Show HN: Sentence Starters – Phrases for academic and professional writing https://ift.tt/MD2RLdn

Show HN: Sentence Starters – Phrases for academic and professional writing https://ift.tt/rBZ9jMA December 21, 2025 at 11:45PM

Show HN: I built a job board that filters "Ghost Jobs" in the Middle East https://ift.tt/64QiDkv

Show HN: I built a job board that filters "Ghost Jobs" in the Middle East https://camels.work/ December 21, 2025 at 07:07AM

Show HN: Ava – open-source AI voice assistant that runs in the browser https://ift.tt/BOA6qzy

Show HN: Ava – open-source AI voice assistant that runs in the browser Hi HN, I built a voice assistant that runs entirely in the browser. No backend, no API calls. Everything runs on your device. The goal was to see how far browser based AI has come, and whether a full voice pipeline can work client side with acceptable latency. How it works - Speech to text: Whisper tiny en via WebAssembly - LLM: Qwen 2.5 0.5B running via llama.cpp WASM port - Text to speech: Native browser SpeechSynthesis API Responses stream in real time. TTS starts speaking as soon as a sentence is generated instead of waiting for the full reply. After the first load, it works completely offline. Nothing leaves the device. Why this matters: - Shows what is now possible with modern browsers, small LLMs and WASM Caveats: - Requires Chrome or Edge 90+ due to SharedArrayBuffer for WASM threading - Around 380MB initial download, cached after - English only for now - The 0.5B model is limited, but small enough to run locally Tested on macOS and Linux desktop browsers. I could not get this working reliably on mobile yet due to memory and threading limits. Getting all of this working in the browser took far longer than expected due to many low level WASM and browser issues. Demo https://ava.muthu.co Source https://ift.tt/qWfGUTP I would love feedback, especially from anyone experimenting with local AI or browser based ML, and ideas on improving performance or mobile support. https://ava.muthu.co/ December 21, 2025 at 05:14AM

Show HN: ArkhamMirror – CIA's Analysis of Competing Hypotheses, Runs in Browser https://ift.tt/74gI9SX

Show HN: ArkhamMirror – CIA's Analysis of Competing Hypotheses, Runs in Browser After adding a fully guided, AI-assisted Analysis of Competing Hypotheses (ACH) feature to ArkhamMirror, my privacy-first open-source Investigative analysis platform, I kept hearing the same request: "I just want to try ACH without setting up Docker and databases." Message received. I built a standalone version that runs entirely in your browser. Live tool: https://mantisfury.github.io/ArkhamMirror/ach/ Full ArkhamMirror repo: https://ift.tt/PN1LGOl What it does: Implements Heuer's 8-step ACH methodology (the CIA technique for avoiding confirmation bias) Guides you through identifying hypotheses, gathering evidence, building the consistency matrix, and running sensitivity analysis Exports to JSON, Markdown, or PDF Privacy model: All data stored in browser localStorage Zero network calls after initial page load except to/from your AI provider (if applicable) No backend, no accounts, no telemetry Works offline once loaded Built as part of ArkhamMirror, a 100% local investigative platform I made as a non-coder using AI assistants. Optional AI assistance: Connect your own API key (OpenAI, Groq) for AI-powered suggestions Or use local LLMs (Ollama, LM Studio, local Anthropic through proxy) if you run it locally The AI helps suggest hypotheses, evidence items, and ratings – but you make all decisions Why standalone? The full ArkhamMirror platform is powerful but requires Docker + databases. This gives journalists, analysts and anyone who's curious a zero-friction way to try the ACH methodology immediately. Analysts have been stuck with crappy spreadsheets for a long time. Now they (and you) have a free upgrade. Source: https://ift.tt/G9AJQ2p... If you try it out, please let me know what you think. https://mantisfury.github.io/ArkhamMirror/ach/ December 20, 2025 at 10:45PM

Show HN: ZXC – Asymmetric, +40% decode vs. LZ4 on ARM (C, BSD-3, Fuzzed) https://ift.tt/wh8QKrd

Show HN: ZXC – Asymmetric, +40% decode vs. LZ4 on ARM (C, BSD-3, Fuzzed) https://ift.tt/SgrFoQa December 17, 2025 at 10:18AM

Show HN: I built an interactive 3D brain viewer (DK Atlas) https://ift.tt/jWPTa0M

Show HN: I built an interactive 3D brain viewer (DK Atlas) I was struggling to understand neuroscience and the word associations between technical terms and where the locations are (anatomically) And quite some of my neuroscience friends are loving it. https://ift.tt/dyip8CT December 20, 2025 at 10:52AM

Show HN: Dbzero – Code as if you have infinite RAM (Python persistence engine) https://ift.tt/YNsoIgh

Show HN: Dbzero – Code as if you have infinite RAM (Python persistence engine) https://ift.tt/f50NFae December 20, 2025 at 09:07AM