of online education and the advantages it offers, such as increased accessibility, flexible scheduling, and cost-effectiveness. It also explores the challenges faced by online learning, including the need for self-discipline and the potential for technical issues.