Technology posts

This is the first article of a new series we will be producing to cover the complexities of this journey towards the full IT-OT convergence in industrial companies.

When implementing a data-based strategy, it all starts with the Data. One of the typical sources to extract data are IoT devices. Knowing which IoT communication protocols exist and how to use them for data communication is essential as they are the ones that make data gathering from them possible.

According to a recent IBM study, nearly 77% of industrial companies are either actively working with or planning to adopt AI and Machine Learning to optimize operations or unlock new revenue streams. In this landscape, Machine Learning Operations (MLOps) is emerging as the essential framework for Data and Infrastructure teams, streamlining workflows and driving successful AI implementation.

In industrial manufacturing, the cement industry is notable for its considerable environmental impact and high energy usage. Amid increasing environmental concerns and a drive towards sustainability, edge computing presents innovative solutions to improve supply chain efficiency, sustainability, energy conservation, and product traceability.

According to Gartner, “The technology or service offering must be innovative, impactful and available for purchase for a Cool Vendor.” With Barbara, companies can deploy, run, and manage their models across distributed locations, as easily as in the cloud.

As artificial intelligence continues to advance, the need for real-time, adaptive, and efficient AI systems becomes increasingly critical. In this article, we dig in into how edge computing complements and enhances adaptive AI, enabling intelligent applications to thrive in diverse and dynamic environments. Join us as we explore the revolutionary synergy between edge computing and adaptive AI.