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🤓 Latest Submissions
AURA: Offline Autonomous Voice Agent
Most voice assistants force a compromise: either give up your private voice data and sensitive files to cloud servers, or settle for rigid, basic voice commands. AURA eliminates this trade-off by bringing autonomous, multi-step voice intelligence directly onto local hardware. Built to run locally with optional AMD ROCm hardware acceleration, AURA listens to spoken instructions, reasons through complex multi-step goals, executes local tools, and speaks back in real time. Whether you need to search private project files, draft summaries, calculate figures, or check calendar schedules, AURA plans and carries out the work while keeping your audio and documents entirely on your device. Key highlights of AURA include: • Autonomous Agent Engine: AURA breaks down broad voice requests into clear tool actions—such as searching local documents, querying file contents, and generating drafts—with explicit permission controls before executing modifications. • Hardware-Accelerated Local RAG: Indexes local PDF, Markdown, and text files using vector embeddings to answer questions with verifiable source citations, powered locally on AMD GPUs. • Real-Time Event Architecture: Uses FastAPI and WebSockets for low-latency voice streaming, instant status timelines, and dynamic feedback. • Privacy-First Design: Full offline capability with zero reliance on cloud services or external databases, persisting data strictly in local storage. AURA demonstrates how powerful, practical, and private personal AI assistance can be when built directly for local desktop hardware.
30 Sep 2026
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ForgeSight AI — AMD-Powered Predictive Maintenance
Unplanned machine failure costs the global manufacturing industry over $50B annually. Industrial plants capture gigabytes of high-frequency SCADA sensor streams every minute, yet operators still rely on reactive maintenance or rigid threshold alarms that trigger too late. ForgeSight AI is an end-to-end industrial intelligence platform designed to detect anomalies, predict equipment failures, explain root causes, and prescribe preventive actions before catastrophic downtime occurs. Built for AMD hardware architectures, ForgeSight AI executes a continuous 7-phase intelligence pipeline: 1. Real-Time SCADA Telemetry Ingestion: Continuously monitors vibration harmonics, thermal drift, pressure differentials, and RPM across machine fleets. 2. Machine Learning Anomaly Detection: Employs unsupervised multivariate Isolation Forest and ensemble models accelerated via AMD ROCm matrix cores for 3.8x faster inference. 3. Time-to-Failure (TTF) Risk Scoring: Calculates remaining risk horizons (e.g. 24–48 hours) and failure probabilities with contributing sensor factors. 4. Computer Vision Surface Defect Scanner: Inspects industrial parts (spindles, bearings, welds) with bounding-box defect localization (fatigue cracks, pitting, misalignment). 5. Semantic Technical SOP Search: RAG engine that queries engineering manuals to retrieve exact repair procedures, torque specs, and replacement parts. 6. Financial ROI & Downtime Avoidance: Dynamically computes saved maintenance hours and bottom-line dollar value per prevented incident. 7. Human-in-the-Loop Operator Console: Fully responsive Next.js 16 control dashboard featuring mobile emergency alert triaging and work order approval workflows. ForgeSight AI transforms factories from reactive firefighting into proactive, high-precision operations.
1 Dec 2026
