The best Hacker News stories from Show from the past day
Latest posts:
Show HN: Dual YOLOv8n UAV Detection on RK3588S at 42 FPS Using NPU
Show HN: 3D print Z reinforcement via injected loops
Commodity FDM print strength is limited by poor Z-axis layer bonding. Parts crack along Z under stress. MAGMA tries to fix this in software that works on any FDM 3D printer.<p>It's a fork of OrcaSlicer with a new infill type that creates paired U-shaped vertical channels inside the print, plus G-code that injects molten plastic into those channels to bridge Z layer interfaces with continuous plastic.<p>Big caveat: I have a junky Ender 3 and haven't gotten a clean physical print yet. Don't expect this to work out of the box! After months of tinkering, I'm releasing the software so the 3DP community can experiment with nozzles, multi-material, weird hardware, and other print parameters I can't. There's around 40 MAGMA-specific settings to fiddle with, plus some general quality-of-life features (e.g. printing thin infill sections as solid, and a "dual infill shell" feature that applies MAGMA only to the outer shell to save print time).<p>THIS CODE IS ALPHA. Around 50 prints old. The injection G-code is novel. Some printer firmware won't like extruding without movement. In extreme cases it could damage your printer or start a fire. DON'T WALK AWAY WHILE PRINTING.<p>Why MAGMA? "Lava tubes" is a misnomer. Molten rock is magma underground, lava only after it surfaces. The injected tubes are buried inside the print, so "magma tubes" is the correct term.
Show HN: Trace – Offline Mac meeting transcripts you can flag mid-call
I'm the developer of Trace, a non-intrusive, shortcut-driven Mac app that records and transcribes your meetings on-device. I know, another meeting transcription app. Please bear with me though, I'm confident that this is at least a little novel.<p>I primarily built Trace for myself. I'd been using MacWhisper, but there was enough fiddling before each call that I'd forget to start it and walk out of an hour-long meeting with nothing written down. So the things I cared about most were that it's quick to activate and stays out of the way. You activate Trace by pressing a global shortcut (configurable), which reveals a small bar at the bottom of your screen (there's also a keystroke and/or option to hide it entirely if you'd rather not see it at all).<p>As I was building it I wanted to bake in a couple of workflows I'd wished for in other transcription apps.<p>1. Mid-meeting you can press another global shortcut to mark a "key moment" and type a note. The note shows up in the resulting transcript inline at that timestamp. I wanted to add this because I kept catching myself thinking "wait, that bit matters" in meetings and reaching to jot it down in a separate app like Obsidian, which I then needed to add context to, which took me out of the meeting. I use it all the time. If I paste the transcript into an LLM afterwards (which I find myself doing more and more these days) the important moments are flagged so it doesn't gloss over them. This is more noticeable in longer meetings with lots of topics.
2. With another keyboard shortcut you can summon a rough live recap (subtitles, basically) to quickly recap what's just been said.<p>Trace uses standard macOS microphone and system recording APIs to capture both sides of the conversation as two separate tracks and then runs the system side through on-device diarization to identify speakers. Right now we only label them as "Speaker 1", "Speaker 2", etc but there are plans for speaker labelling in the future. You can also show a "live recap" as the call is happening to review what someone just said.<p>All transcription models run on your machine. To be clear though, Trace doesn't do any of the summarising itself, it just produces a markdown transcript, so if you want summaries then you need to pass the output to an AI.<p>The app is sandboxed and your audio/transcripts are never uploaded anywhere - they just exist as audio files and markdown on disk. The only network call Trace is required to make is on the first run to download the speech and speaker models (around 500MB) from Hugging Face, and after that it can be used fully offline. If enabled, a Google Calendar integration can auto-name sessions but that needs a network connection.<p>The app is £9.99 on the macOS App Store. I've been using it every day for months now and I'm super happy with how it's improved my workflow. Feedback very welcome.
