
QInatomy
High-yield anatomy quizzes for students
What it does
QInatomy is an anatomy quiz app built for focused study and active recall. It includes 500 offline anatomy questions, so students can practice anytime without internet. The app also offers an AI quiz generator that creates new anatomy questions on demand. Users can unlock the AI feature with a one-time $4.99 purchase.
Does the same job
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I saw this app youlearn.ai on YC and thought of building it. They are claiming to have 1M+ users with just one feature which is to convert your learning material into summaries, quizzes etc. I gave this a shot and cloned almost most of the features in just 9+ hours of continous vibe coding (with 20% manual though). Now I'm selling this on mvp marketplace. Might probably open source it in future or give it free.
- IBI Built AskMedically – Get Research-Backed Answers to Medical Queries2025 · ▲11
Hi HN, I’ve built AskMedically – an AI-powered assistant that answers health and medical questions using real research papers from trusted medical sources like PubMed, Cochrane, etc. Whether you’re a healthcare enthusiast, patient, student, or professional – AskMedically helps you explore trusted medical knowledge without needing a medical degree or slogging through dozens of PDFs. Examples: • “Does intermittent fasting improve insulin sensitivity?” • “What are the benefits of creatine for brain health?” • “Is ashwagandha safe to take long-term?” • “How does ADHD present in adult women?” •…
- IBI built a tool that generates quizzes from documents using LLMs2025 · ▲10
Hey everyone! I recently built this little side project that takes any document you upload and turns it into practice quizzes using LLMs to generate the questions: https://www.cuiz-ai.com Being a backend engineer, I have always struggled to finish my side projects due to my awful frontend skills. Now, with the progress of AI coding tools, I had no more excuses. 100% of the frontend, landing page and even the logo was made using a combination of Cursor, ChatGPT and Claude, but it's always been under my supervision and never blindly accepted the proposed changes. The backend 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.
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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, May 2026
the whole month →

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