I Built a Fully Local AI Voice Assistant (No Cloud, Open Source) скачать в хорошем качестве

I Built a Fully Local AI Voice Assistant (No Cloud, Open Source)

I built JARVIS — a fully local, GPU-accelerated AI voice assistant that runs entirely on my PC with zero cloud dependency. This 3-minute demo shows wake word detection, voice commands, live web research, document generation, and desktop control — all powered by a local LLM running on an AMD GPU. Everything runs on-device: speech recognition, language model, text-to-speech. No subscriptions, no API costs for core functionality, no data leaving your machine. == TIMESTAMPS == 0:01 - Wake word & basic voice commands 0:11 - Real-time web research 1:09 - Document generation (PPTX/DOCX/PDF) 1:42 - Desktop & application control 2:06 - Multi-skill demo 2:35 - News headline rundown & wrap-up == TECH STACK == • LLM: Qwen3-VL-8B (Q5_K_M, local via llama.cpp + ROCm) • STT: Fine-tuned Whisper (CTranslate2, Southern US accent) • TTS: Kokoro 82M (CPU inference) • GPU: AMD RX 7900 XT (20GB VRAM) with ROCm • Wake Word: Porcupine • Intent Matching: Semantic (sentence-transformers) • 11 active skills == LINKS == GitHub: https://github.com/InterGenJLU/jarvis Setup Guide: https://github.com/InterGenJLU/jarvis/blob... == WHAT MAKES THIS DIFFERENT == Most "AI assistants" are thin wrappers around cloud APIs. JARVIS runs a full 8B-parameter vision-language model locally on consumer AMD hardware. Speech recognition is fine-tuned for my accent. The entire pipeline — wake word, STT, LLM reasoning, tool use, TTS — executes on-device with sub-second latency. Built for privacy-first personal productivity. No telemetry, no cloud accounts required. #LocalAI #OpenSource #VoiceAssistant