Add Sentinel Vision Navigator progress log

README.md

@@ -84,4 +84,37 @@ model.eval()
 
 ## Next Phase Direction
 
-The recommended next phase is a controlled SFT/auto-critic cycle: train from the pretrain anchor plus selected v2 weights only after passing format probes, prioritize executable Python/TypeScript/code-repair datasets, reject non-compiling generations, and benchmark every 250-500 steps before continuing.
+The recommended next phase is a controlled SFT/auto-critic cycle: train from the pretrain anchor plus selected v2 weights only after passing format probes, prioritize executable Python/TypeScript/code-repair datasets, reject non-compiling generations, and benchmark every 250-500 steps before continuing.
+
+<!-- sentinel-vision-navigator-progress-2026-05-07 -->
+
+## Sentinel Vision Navigator Progress Log
+
+**Date:** 2026-05-07  
+**Hackathon:** AMD Developer Hackathon  
+**Tracks:** Vision & Multimodal AI, AI Agents & Agentic Workflows, Fine-Tuning on AMD GPUs, Hugging Face Space
+
+Sentinel Vision Navigator is now connected to this model page as the applied assistive-AI product layer for the SentinelBrain roadmap. The public prototype focuses on blind and partially sighted users who need immediate, camera-first understanding of their surroundings.
+
+### Current build
+
+- Public web demo: https://amdvision.qubitpage.com/
+- Hugging Face Space: https://huggingface.co/spaces/lablab-ai-amd-developer-hackathon/sentinel-vision-navigator
+- Whitepaper PDF: https://amdvision.qubitpage.com/downloads/sentinel-vision-whitepaper.pdf
+- Pitch deck PDF: https://amdvision.qubitpage.com/downloads/sentinel-vision-pitch-deck.pdf
+- Android APK distribution path: https://amdvision.qubitpage.com/downloads/sentinel-vision.apk
+
+### Implemented application features
+
+- Live camera scene analysis for blind mobility prompts.
+- Camera-first local navigation behavior for commands such as `guide me`, `get out`, `avoid obstacles`, and `which way`.
+- Embedded vision-direction RAG knowledge for indoor paths, outdoor sidewalks, stairs, curbs, text reading, and object finding.
+- Fluent English speech output with calmer, shorter instructions.
+- Android first-run setup for camera, mic/speech, contacts, location, email handoff, WhatsApp handoff, SMS, and calls.
+- Multitasking agent routing for navigation, calls, SMS, WhatsApp, email, maps, app opening, battery, time, text reading, object finding, and conversation.
+- 3D Terminator-style camera HUD with reticle, scan line, perspective grid, connector status, and detected-object chips.
+
+### Model status note
+
+The production demo currently uses Akash-hosted Qwen multimodal inference for visual reasoning while SentinelBrain-14B-MoE-v0.1 remains the project model artifact and training/progress page for the specialized assistant roadmap. The next step is to collect interaction traces and evaluate a fine-tuned SentinelBrain navigation/router layer on AMD GPU infrastructure.
+