Show HN: Generating Random Art in Haskell https://ift.tt/3VszUda

Show HN: Generating Random Art in Haskell https://ift.tt/Rj8QSU4 March 3, 2025 at 11:53PM

Show HN: A Transformer model that preserves logical equivalence https://ift.tt/bwEX1x5

Show HN: A Transformer model that preserves logical equivalence https://ift.tt/cOGMVAR March 3, 2025 at 02:11AM

Show HN: Mmar – open-source, zero-dependancy, cross-platform HTTP tunneling https://ift.tt/b17Vf5W

Show HN: Mmar – open-source, zero-dependancy, cross-platform HTTP tunneling Hey HN! For the past couple of months, I've been working on and off on a cool project I'm excited to share. mmar (pronounced "ma-mar") is an open-source, zero dependency, cross platform and self-hostable HTTP tunnel built in Go. It allows you to easily expose your localhost to the world on a public URL. You can easily create an HTTP tunnel right away for free on a randomly generated subdomain on "*.mmar.dev" if you don't feel like self-hosting. This isn't something new, in fact there's quite a few of alternative HTTP tunneling tools out there. mmar is my attempt to optimize for a super easy developer experience and simplified implementation. None the less, I had a blast building it and I think developers could find it pretty useful. Additionally, I documented the whole process of building mmar through devlogs. You can read about the thought process and implementation details here ( https://ift.tt/pjOmFrs ). If I would suggest one devlog to read, I highly recommend devlog 5 ( https://ift.tt/CKxbHqX ). I describe how I built a (very) basic DNS server just to run simulation tests for mmar (a bit of an overkill, but a fantastic learning experience). I dive deep into the DNS protocol and explain why I needed to implement it. Finally, I would love to hear your thoughts and feedback. If you try mmar out, let me know! https://ift.tt/XKvp956 March 3, 2025 at 01:28AM

Show HN: Fast Transition from Firefox to Librewolf https://ift.tt/G3EVSZd

Show HN: Fast Transition from Firefox to Librewolf After looking at various browser alternatives to Firefox (my daily driver for years), I decided to try LibreWolf and the transition was trivial on a Debian based system (by HN standards). My extensions even ran without logging in (YMMV). First install LibreWolf: sudo apt update && sudo apt install extrepo -y sudo extrepo enable librewolf sudo apt update && sudo apt install librewolf -y Second: After closing Firefox, copy Firefox profile (in ~/.mozilla/firefox/) to Librevox profile (in ~/.librewolf/). Note: I copied the profile into the default profile (as seen in about:profiles) not default-default. I then launched the profile and all my tabs were restored, bookmarks, logins, etc. I will update if something seems broken. March 2, 2025 at 11:44PM

Show HN: Schedual https://ift.tt/cnlD8eb

Show HN: Schedual No nonsense tasks. https://schedual.app/ March 2, 2025 at 01:10AM

Show HN: LLM Token Visualizer – How big is 128k token input https://ift.tt/JtLbhYu

Show HN: LLM Token Visualizer – How big is 128k token input https://ift.tt/M62q9Hs March 2, 2025 at 01:14AM

Show HN: Open-source tool that send UI feedback with context https://ift.tt/Cqvi27h

Show HN: Open-source tool that send UI feedback with context https://ift.tt/uksr9E8 March 2, 2025 at 01:11AM

Show HN: I built an app to convert ChatGPT Deep Research to PDFs with footnotes https://ift.tt/7QFy3mk

Show HN: I built an app to convert ChatGPT Deep Research to PDFs with footnotes Whilst ChatGPT Deep Research is very useful for generating in-depth reports, it's time consuming to copy, reformat the text (thousands of words) and clean referenced hyperlinks for use in a professional context. Out of frustration, I built deep research docs to help save time by automating the reformatting, cleaning links, footnote references, and conversion to shareable PDF format. Hopefully this helps you save time to focus on meaningful work. Let me know your feedback. https://ift.tt/1kQu4Zo March 1, 2025 at 06:22PM

Show HN: Torii – a framework agnostic authentication library for Rust https://ift.tt/CApP0re

Show HN: Torii – a framework agnostic authentication library for Rust https://ift.tt/kWTw47J March 1, 2025 at 04:46AM

Show HN: Find out if you qualify for an O-1 visa https://ift.tt/q5ElBmS

Show HN: Find out if you qualify for an O-1 visa https://o1pathways.com/ March 1, 2025 at 03:49AM

Show HN: Betting game puzzle (Hamming neighbor sum in linear time) https://ift.tt/9LSQAjd

