Federated Learning for AI Analytics
Discover how federated learning enabled by AI can process high volumes of data in decentralized systems to increase performance, security, and deep insights for business intelligence.
Federated Learning is Next-Gen Business
Federated learning, meaning robust AI with an intuitive learning model, is the leading edge of AI analytics.
Extract high-value data from IoT devices using edge networks, a distributed data learning model, and AI.
Preserve data integrity, privacy, and security through homomorphic encryption with federated learning and Intel® Software Guard Extensions (Intel® SGX) technology.
Gain insights from a particular device or part of the system vs. an entire data set using AI with federated learning.
Converging Edge, Cloud, Data Center Computing, and AI
Federated learning securely turns big data into smart data by identifying problems and patterns.
Data remains securely with the owner without impacting data training algorithms.
AI is dynamic with rapid advancements; early adopters will remain competitive in their markets.
Enterprises will continue to grow and optimize their use of advanced analytics and AI. Ninety-eight percent of organizations say that analytics are important to driving business priorities, yet fewer than forty percent of workloads are leveraging advanced analytics or artificial intelligence.1
Data is all around us, and it's changing how we do business. The ability to use this data to compete and innovate will set the winners apart from the losers. Research shows that, with analytics and AI tools, you are five times more likely to make faster decisions than your competitors.2