Devdiscourse

Financial institutions turn to blockchain and federated AI for secure fraud detection

The review reports that blockchain-enhanced federated learning systems typically achieve slightly lower raw accuracy than ...
EurekAlert!

Federated metadata-constrained iRadonMAP framework with mutual learning for all-in-one computed tomography imaging

FedM2CT consists of 3 modules, i.e., task-specific iRadonMAP (TS-iRadonMAP), condition-prompted mutual learning (CPML), and federated metadata learning (FMDL). TS-iRadonMAP performs the local CT image ...
EurekAlert!

FTI-SLAM: federated learning-enhanced thermal-inertial SLAM

The workflow of FTI-SLAM framework. The SLAM front-end comprises federated learning-enhanced deep neural networks for odometry, embedding, and loop closure detection. After optimising odometry based ...
InfoWorld

Federated learning: The killer use case for generative AI

Let’s imagine a fictional company, Global Retail Corporation, a multinational retail chain struggling with its initial approach to AI integration. They built custom generative AI applications on their ...
Forbes

IBM Federated Learning Research - Extracting Machine Learning Models From Multiple Data Pools

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.