Show HN: Betting game puzzle (Hamming neighbor sum in linear time) In Spain, there's a betting game called La Quiniela: https://ift.tt/KrUeApM Players predict the outcome of 14 football matches (home win, draw, away win). You win money if you get at least 10 correct, and the prize amount depends on the number of winners. Since all bets are public, the number of winners and the corresponding payouts can be estimated for each of the 3^14 possible outcomes. We can also estimate their probabilities using bookmaker odds, allowing us to compute the expected value for each prediction. As a side project, I wanted to analyze this, but ran into a computational bottleneck: to evaluate a prediction, I had to sum the values of all its Hamming neighbors up to distance 4. That’s nearly 20,000 neighbors per prediction (1+28+364+2912+16016=19321): S_naive = sum from k=0 to r of [(d! / ((d-k)! * k!)) * (q-1)^k] (d=14, q=3, r=4) This took days to run in my first implementation. Optimizing and doing it with matrices brought it down to 20 minutes—still too slow (im running it in GAS with 6 minutes limit). For a while, I used a heuristic: start from a random prediction, check its 28 nearest neighbors, move to the highest-value one, and repeat until no improvement is possible within distance 3. It worked surprisingly well. But I kept thinking about how to solve the problem properly. Eventually, I realized that partial sums could be accumulated efficiently by exploiting overlaps: if two predictions A and B share neighbors, their shared neighbors can be computed once and reused. This is achieved through a basic transformation that I implemented using reshape, roll, and flatten (it is probably not the most efficient implementation but it is the clearest), which realigns the matrix by applying an offset in dimension i. This transformation has two key properties that enable reducing the number of summations from 19,321 to just 101: - T(T(space, d1), d2) = T(T(space, d2), d1) - T(space1, d) + T(space2, d) = T(space1+space2, d) Number of sums would be the result of this expression: S_PSA = 1 + (d - (r-1)/2) * r * (q-1) I've generalized the algorithm for any number of dimensions, elements per dimension, and summation radius. The implementation is in pure NumPy. I have uploaded the code to colab, github and an explanation in my blog. Apparently, this falls under Hamming neighbor summation, but I haven't found similar approaches elsewhere (maybe I'm searching poorly). If you know or you've worked on something similar, I'd love to hear your thoughts! colab: https://ift.tt/pFVkozG... github: https://ift.tt/8qe3E9R blog: https://ift.tt/gzfQhmt... March 1, 2025 at 02:03AM

Show HN: News-briefing-generator – Local LLM-powered news digest https://ift.tt/ieEHB2m

Show HN: News-briefing-generator – Local LLM-powered news digest Hey HN, I created a tool to generate personalized news briefings from RSS/Atom feeds using local LLMs through Ollama. It currently works in two modes: fully automatic or with an interactive review where you can select which "main topics of the day" to include in your briefing. The result is a HTML document with summaries for each topic. https://ift.tt/zryDNqE February 28, 2025 at 10:45PM

Show HN: Wampy, interface addon for Linux-based Walkmans https://ift.tt/DNetQUr

Show HN: Wampy, interface addon for Linux-based Walkmans Wampy is an interface addon for modern Linux-based Walkmans, which allows you to switch between standard interface and custom one using hardware Hold switch. The project was born out of handful of standard UI nitpicks and "can I make a prettier UI?". There is no Rockbox port for my device (NW-A55), so I did a UI myself, unlocking and adding various features along the way, such as: - Winamp 2 skin support - Custom cassette skins - Digital clock skin ported from iPod Nano 7g - Audio amplification table editor for S-Master HX - All audio filters are available regardless of firmware - Per-song audio filter options - Standard interface enhancements (add clock and increase cover art size) - Low latency USB DAC module - FM radio on devices with FM chip and Walkman One (A40/50) The result covers 6 models, from cheapest NW-A30 to premium NW-WM1Z. Development process involved a lot of reverse engineering, digging into device internals and was pretty fun overall; there are links to development stories in README.md, describing how this or that feature was added. https://ift.tt/oRfIPyb February 27, 2025 at 11:37PM

