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This article investigates the intersection of Artificial Intelligence (AI) with the space economy and its profound geopolitical implications. Artificial intelligence is increasingly powering space missions, satellite networks and resource utilization, thereby reshaping the global landscape of the space industry. AI-driven advances are fueling economic opportunities and competition among nations in space-related sectors and the resulting geopolitical effects. From satellite services to lunar and Martian exploration, AI is poised to become a driving force in shaping the balance of power in the space arena, making it a critical topic for policymakers, strategists and industry leaders.

In contemporary society, artificial intelligence (AI) impacts human lives to different extents, including reshaping the public's creative experience. Software and programs enable users to create images from scratch, notwithstanding their actual knowledge or competencies. The visual art system is currently facing an ongoing democratization process, in which the distance separating the creator and the informatic algorithm is gradually fading. Therefore, there is a growing need to analyze AI's implications on the creative process. The paper will analyze the different software and websites providing image- generating services while discussing their impact on society as a whole.

Piena operatività delivery in Cina, esperimenti in USA e a Milano. Il fondamento dell'impianto cartografico 3D si fa stringente, necessario e improrogabile

In late 2022, the Bologna Technopole unveiled its latest pre-exascale supercomputer, Leonardo. This new supercomputer facility will support a wide range of scientific research and Cultural Heritage initiatives, offering exciting possibilities for various fields of knowledge, particularly in the areas of Big Data and Artificial Intelligence. Cineca VisitLab is actively engaged in multiple EU projects that are expected to greatly benefit from the cuttingedge capabilities of this advanced technology.

Considering the remarkable historical, artistic, monumental, demoethno-anthropological, archaeological, archival and national library heritage, in order to improve the management and safety of places of culture, it becomes essential to focus attention on the new 6G technology which will allow the fusion of digital world with the physical world capable of transmitting huge amounts of data and information in seconds. The places of culture (archaeological areas, archaeological parks, museums, monuments, archives, libraries), like other built places, thanks to 6G technology and its flexibility, versatility, sustainability, reliability, will be able to become completely interconnected.

Mountain areas include precious environments like pastures that require preservation strategies by the appointed authorities. Here we present a system that processes orthophotos acquired by Agenzia per le Erogazioni in Agricoltura using Artificial Intelligence to reduce the time and costs of human inspection in pasture management activities. The system is trained to automatically classify multiple kinds of pasture and no-pasture areas. A user interface allows to query and refine the pasture maps. The map can be updated as new orthophotos come in. The system achieves good performance in the Provincia Autonoma di Trento (PAT), but it is suitable for similar mountain areas as well.

JOHN MCCARTHY, computer scientist at Stanford University, first coined the term "artificial intelligence” in 1955, defining it as, "the science and engineering of making intelligent machines, especially intelligent computer programs.” Machines are intelligent when they can replicate human cognitive skills such as forming categories, recognizing patterns, and solving problems. For machines to achieve artificial intelligence, computer programmers must create algorithms that can scan and organize input data to train and teach the machines to perform tasks. This method is called machine learning, the most basic of all AI techniques. Several other AI methods have since been developed, including neural network, a process that mimics how the human brain learns by using interconnected nodes to process data. Its more sophisticated version is called deep learning, which uses multiple layers of neural networks so that computers can analyze bigger datasets. With the advent of big geospatial data, there are far more inputs for AI machines to train on and improve their accuracy. And due to AI's ability to handle big datasets such as imagery, computer vision is currently one of the hottest geospatial applications. With computer vision technology, machines can be taught to "see” real-world objects from images, thus allowing companies like Mapillary to identify roads from street photos, Ecopia to extract built-up areas from satellite imagery, and VOXELGRID to recognize construction materials from a point cloud.

Description and graphic illustration of an hybrid technique for the automatic registration of RGB images captured with drone and proximity photogrammetry, thermal images and 3D laser scanner. Automatic restitution of reliefs of the deterioration of the building in schedules and tables starting from the point cloud, representation and automatic measurement of the progress of the works. Using AI during acquisition and post processing of datasets.

Point clouds, generated by photogrammetry or laser scanning, mainly contain geometric information. This makes them not very useful for different applications. Artificial Intelligence methods have opened up a new area of research and development, providing automatic solutions for segmentation and classification purposes.