Conventional ML training has the safety concern of collecting all data in a single place and violating the privacy of the data owners. DLFi aims to solve this.
DLFi is a Privacy-Preserving AI-as-as-Service (PP-AIaaS) solution. It provides a training environment on remote sites without necessarily displacing or transferring the data. It enables data providers to train a ML model without revealing their business-critical data to each other. DLFi offers communication-efficiency and guarantees the privacy of data owners.
Features
- Privacy-Preserving
- Cloud-Native
- Modular and Pluggable
- Customized Visualization Dashboard
- GPU-Acceleration Support
Applications
- ML Model Training over Geo-distributed Data Sources
- Collaborative ML Model Training in Multi-domain Multi-vendor and Disaggregated Networks
- Shared Governance and Ownership of ML Models
Implemented Use-cases
- QoT Estimation in Multi-domain Multi-vendor Optical Networks
- Vision Inspection for Quality Assurance in Factory Shop Floors
Interoperability
Relevant Projects
- AI-NET-PROTECT
- Zero SWARM
- QuNET+ML
Previous Demonstrations
- Demonstration of Federated Learning over Edge-Computing Enabled Metro Optical Networks at ECOC 2020