Topos
AR Memory Palace + AI flashcards for iPhone
What it does
Topos turns your notes into flashcards in seconds using AI, then helps you remember them with spaced repetition and Memory Palaces — built right into your iPhone camera with AR. No more manually creating cards. No more forgetting what you studied. Just paste your notes, study smarter, and actually retain what you learn. Free to start. Pro is $5.99/month or $49.99/year with a 7-day trial.
Does the same job
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- FNFlash Notes – Flashcards for Your Notes, LLM, iOS/macOS Sync2024 · flashnotesapp.com · ▲82
The app started as my wishful thinking that flashcards should really be derived from notes. I've been constantly writing things down and wishing to remember them. However, I never could convince myself to populate a flashcard app with them. I really tried (Anki, Supermemo), but I guess regular form filling is not for me. So I've started experimenting with flashcards derived from structured notes. Writing the 1st MVP was fast, but productionising it was way harder. Content synchronisation when the user can work from tube/plane and use multiple devices and content is text is… not trivial.…
MyStudyDeckJun 2026 · mystudydeck.store · ▲8Photos and PDFs become Anki flashcards — fully on-device
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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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