Show HN: Kage – Shadow any website to a single binary for offline viewing
Show HN: Lightweight Task queue on Erlang/OTP, SQLite-backed, no overengineering
Setting up Kafka or such enterprise oriented software with their clusters or dedicated servers is heavy and bothering enough that most small
teams or indie hackers skip it entirely and making compromise to use in-memory queues.<p>I wanted something in between: a persistent queue that is simple to run (one binary, which makes one sqlite db), gets real fault isolation and crash recovery due to Elixir, easy to inspect (open ezra.db in any SQLite browser and see every
task), and requires no new client library - it speaks the Redis Streams wire protocol,
so any Redis client in any language just works out of the box.<p>Very short demo video: [<a href="https://www.youtube.com/watch?v=MLYyD3DVWmE" rel="nofollow">https://www.youtube.com/watch?v=MLYyD3DVWmE</a>]
Show HN: Lightweight Task queue on Erlang/OTP, SQLite-backed, no overengineering
Setting up Kafka or such enterprise oriented software with their clusters or dedicated servers is heavy and bothering enough that most small
teams or indie hackers skip it entirely and making compromise to use in-memory queues.<p>I wanted something in between: a persistent queue that is simple to run (one binary, which makes one sqlite db), gets real fault isolation and crash recovery due to Elixir, easy to inspect (open ezra.db in any SQLite browser and see every
task), and requires no new client library - it speaks the Redis Streams wire protocol,
so any Redis client in any language just works out of the box.<p>Very short demo video: [<a href="https://www.youtube.com/watch?v=MLYyD3DVWmE" rel="nofollow">https://www.youtube.com/watch?v=MLYyD3DVWmE</a>]
Show HN: 2 Weeks of Hallucinate – The Photo Gallery
Show HN: 2 Weeks of Hallucinate – The Photo Gallery
Show HN: Paca – Lightweight Jira alternative for human-AI collaboration
I built Paca out of pure passion—a free and lightweight Jira alternative written in Go where humans and AI agents work together as equal teammates to plan sprints and assign tasks to each other. It is fully customizable with custom views, fields, and a WASM-based plugin architecture. My team uses it daily for our own development, so it will be continuously maintained and completely free forever
Show HN: Paca – Lightweight Jira alternative for human-AI collaboration
I built Paca out of pure passion—a free and lightweight Jira alternative written in Go where humans and AI agents work together as equal teammates to plan sprints and assign tasks to each other. It is fully customizable with custom views, fields, and a WASM-based plugin architecture. My team uses it daily for our own development, so it will be continuously maintained and completely free forever
Show HN: I am building a map of people who lived in the Roman Empire
Driving home from work one day, I wanted to know how many people we knew the names of who lived during the Roman era. Searching around, I found lists of Consuls and officials, but nothing that covered ordinary people or even most people like freedmen and slaves. So I ended up building a pipeline to process the more than 500k Latin inscriptions in the Epigraphic Database Clauss-Slaby <a href="https://edcs.hist.uzh.ch/en/" rel="nofollow">https://edcs.hist.uzh.ch/en/</a> and extract the names of people (and attempt to cluster them, but this is a work in progress).<p>There are databases where Classicists have done this manually for specific regions, Trismegistos <a href="https://www.trismegistos.org/" rel="nofollow">https://www.trismegistos.org/</a> and Latin Inscriptions of the Roman Empire (LIRE) <a href="https://pure.au.dk/portal/en/publications/latin-inscriptions-of-the-roman-empire-lire/" rel="nofollow">https://pure.au.dk/portal/en/publications/latin-inscriptions...</a> are two major efforts I found. But there doesn't seem to be a project that did what I set out to do, although I have read in some places that it was believed to be possible.<p>I am not a classicist or a web developer, but I have Claude and Gemini and I can sort of read basic Latin - so I set to work. I used LIRE and another database as ground truth and built a pipeline to extract and process the inscriptions to recover the names. The process I developed uses a high end LLM like Sonnet or Gemini Pro to supervise the extraction and tuning process on a regional basis until the obvious error rate is reasonable. For this, so far, reasonable to me means less than 1-2% in the smaller initial samples of 100-500 and no observed systemic issues. The different regions often need different prompts, so this basically became an exercise in letting the higher level AI tune the prompt for the lower level AI. The extraction when measured against LIRE produces an F1 score between 0.64 and 0.87, but take this with a grain of salt.