SaralReport
Understand Medical Reports Without Confusion
What it does
SaralReport helps families understand confusing medical reports, blood tests, and doctor prescriptions using AI-powered explanations in simple Hindi & English. Key features: • AI-powered medical report analysis • Hindi + English explanations • Family Health Vault • Medicine reminders • WhatsApp sharing for parents & family • Secure and private health storage Built for normal people, parents, and families not medical experts.
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LineaJ (pronounced "lineage")Jun 2026 · lineaj.io · ▲6Personal and family health records, on your device
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This prototype makes use of Open AI’s davinci model to identify and subsequently redact potential protected health information (PHI) or personal identifying information (PII) within the provided input. The output will be a de-identified version of the original input, where both direct and indirect identifiers - like those mentioned above - have been redacted. This ensures that the resulting output is HIPAA compliant, and We encourage you to test and play around with this tool - no input or output data is stored or saved. Feedback is welcomed - let us know what you think either at…
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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?” •…
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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…
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