Technology posts

‍‍In today's fast-paced business landscape, artificial intelligence (AI) and machine learning (ML) have become instrumental in many business processes. MLOps is a rapidly growing field that is revolutionizing the way Machine Learning models are being deployed and managed. By using MLOps in the Edge, organizations can take advantage of the benefits of local processing, increased security and privacy, and reduced bandwidth usage. This article delves into the advantages and challenges of deploying ML in the Edge.

Gartner's Emerging Technologies and Trends Impact Radar shows IT leaders where to capitalize on market opportunities. Its latest feature for 2023 points to EDGE AI as the next breakthrough technology. With the growing demand for real-time AI solutions and the need for decentralized data processing, AI at the Edge has been positioned as a critical technology this year.

As organizations adopt Edge Computing and Edge AI to power real-time decision-making in industrial environments, traditional tools like Kubernetes fall short. This article explores the evolution from monolithic systems to containerized microservices, the limits of Kubernetes at the edge, and how Barbara’s platform empowers secure and scalable orchestration in distributed, offline, or resource-constrained scenarios.

Artificial Intelligence and Machine Learning are the most popular technologies used to create intelligent systems and although they are related, they are not the same. Because of this relationship, when you look at Artificial Intelligence versus Machine Learning, you are actually analyzing their interconnectedness.

As the market moves from proof of concepts to large multi-application deployments that require scalability, different technological alternatives emerge at the Edge. In this article, we explore the foundation for a successful Edge Computing project.

The true potential of Industrial IoT can only be achieved through the introduction of Artificial Intelligence. In this article we will go beyond IoT and will focus on Data Analytics and Data exploitation because for us IoT without Big Data is nothing.