Streamline Control and Snowflake deliver a unified data foundation that helps energy organizations modernize faster and ...

Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...

Data is one of organizations' most potent assets in an era of growing competition and artificial intelligence (AI) mandates. However, effectively managing and using it requires balancing strict ...

Data-driven control represents a paradigm shift in the design and implementation of controllers for both linear and nonlinear systems. Eschewing traditional reliance on first‐principles models, this ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

Machine Design’s Motion Systems Takeover Week (Oct. 20–24, 2025) explored how the fusion of mechanical motion and data-driven control is reshaping high-precision applications across industries, from ...

In the modelic control paradigm, the first step is to establish a dynamic model through system identification. This model offers a continuous but inaccurate description of state transition information ...

Building a data-driven culture is a business transformation. Too often, organizations treat data initiatives as IT deployments, focusing on dashboards, data lakes and AI platforms. While these tools ...