Industry at the Edge posts

In today's fast-paced and competitive landscape, optimizing operations is crucial for success. With the advent of cutting-edge technologies like Edge Computer Vision, businesses can gain a significant advantage by leveraging real-time data analysis and decision-making. In this article, we will explore what industries need to know about optimizing operations with Edge Computer Vision and how this transformative technology can propel their growth.

Artificial Intelligence (AI) is revolutionizing all industries, providing new opportunities and challenges for growth and innovation. However, with great power comes greater responsibility. The European Union (EU) has recognized the urgent need for ethical and transparent AI practices to protect individuals' rights and to ensure fair and accountable use of AI technologies. This article aims to guide companies on what they must do to comply with EU AI regulations.

‍‍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.

With the rapid growth of artificial intelligence, the environmental impact of AI is a hot topic. Green AI aims to create sustainable, energy-efficient, and environmentally-friendly AI systems. However, achieving this goal requires a combination of different technologies and one of the most critical ones is Edge Computing. In this article, we'll explore Green AI, its importance, and the critical role of Edge Computing in its success.

The main goal of virtualization is to provide a new operational environment, which is not bound to any computer hardware or operating system. Hardware components are typically designed to be robust and reliable, but they can also be expensive and difficult to modify or upgrade. Separating hardware from software allows for the software to be updated or modified without affecting the hardware.

Replay this webinar given by some of the top leaders in AI in Spain about the most important Machine Learning applications and how their deployment is getting closer to the source of data to ensure privacy and enable real-time decision making.