Industry 4.0 depends on continuous data exchange between sensors, machines, production lines, and enterprise systems, but much of this data cannot be centralized due to privacy, security, and ...

Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, traditional ...

Enterprise AI adoption is widespread in ambition and uneven in execution. Across industries, organizations are experimenting with machine learning and generative models, training teams, and deploying ...

Federated Learning 2 Authors, Creators & Presenters: Cheng Zhang (Hunan University), Yang Xu (Hunan University), Jianghao Tan (Hunan University), Jiajie An (Hunan University), Wenqiang Jin (Hunan ...

The Great Power Competition is no longer confined to traditional warfare. It plays out in data, algorithms and artificial intelligence (AI). As adversaries weaponize misinformation and cyber attacks ...

As the use of Unmanned Aerial Vehicles (UAVs) expands across various fields, there is growing interest in leveraging Federated Learning (FL) to enhance the efficiency of UAV networks. However, ...

Each year, cyberattacks become more frequent and data breaches become more expensive. Whether companies seek to protect their AI system during development or use their algorithm to improve their ...

Danske Bank, Credit Suisse, Santander Bank UK, USAA Federal Savings Bank and Wells Fargo have all been subjected to significant fines, collectively amounting to about $2.2 billion, for various ...

Not only can federated learning reduce costs, but it can also increase the effectiveness of anti-money-laundering, say Gary Shiffman, Shelly Liposky and Rick Hamilton. Financial institutions can help ...