Doom Study
Doom scrolling with micro learning based on your notes
What it does
scroll through notes not instagram
Does a similar job
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Microlearning apps with a TikTok-style feed to beat doomscrollingJun 2026 · usescroll.app · ▲5I wanted to kick my doomscrolling habit, so I built a microlearning app that uses a TikTok-style algorithm, same addictive feed mechanics, but you actually learn something. I started with a general version, Scroll: Daily Microlearning (microlearning.usescroll.app), but quickly realised it works better when focused on a single topic. So I split it into: Scroll: Personal Finance (https://finance.usescroll.app) Scroll: Learn AI (https://ai.usescroll.app) Scroll: Daily Microlearning (https://microlearning.usescroll.app)
- DRDoomscrolling Research PapersDec 2025 · openpaperdigest.com · ▲14
Hi HN, Would love your thoughts on Open Paper Digest. It’s a mobile feed that let’s you “doomscroll” through summaries of popular papers that were published recently. Backstory There’s a combination of factors lead me to build this: 1. Quality of content social media apps has decreased, but I still notice that it is harder than ever for me to stay away from these apps. 2. I’ve been saying for a while now that I should start reading papers to keep up with what’s going on in AI-world. Initially, I set out to build something solely for point 2. This version was more search-focussed, and…
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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.
AI · 18d ago · simedw.com
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AI · 19d ago · company-app.joinastute.com
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…
AI · 28d ago · cactuscompute.com
Source: Product Hunt launch ↗