<p>Once I had done a few regions, I wanted to see the work, so I threw together a pretty crude website but as I am not a web developer, it was crude in how it accessed its data. It does look cool and I also added summarization, and machine translation to each entry. I wanted to eventually get feedback from an actual team of classicists and make the website work better, so I am rewriting it as we speak but it is broadly functional now with a few extra bugs but substantially improved performance compared to the old one. All entries link back to the proper sources, and the old web app linked to several additional sources where the data was present, but I haven't gotten that working again just yet on the new one. (The old web interface is still available at <a href="https://roman-names.com" rel="nofollow">https://roman-names.com</a>, but I will warn you it is clunky and not mobile friendly at all)<p>Key findings so far:<p>AI supervised AI extraction saved me time. I was manually tuning things for a while and then the runbook became an idea that I feed my instructions in and let the big AI go with sparse oversight from me.<p>The extraction improved significantly (by about 10 F1 points) when I fed the model the raw text including the markers, vs a cleaned up version of the text.<p>I just thought it was a cool little project and wanted to share. If you happen to work in any adjacent space and there is something I could do better etc let me know.
Show HN: I am building a map of people who lived in the Roman Empire
Driving home from work one day, I wanted to know how many people we knew the names of who lived during the Roman era. Searching around, I found lists of Consuls and officials, but nothing that covered ordinary people or even most people like freedmen and slaves. So I ended up building a pipeline to process the more than 500k Latin inscriptions in the Epigraphic Database Clauss-Slaby <a href="https://edcs.hist.uzh.ch/en/" rel="nofollow">https://edcs.hist.uzh.ch/en/</a> and extract the names of people (and attempt to cluster them, but this is a work in progress).<p>There are databases where Classicists have done this manually for specific regions, Trismegistos <a href="https://www.trismegistos.org/" rel="nofollow">https://www.trismegistos.org/</a> and Latin Inscriptions of the Roman Empire (LIRE) <a href="https://pure.au.dk/portal/en/publications/latin-inscriptions-of-the-roman-empire-lire/" rel="nofollow">https://pure.au.dk/portal/en/publications/latin-inscriptions...</a> are two major efforts I found. But there doesn't seem to be a project that did what I set out to do, although I have read in some places that it was believed to be possible.<p>I am not a classicist or a web developer, but I have Claude and Gemini and I can sort of read basic Latin - so I set to work. I used LIRE and another database as ground truth and built a pipeline to extract and process the inscriptions to recover the names. The process I developed uses a high end LLM like Sonnet or Gemini Pro to supervise the extraction and tuning process on a regional basis until the obvious error rate is reasonable. For this, so far, reasonable to me means less than 1-2% in the smaller initial samples of 100-500 and no observed systemic issues. The different regions often need different prompts, so this basically became an exercise in letting the higher level AI tune the prompt for the lower level AI. The extraction when measured against LIRE produces an F1 score between 0.64 and 0.87, but take this with a grain of salt.<p>Once I had done a few regions, I wanted to see the work, so I threw together a pretty crude website but as I am not a web developer, it was crude in how it accessed its data. It does look cool and I also added summarization, and machine translation to each entry. I wanted to eventually get feedback from an actual team of classicists and make the website work better, so I am rewriting it as we speak but it is broadly functional now with a few extra bugs but substantially improved performance compared to the old one. All entries link back to the proper sources, and the old web app linked to several additional sources where the data was present, but I haven't gotten that working again just yet on the new one. (The old web interface is still available at <a href="https://roman-names.com" rel="nofollow">https://roman-names.com</a>, but I will warn you it is clunky and not mobile friendly at all)<p>Key findings so far:<p>AI supervised AI extraction saved me time. I was manually tuning things for a while and then the runbook became an idea that I feed my instructions in and let the big AI go with sparse oversight from me.<p>The extraction improved significantly (by about 10 F1 points) when I fed the model the raw text including the markers, vs a cleaned up version of the text.<p>I just thought it was a cool little project and wanted to share. If you happen to work in any adjacent space and there is something I could do better etc let me know.
