NOTUS
Turn any document into smart notes.
What it does
Notus turns any PDF, PowerPoint, or Word doc into a full study toolkit instantly. Upload your document and get AI-generated smart notes, flashcards, exam-priority rankings, and a document-aware chat, all in one place. Unlike basic summarizers, Notus doesn't just tell you what a document says, it tells you what to study, in what order, and where students go wrong. Study smarter, not harder.
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- IMI’m 16 years old and working on my first startup, a study app2025 · notiv.app · ▲82
As a student with a lot of notes I had a problem with studying fast for tests. So I created Notiv an AI study app that analyzes your notes and prepares you for test.
- IMI made an AI that turn live lecture into structured notes,mind-maps,PDF2025 · notorium.app · ▲27
Hi HN, University lectures are long, dense, and fast-paced. Like many students, I used to record them thinking I’d revisit them later — but that never really worked. Even transcripts felt like raw logs. So I built [Notorium](https://www.notorium.app) — an AI assistant that records live lectures and automatically turns them into structured notes, flowcharts, and mind maps— within minutes after class. What it does: - Record lectures inside the app (in-person, live) - Transcribe using Whisper - Send the full transcript to LLM - Use a custom system prompt to: - Summarize the lecture -…
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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 · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
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 · 27d ago · cactuscompute.com
Launched alongside, May 2026
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Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com