I trained a 125M model to autocomplete piano on-device
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
Check if any of the $656M in unclaimed royalties at The MLC is yours
Hi HN, I built this. Quick background on why it exists: When music is streamed on digital streaming platforms (think Spotify, Apple Music, Pandora), there are two separate royalty streams: one for the recording, paid through your distributor (DistroKid, TuneCore, CDBaby), and one for the underlying work (generally known as publishing). The work side's mechanical royalties are collected by The MLC, a nonprofit that was created by the 2018 Music Modernization Act (MMA). If you haven't registered your songs with The MLC, there are issues with your metadata, or about half a dozen other reasons, that money will never reach you, it just collects in a big pile we call the "black box". That pile is big. The MLC's own dashboard currently shows over $656M is held (themlc.com/blanket-royalties), and the biggest problem is the MMA dictates that The MLC cannot hold that money indefinitely. At some point, by law, The MLC must distribute this big pile of cash, and since they don't know who it's supposed to go to, they pay it out through a process called "market share" (themlc.com/marketshare). Market share means they pay it out, pro-rata, to the artists, songwriters and publishers that are in the system, which in practice means the largest publishers collect most of the leftovers. This is slated to begin in January 2027 and will pay portions of the pool out monthly (themlc.com/unclaimed-accrued-royalties), as of this morning, the next 12 months of market share sums up to $76.61M, starting with $6.41M in January. Full disclosure: I run Doubly, which is an independent publishing administrator, so I have a commercial interest in this space. That being said, we're a team of two people and we don't have the bandwidth to directly assist the hundreds of thousands of artists and songwriters who are going to start losing this money in January 2027. That's why I built this self-service tool, no signup, no email, no paywall, the reports are completely actionable without needing anything from us. The tool: paste a Spotify artist link (or search for a Spotify artist by name). It pulls every release on that profile, checks each recording against The MLC's public bulk data, and tells you per-song whether it's fully claimed, partially claimed, registered but unmatched, or missing entirely. It then provides a link to the exact MLC tool that fixes each case. It also estimates the dollars stuck, as a rough range. Even if you're not an artist yourself, you probably know someone who is a musician, please share it with them. Thanks for your time and I'm happy to answer any questions about the industry as a whole, The MLC, the tech, anything really.
Open-source Stripe Connect alternative
Hey, I'm Ben. I built Zoneless because I was paying so much to use Stripe Connect on my own marketplace. The fees were really, really bad, and it was also limiting in terms of the seller countries I could onboard. To give you an idea, I was paying around $9,000 per month in fees just to run payouts. Using Zoneless, that cost goes down to around $6. I've been using it personally for the past few months, and onboarded 5,000+ sellers and done 3,000+ payouts. 74% of new sellers on my marketplace choose Zoneless over Stripe, which is really interesting. I appreciate crypto and stablecoins are a bit of a touchy subject, but for this use case of sending global payouts cheaply, it's perfect. The project is open source with an Apache 2.0 licence, which means there's the benefit of no lock-in and no risk of your account getting flagged or shut down. It also has an almost identical API and dashboard to Stripe. Would love to hear any feedback you may have in the comments.
Why You Lost
Show HN: Why You Lost – a Dota 2 post-match autopsy
We chased a weather balloon across Montana and never found it
Since April, I have been working with Sam Flynn (https://drook.dev) to make this balloon payload, UpLink. We did a similar launch last year with Hack Club but this was our first independent launch. UpLink was a 491 gram payload testing the insulation properties of 3D printing filaments, while also transmitting 320x240 images over a radio link -- up from the 18x10 images last year! This is a writeup on our engineering process, mistakes made, and learning experiences. It covers: - Custom electronics designed in KiCad - Firmware design - Results from the data we received on the ground - Image transmission - Launch day logistics, and where things went wrong All hardware, software, firmware, and CAD is available on GitHub: https://github.com/radeeyate/UpLink, licensed + certified as open source hardware: https://certification.oshwa.org/us002826.html If you just want to see the images received, I put up a gallery here: https://uplink.gallery.radi8.dev/ If you have any questions, comments, or concerns, let me know. I'm happy to answer anything!