Show HN: StackScope – I crawled over 40k indie launches to see what they ship
Hey all, I built StackScope, a crawler/catalogue that looks at new product launches and shows what they were built with.<p>It watches launches from Product Hunt, Show HN, and PeerPush, then crawls the public site behind each one. The goal is to show what people actually launched with: hosting, frameworks, analytics, DNS, security headers, legal pages, AI-builder signals, and other public clues.<p>I started building it because most stack-detection sites look at the web as a whole. I was more interested in the current indie launch scene: what people are choosing right now, at the point they first put something in public.<p>A few implementation details: it runs on .NET, uses Playwright for rendered pages, and has a first-party fingerprint catalogue rather than one copied from Wappalyzer/etc. robots.txt is honoured, and the bot identifies itself.<p>Frustratingly, I am still waiting for verified bot status from Cloudflare and currently that knocks out about 10% of all sites.<p>There is also a private readiness check: paste a URL, get the same style of report, fix things, and recrawl. No account or email needed.<p>I'd be interested in feedback on the usefulness of this, the methodology, and any obvious false positives.<p>Jonathan.
Show HN: Script to bulk delete Claude chats from the web UI
I haven't found a way to delete all chats in bulk like you can on Chatgpt. With Claude, you have to scroll to the bottom, select everything, and delete. The problem is, if you have a lot of chats, it becomes impossible. I created this script. It does it alone. I hope it helps someone.<p>(conversations disappear from the UI slowly, over several minutes, and remember to keep the tab open until the console shows "Finished", refreshing away from the page can stop the deletion process.)
Show HN: Putt.day a daily mini golf game
Show HN: Putt.day a daily mini golf game
Show HN: Putt.day a daily mini golf game
Show HN: Atlasphere – Live Infrastructure Diagrams
Hi HN. My name is Andrey. On a regular business day, I'm a software engineer working at AWS. Outside of work hours, I spend time on my hobby - writing code.<p>I was once building a pet project that allowed customers to spin up fully synchronized blockchain nodes within just a few minutes. The backend was split into a control plane and a data plane, each with its own AWS account. Later I added two more AWS accounts. One for shared RPC nodes. One for the Analytics Service.<p>Since I love to visualize things, I used drawio to visualize the architecture.<p>With time, I noticed a pattern. I'd write some code, add a few lambda functions, update my drawio diagram, write more code, introduce a few more resources, test things, see that everything works fine and go to sleep with a smile on my face. Next week I'd check my diagram, and shockingly, it's missing some of the resources! This kept happening for a few more weeks until I decided to fully abandon the project until my infrastructure diagrams could stay in sync with my cloud account.<p>That's how Atlasphere.io was born. I've been working on it for the past 6 months and I think the product is ready for some feedback :)<p>A few notes:<p>- Atlasphere uses a ReadOnly IAM role to scan your AWS account (my account reaches your account through a trust relationship).<p>- The number of services is currently limited (WIP)<p>- It's a macOS app<p>- It's NOT an Electron app, i use Rust + Webview<p>What am I looking for? All I really need is for someone to try the app and tell me what they like about it and what they absolutely hate about it, haha!<p>The website is <a href="https://atlasphere.io/" rel="nofollow">https://atlasphere.io/</a>
Show HN: Boo – Screen-style terminal multiplexer built on libghostty
Show HN: Boo – Screen-style terminal multiplexer built on libghostty