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Release Notes

Barbara platform release 2.8.0: New AI frameworks, improved network management and much more

One of the key goals of the Barbara platform is to support data scientists and AI engineers in deploying their algorithms with minimal friction. In line with this, our latest release, version 2.8.0, introduces several new features, including support for additional development frameworks like ONNX and Pytorch, as well as GPU support, among others. However, these are just a few of the enhancements in the 2.8.0 release. Let’s take a closer look at all the updates.

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Adaptive AI and the Role of Edge Computing

As artificial intelligence continues to advance, the need for real-time, adaptive, and efficient AI systems becomes increasingly critical. In this article, we dig in into how edge computing complements and enhances adaptive AI, enabling intelligent applications to thrive in diverse and dynamic environments. Join us as we explore the revolutionary synergy between edge computing and adaptive AI.

Technology

Edge Computing as a solution to achieve the convergence between IT, OT and ET

Edge Computing helps in integrating Information, Operation, and Engineering technologies since it converts data into valid information for real-time decision-making and can relate data coming from IT, OT, and ET systems, which can be difficult to integrate due to their very different origins. In this article written by Daniel Garrote, we dig into the different systems and the role of Edge Computing in helping integrate all these systems.

Technology

How Edge Computing drives Maritime Business Revolution through Energy Optimization

Edge Computing plays a pivotal role in revolutionizing the marine business, particularly in the domain of energy optimization. By bringing computing resources closer to the data source, edge computing enables real-time data processing and analysis onboard ships and marine installations. This paradigm shift allows for more efficient energy management and optimization, leading to significant cost reductions and a reduced environmental impact.

Technology

Overcoming the Challenges of Deploying Computer Vision Models at Scale

Deploying computer vision models in production is a complex endeavour that requires a holistic approach that encompasses data, models, infrastructure, and processes. By addressing the challenges of data acquisition, model selection, infrastructure, CI/CD, monitoring, and ethical considerations, organizations can successfully deploy computer vision models at scale. Thibaut Lucas, CEO and Co-founder at Picsellia shares his view on both, the business and technical aspects surrounding the challenges of deploying Computer Vision at scale.

Industry at the Edge

Barbara platform release 2.5.0: Unleashing the Power of Edge Applications with Barbara Marketplace

Our mission has always been to empower industrial companies to harness the full potential of edge computing. That's why we are proud to unveil Barbara Marketplace, an extraordinary repository of edge applications that will revolutionize the way you do business.

Release Notes

Smart and cybersecure machines with Edge technology: A vision of the industrial future.

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 automation and decision making . In this talk we address the key role of an Edge Platform as a solution to overcome the Data Gravity issue of the Cloud.

Smart Manufacturing
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Resources

Industrial Energy Efficiency Plan 2023

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How Edge Computing is changing the Industrial sector

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The state of cybersecurity in industry (only available in Spanish)

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