Show HN: Ranked Search for Semi-Structured Data https://ift.tt/qNPSpAM

Show HN: Ranked Search for Semi-Structured Data We’ve been working on a search problem that requires querying both text and numbers simultaneously. For example, in a dataset of clothing items with descriptions and prices, a search for “slim pants for $20” should prioritize skinny jeans for $25 over slim pants for $50 because they are semantically similar and the price is closer. I’ve found that standard embedding models struggle with numerical ordering, while text-to-SQL methods rely on exact matches and often filter out too many results. To solve this, we built a system designed specifically for structured datasets like CSVs or tables. Here’s a demo link where you can upload a small CSV to try out (no login required): https://ift.tt/xD7rVp8 . Unlike most RAG approaches, we process each column independently, handling text with embeddings and numbers with custom scoring. When a user submits a query, we parse it into relevant fields—for instance, extracting “slim pants” as the description and “20” as the price. We then compute cosine similarity between the description embeddings and “slim pants” while also calculating the percent error between the user’s price input and the numerical field. These individual similarity scores are then combined across all columns to generate a final ranking. Right now, our system works best with well-structured data, so some preprocessing is often needed. We’re working on improving this by detecting and restructuring messy data automatically, such as pivoting columns or extracting attributes from large text fields. We’re also adding feedback mechanisms, like a thumbs up/down system, to refine future search results based on user input. I’d love to hear about your experiences with similar search challenges and would appreciate any feedback! https://ift.tt/xD7rVp8 February 27, 2025 at 11:27PM

Show HN: Simple website for training your ear https://ift.tt/AdcVkg8

Show HN: Simple website for training your ear If the experience is bad on mobile, try with headphones or on a PC / Mac. https://ift.tt/BUFuwCe February 27, 2025 at 12:56AM

Show HN: Instantly Translate Manga – TranslateManga https://ift.tt/XiCEdUA

Show HN: Instantly Translate Manga – TranslateManga Since I was young, I've loved anime, and over the years, manga has brought me joy, given me courage, and sparked excitement in my heart. However, as I read more, I realized that many of these manga weren't translated at all. I also came across some AI-based translation tools, but the results often fell short. So, I decided to create a tool that allows manga fans to read and enjoy their favorite manga, no matter the language or whether a translation team is available. This product has just been launched, and there are certainly areas that can be improved. However, with time, I'm confident it will only get better. You're welcome to try it out and share your valuable feedback! https://ift.tt/pKWLPyZ February 24, 2025 at 08:09PM

Show HN: I built a PR listener and ruleset to detect malicious code in CI/CD https://ift.tt/1Z0wakH

Show HN: I built a PR listener and ruleset to detect malicious code in CI/CD I built a GitHub app that detects it in pull requests, notifies or blocks them. Alongside it, I published a Semgrep ruleset for any stage of the CI/CD. I started this after getting frustrated by all the FUD around malicious code - lots of noise, little effort to solve it. Having said that, it's still a major attack vector - a stored RCE, with the codebase itself as the sink. Feedback is appreciated. The app, PRevent - https://ift.tt/R3AisjV The ruleset: https://ift.tt/G4y1e7n The research: https://ift.tt/cmRT4Nq... https://ift.tt/R3AisjV February 26, 2025 at 12:52AM

Show HN: Minimalist Travel Planner https://ift.tt/cJvSulB

Show HN: Minimalist Travel Planner I was tired of finding repetitive travel plans on ad-filled travel sites, so I made a minimal editable trip plan maker. https://triptip.cat/ February 25, 2025 at 08:21PM

Show HN: URnetwork – Decentralized VPN Replacement https://ift.tt/uKMAW9H

Show HN: URnetwork – Decentralized VPN Replacement I spent the last 1.5 years working out how to scale a decentralized network safely and efficiently to millions of users. URnetwork is a market for network capacity, where each connection races to find the best provider on the network. This means users have many IP addresses that continually cycle, and users can directly connect to each other, which is great for privacy when some minimum conditions are met. Because the world already has a bunch of hardware and network capacity that can be used, the challenges were to design a protocol to make it safe to use and participate, fast and reliable, and to set up the right encryption bar for safe peer to peer data. You can try the apps on iOS and Android and see if they work better than your current VPN. The source is here https://ift.tt/FD45skp About me, I was an early engineer at Palantir, former YC founder, and spent the last decade building global infrastructure. I'm interested in truly free, transparent, private, available, and secure networks that reward people to contribute what they have. Ease of use and safety to participate has been a big focus for me. https://ur.io/ February 25, 2025 at 02:47AM

Show HN: Electro – A hyper-fast Windows image viewer with a built-in terminal https://ift.tt/bNlpsXZ

Show HN: Electro – A hyper-fast Windows image viewer with a built-in terminal This is my first major OSS release! I was always so frustrated by how slow image viewers were on Windows so I built one from the ground up with Rust & Tauri v2.0! Electro also has a very unique feature: a built-in terminal. I was always mesmerised by merging CLI tools with GUI based systems and this is my first go at it! I have big plans on expanding the terminal functionality with built-in image editing commands, command chaining, file handling etc. https://ift.tt/LjaVkc1 February 25, 2025 at 02:20AM