Can we acknowledge that our relationship with nature has evolved from human dominance to an intimate interconnectedness, recognizing that nature has genuinely attained a form of "personhood," and that artificial intelligence (AI) can facilitate this transforma - tion, serving as a novel medium for human-nature connection? This article begins by examining the critical role of AI at the heart of the urgent ecological transformation currently underway, exploring the paradigm shift emerging from the intersection of AI and non-human life. The discussion progressively narrows its focus to how this innovative AI-nature paradigm manifests specifically within the fields of art and design, highlighting its distinctiveness from traditional artistic and design media. The article seeks to explore how various artists and designers incorporate AI into ecological, microbiological, and geophysical creative practices. Through a comparative analysis of their creative strategies, it elaborates on the relationship between different applications of AI--such as data analysis, image recognition, and ecological restoration--and their unique artistic expressions, while also considering the extended value inherent in AI-driven art and design. However, the precise value of this emergent design paradigm remains subject to ongoing discourse.

Faulty wind turbine blades can incur huge costs for the companies that operate them, especially if the defects go unnoticed until it's too late. That's why quality assurance is such a strategic issue for global wind-turbine manufacturers. Today, quality inspections are limited to surface inspection of limited areas as these composite structures roll off the production line. But under a new approach co-created by EPFL and University of Glasgow researchers, inspection engineers can use a new patented radar technology, combined with an AI assistant, to detect possible anomalies beneath the surface. This approach has many advantages: it's non-destructive, non-contact, supports agile and rapid data acquisition and analysis, and requires very little power to operate.

As Artificial Intelligent (AI) technology advances and increasingly large amounts of data become readily available via various Industrial Internet of Things (IIoT) projects, we evaluate the state of the art of predictive maintenance approaches and propose our innovative framework to improve the current practice. The paper first reviews the evolution of reliability modelling technology in the past 90 years and discusses major technologies developed in industry and academia. We then introduce the next generation maintenance framework - Intelligent Maintenance, and discuss its key components. This AI and IIoT based Intelligent Maintenance framework is composed of (1) latest machine learning algorithms including probabilistic reliability modelling with deep learning, (2) real-time data collection, transfer, and storage through wireless smart sensors, (3) Big Data technologies, (4) continuously integration and deployment of machine learning models, (5) mobile device and AR/VR applications for fast and better decision-making in the field. Particularly, we proposed a novel probabilistic deep learning reliability modelling approach and demonstrate it in the Turbofan Engine Degradation Dataset.

In Europe, 51 per cent of top global manufacturers use at least a single use case of AI in their operations. New Delhi: Europe is leading the implementation process of artificial intelligence (AI) in the manufacturing sector, claims a study by Capgemini Research Institute. More than half of European manufacturers are implementing AI use cases in the sector with Germany as the frontrunner. In Europe, 51 per cent of top global manufacturers use at least a single use case of AI in their operations. While, in Germany, 69 per cent of manufacturers are using AI in their operations, compared to 28 per cent in the US and 11 per cent in China, reveals the study.

Oracle Consulting Digital Experience (OCDX) are using Artificial Intelligence (AI) to create innovative solutions to help businesses adapt to modern demands and challenges. This blog will take a look at some of the exciting use cases and benefits available with our cutting-edge AI services. With the power of AI we are able to co-innovate with organisations to tackle specific challenges by tailoring solutions to their unique needs. An example of this is the ability to identify vehicles and examine those that flag up with issues, such as uninsured or overdue for an MOT, to help optimise safety on the road. By identifying potential hazards, public safety can be increased to prevent incidents.

Access to improved safety and control.