As organizations‘ appetite for seizing opportunities at the edge grow, scaling from a single use case in one facility to various uses cases in multiple locations poses a significant challenge. This article highlights the importance of implementing an Edge Management and Orchestration tool to efficiently and securely scale edge computing initiatives.
Most industrial companies (up to 77% according to a last-year study by IBM) are working or planning to work with AI and Machine Learning as a means to optimize their operations or enable new revenue streams. And Machine Learning Operations (MLOps) is becoming the paradigm as a work framework for the Data and Infrastructure teams involved.
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.
Edge Computing helps in integrating Information, Operation, and Engineering technologies since it converts data into valid information for real-time decision-making and can relate data coming from IT, OT, and ET systems, which can be difficult to integrate due to their very different origins. In this article written by Daniel Garrote, we dig into the different systems and the role of Edge Computing in helping integrate all these systems.