Technology posts

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.

The purpose of this article is to help the industrial ecosystem (service providers, integrators,, companies...) to better understand the industrial landscape of Edge technology. It is known that by 2026, 30% of packaged enterprise capabilities will be deployed on the Edge with integrated resources (gateways with local compute) to drive inference and business outcomes on nearby data. Find out more on the survey we conducted over 200 industrial companies.

Industrial IoT is transforming the way plant environments operate by enabling hyper-connected networks that provide value through smart factories, predictive maintenance, energy management, remote monitoring, and more. This technology empowers industries to optimize productivity, increase efficiency, and reduce costs.

As the number of connected devices increases, so does the amount of data generated. This ability to analyze data, extract insights from it and make autonomous decisions based on the analysis is the essence of Artificial Intelligence (AI) of things, also known as AIoT.