AI Module
The AI Module is currently in development and will provide enhanced artificial intelligence capabilities for edge computing applications on the Compute Blade platform.
Current Status
The AI Module is actively being developed to bring machine learning and artificial intelligence capabilities directly to your Compute Blade setup. This module will enable:
- Edge AI processing without cloud dependencies
- Real-time inference capabilities
- Integration with popular ML frameworks
- Optimized performance for Raspberry Pi hardware
Planned Features
- Inference Engine
- ML Frameworks
- Hardware Acceleration
On-device Model Inference
- Support for TensorFlow Lite models
- ONNX runtime compatibility
- PyTorch mobile integration
- Quantized model support for faster processing
Supported Frameworks
- TensorFlow/TensorFlow Lite
- PyTorch
- OpenCV for computer vision
- scikit-learn for classical ML
- Custom model deployment tools
Performance Optimization
- GPU acceleration where available
- Multi-core CPU utilization
- Memory-efficient model loading
- Batch processing capabilities
Use Cases
Computer Vision
- Object detection and classification
- Facial recognition systems
- Quality control in manufacturing
- Security monitoring applications
Natural Language Processing
- Text classification and sentiment analysis
- Language translation for IoT devices
- Voice command processing
- Chatbot deployment at the edge
Predictive Analytics
- Sensor data analysis
- Predictive maintenance for industrial equipment
- Anomaly detection in real-time
- Time series forecasting
Development Roadmap
- Phase 1: Core inference engine development
- Phase 2: Framework integration and testing
- Phase 3: Hardware optimization and acceleration
- Phase 4: Documentation and example projects
- Phase 5: Community beta testing
Stay Updated
Check back for updates on the AI Module development progress and availability. Follow our GitHub repository for the latest developments and early access opportunities.
Coming Soon
The AI Module is expected to be available in Q3 2025. Early access will be provided to beta testers and community contributors.