We built a modern research paper reader
Over the past year, we’ve been frustrated with how clunky it is to manage research papers. So we built Ontosyn, a modern research paper reader, with clean ui, better in paper navigation (bookmarks, jumping back up after clicking on a reference), an integrated ai chat with useful tools such as recommending relevant papers that you can directly add to your library, and, of course, library functionality to keep everything organized. We launched a closed alpha last week, and our first users are quite pleased with it. One user asked for author-based search for paper recommendations yesterday, and…
In plain words
Ontosyn is a research paper reader designed to simplify how researchers manage and engage with academic papers. It features a clean interface with improved navigation tools including bookmarks and reference jumping, an integrated AI chat that recommends relevant papers for direct library addition, and organizational library functionality. The platform aims to help users stay current with research in their field while making paper engagement more enjoyable. The product is in closed alpha and actively incorporating user feedback.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Over the past year, we’ve been frustrated with how clunky it is to manage research papers. So we built Ontosyn, a modern research paper reader, with clean ui, better in paper navigation (bookmarks, jumping back up after clicking on a reference), an integrated ai chat with useful tools such as recommending relevant papers that you can directly add to your library, and, of course, library functionality to keep everything organized. We launched a closed alpha last week, and our first users are quite pleased with it. One user asked for author-based search for paper recommendations yesterday, and we shipped it within an hour. Our goal is to make it easy to stay up to date with relevant research and enjoy engaging with it. We have lots of cool features planned, we’re still very early, and we’d love to iterate with feedback from the HN community. You can try it at ontosyn.com
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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.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, October 2025
the whole month →

- SA
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AI · Oct 2025 · blog.shashanktomar.com

- ASAutism Simulator▲779
Hey all, I built this. It’s not trying to capture every autistic experience (that’d be impossible). It’s based on my own lived experience as well as that of friends on the spectrum. I'm trying to give people a feel for what masking, decision fatigue, and burnout can look like day-to-day. That’s hard to explain in words, but easier to show through choices and stats. I'm not trying to "define autism". I’ve gotten good feedback here about resilience, meds, and difficulty tuning. I’ll keep tweaking it. If even a few people walk away thinking, "ah, maybe that’s why my coworker struggles in those…
Life & fun · Oct 2025 · autism-simulator.vercel.app
