Framework for Auditable Edge MLOps
4 minutesUnderstand the governance framework for auditable edge MLOps, ensuring compliance with AI principles and robust audit trails.
Framework for Explainable Edge MLOps
12 minutesLearn about methods for making edge MLOps transparent and explainable, facilitating better understanding and trust in AI systems.
Framework for accessing privacy accuracy trade-off in FL
14 minutesDiscover techniques to balance privacy and accuracy in AI models, optimizing both for enhanced data protection and performance.
Fortifying AI Against Adversarial Attacks in Federated Learning
19 minutesExplore a framework for fortifying federated learning against adversarial attacks, ensuring secure and robust AI deployments.
OctaiPipe’s Federated XGBoost Implementation for Enhanced Data Privacy
8 minutesFLeXGBoost improves communication efficiency, reduces power consumption, and enhances data privacy while maintaining high model accuracy.
The UK Water Industry’s Transformation with Federated Edge AI
12 minutesLearn about the potential of federated edge ai in the water industry, which OctaiPipe and Arup have collaborated on.
Federated Learning and Trust: Building Trustworthiness in Distributed AI Systems
11 minutesUnveil strategies for navigating security challenges, achieving privacy-accuracy equilibrium, and ensuring model explainability across diverse edge devices.
