Innovation posts

Barbara helps grid operators deploy and maintain algorithms in real-time while complying with the highest cybersecurity standard

We dig in into how edge computing complements and enhances adaptive AI, enabling intelligent applications to thrive in diverse and dynamic environments.

Edge Computing is a critical driver in transforming the marine business, especially in the realm of energy optimization. By positioning computing resources nearer to the data source, edge computing facilitates real-time data processing and analysis directly onboard ships and marine installations.

As thousands of millions of assets are connected to the Internet the industrial world faces new challenges when it comes to connectivity and cybersecurity for real-time decisions. In this video we talk about the key role of Edge Platforms as a solution to overcome the Data Gravity problem.

TinyML has proven to be a powerful tool for implementing machine learning models in devices and environments with limited resources. In this article, we explore one of the ideal scenarios where this paradigm can be revolutionary.

With more data being collected every year, computing is shifting towards the edge, creating a big market opportunity for machine learning. This presents a unique moment for Machine Learning to adopt best practices for implementing Machine Learning in the Edge for AI and MLTeams looking to break into Edge AI. Join us on June 27, at the "Cutting - Edge of MLOPS" live webinar to gain insights into how to build compliant, efficient, and real-time Edge AI.