Sci-Trust
Show HN: Sci-Trust – Compare trust among researchers based on their citations
Simple Screenshot Copy
Show HN: Simple Screenshot Copy – screenshots straight to the clipboard
Huzzah
Hello everyone. I've been working on this experimental editor called Huzzah. I've been working almost exclusively with coding agents since January of this year, and over the past few months I began to feel utterly exhausted by them. They're great, but I'm finding it more and more tedious to write full sentences for every change I want. Not only that, but it seems there's a complexity limit for codebases - beyond a certain point the agent begins confusing itself. I'd like to go back to writing code, but I don't want to go all the way back to fully manual coding. So I've come up with this interaction paradigm where you: 1. write pseudocode in whatever way makes the most sense to you 2. on save, the editor synchronizes your work to real source code 3. the pseudocode is persisted alongside the generated code, making your prompt effectively a stored record of intent. It may not work for every use case, but in my initial playthroughs I've found it very enjoyable. Right now it's just a proof of concept - installation instructions are here in the readme: https://github.com/danielvaughn/hz You can also watch a video of it in action here: https://x.com/danielvaughn/status/2090456808431165715 Cheers!
WaveHouse
While building an IoT telemetry solution, we ran into hurdles with Clickhouse. For one, you can't insert quickly AND durably into Clickhouse without setting up something like Kafka, which gets complicated for quick projects wanting to make use of Clickhouse's powerful features. Then, trying to actually query Clickhouse and show data in a UI required a whole backend API to handle auth and permissions. We figured that all these parts together – fast, durable ingest, row-level and column-level security and roles, and realtime streaming – were a lot of scaffolding to have to rebuild for every project we wanted to use Clickhouse in. So, we built them all into a single Go binary to be deployed alongside Clickhouse, to help lower Clickhouse's barrier to entry. We call it WaveHouse. Would love any feedback as we work on improving and adding more features to this OSS project!
Kandelo
Kandelo is an open-source, Wasm-based multi-process kernel that runs POSIX programs in browsers and Node.js. Kandelo is still experimental, but it already runs a substantial range of existing software. Do you have use cases for this? We are trying Kandelo as a new foundation for WordPress Playground which runs server-side WordPress entirely in the browser. Kandelo also looks promising as a sandbox for running agents in the the browser and on the command line. On the side, we've been playing with porting games and desktop environments and even compiling runnable programs within Kandelo. Yet it feels like there are many possibilities we haven't considered. How would you like to use something like this? Demos: Some notes: The demos have been tested in desktop browsers. Unfortunately, YMMV on mobile today. Some of the disk images are large (~50MB) and may take a while to boot initially. Main set, with Shell (bash, vim, nethack, and more), Nginx, PHP, WordPress, and Doom: https://kandelo.dev/20260819-demo/ LÖVE game engine: https://kandelo.dev/20260819-demo-love/ SNKRX running under LÖVE: https://kandelo.dev/20260819-demo-love/?vfs=love-snkrx-abi44... Commander Keen running in DOSBox: https://kandelo.dev/20260819-demo-dos/?demo=keen LXDE desktop PoC: https://kandelo.dev/20260819-demo-lxde/?demo=desktop-lxde Background I wanted an authentic OS-level foundation for running systems software in the browser and started this as a vibe-coded exploration. I figured it would end up being too slow and that we would have to offer many different ways to compromise default POSIX behavior to get anything usable. But after weeks of fighting agents, insisting on genuine POSIX compatibility as the default, I was surprised at how well the system worked without those compromises. Nginx, PHP, Python, Ruby, Redis, and even MariaDB were able to be built using the SDK with minimal hacks. Then we started porting games, having fun, and playing to see how far we could push it. Notes on architecture: There is a central, single-worker kernel, aiming to provide all supportable POSIX syscalls. Each process is a dedicated worker with independent memory. Each process thread is a dedicated worker that shares memory with threads from the same process. Syscalls are done with the process SharedArrayBuffer and the Atomics API. fork() is supported. The system is centered around virtual file system (VFS) images, and the VFS can contain lazy references to programs that may or may not be used. Vim is such a reference in the shell demo. On GitHub: https://github.com/Automattic/kandelo
