Volkmar Kunerth For the past decade, most AI processing has happened in centralized data centers. Companies sent data to the cloud, waited for a response, and paid for bandwidth and storage along the way. That model is breaking down. The alternative is edge computing: running AI directly on devices—sensors, cameras, industrial equipment—where the data originates. This isn't just faster. It's cheaper, more private, and often more practical for real-time decisions. The shift is

Unlocking Efficiency in Industry 4.0: The Role of Foundational Visibility in Robotic Systems Integration in the Context of Uptime and ROI...