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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 ...

One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...

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.

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 ...