ParqDB
Show HN: ParqDB – Vector search in the browser from Parquet over HTTP"
OzBrain, a shared brain for knowledge between agents and your team
I think agent-first chat interfaces will be a primary software modality and busy dashboard/UI will go away. I’m not sure who exactly wins it, but I want my knowledge to grow/go with me. A lot of the “knowledge” ie research, analysis, reasoning will be done by agents as the primary user. Our current notes tools & tasks management systems were built for humans… I don’t care what the 17th thing on my bug backlog is. I want to conduct agents that can execute for me and do great work. What I built OzBrain to do: + Create a central place for agent reasoned knowledge to live + Be agnostic about what apps/agents connect to it + Capture everything and track it so I can audit it + Enable teams, collaborators or partners to share brains + Handle conflicts so many agents in the same article doesn’t blow up + Refactor knowledge into more token friendly chunks and map the index well + Close the knowledge loop so new thinking supersedes old thinking across the corpus. Don’t erase, depreciate and link + Keep user data safe and secure ++ Be easy enough to use that you don’t have to have any technical knowledge Some among us will always build their own custom solutions, but there are millions of tech professionals and small business owners that will use agents heavily and need a solution. So I’m trying to build that. Isn’t this like gBrain? Yes, similar. I think it’s like AWS vs Vercel. AWS is very powerful, configurable, and useful if you’re technical and want to invest the time into really fine tuning your system… but if you just want your web deploy/hosting to just work and be easy to deal with you use Vercel. // WHY I MADE IT I’ve been enjoying getting back to my technical roots, as I lost my coding skills more than a decade ago, but with AI I can focus on the system and the product in partnership with agent coding workflows. I recently built a Voice AI for older people. To build it I created an agentic engineering workflow (feel free to rip that up as I’m always looking to improve systems: https://ozbrain.com/resources/eng-flow) My approach with coding agents is trust but verify, and I’m trying to replace the parts where a human would review with an adversarial or specialized agent who would give a better answer/review. I have workflows that will go high level task to shipped PR running in Claude cloud sessions. I use Claude Code locally and Cursor when I want a tighter loop on doing visual work like UI or layout. And Codex to either load balance usage for TokenThriffting or when I want a different llm to think thru something. It was a pain in the ass passing .md files around and keep track of which version was the most recent, so I built a hosted .md storage right in Supabase and any of my agents already have Supabase access. This let me build a solid, scalable, secure voice AI from my phone at the gym. All my agents have access to our knowledge, can write to it, update and refer to it as we build and improve the product and the systems we use. Out of 75 founder friends I asked about how they manage shared knowledge, 26 built their own custom knowledge systems… Obsidian vaults with 7k files synced through a VPS, markdown repos behind their own MCP servers, cron jobs stitching Supabase to a skills file… each a different Frankenstein they have to maintain. 32 said they felt the pain of moving static files around but didn’t have any solution for it. So I rebuilt my brain better and used it to build it. // HOW YOU CAN HELP Would love to have you try it out. The maintenance loop is still in alpha so not running it on customer data yet. If you built your own brain I’d love to hear how you did it. What criteria was most important for you in its design & function. If you are tired of shuffling .md files around I’d love to have you try out OzBrain and to give feedback, just ask your agent to put it in the shared bugs & features brain! Cheers! Bubs.co