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.

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.

AI is transforming the way businesses operate, but it also introduces new security concerns. Companies must protect their data from cyberattacks, comply with data protection regulations, and ensure their AI models are ethical and transparent. Deploying AI at the Edge can provide a secure infrastructure for private, compliance, and secure AI deployment.

Do you want to know how you can monitor all your distributed assets and regain control over them? Join us on April 18th at 17:30 to our DEMO & BEERS together with Mytra at Advanced Factories.

We have seen especially during the last few months how model releases with billions of parameters requiring high processing power have been reproduced. On the other hand, there is also a growing trend that revolves around the ability to run lightweight models in real-time without the need for constant connection on low-power devices such as microcontrollers, sensors, and other embedded systems which is also revolutionizing the AI industry. This trend is known as TinyML.

Under the name SEC2GRID, Barbara together with Ingeteam, Iberdrola, Ormazabal, Arteche, PwC, Zigor ZIV, Ikerlan and the GAIA Cluster will provide cybersecurity to the electricity grid. A collaborative framework composed of competing companies that will extend to 2024 with a total investment of €6.4 million.