Generative AI: Advanced Technologies, Applications, and Impacts

Dear Colleagues,

The recent successes and the widespread popularity of Generative AI have attracted growing interest and opened up new opportunities, not only in terms of the exploitation of Generative AI tools in several application domains, but also in terms of its novel scientific/technological challenges, e.g., making it more decentralized and edge-based in cloud continuum deployment environments. As a notable example, Generative AI models such as Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) are capable of creating high-quality content in diverse modes (including text, images, videos, etc.) and improving/accelerating several research/business tasks in many sectors, such as via dataset augmentation for simulations and digital twins. These capabilities bring enormous opportunities to a wide range of research areas, for both basic and applied research. Actual applications range from humanities and social sciences to pharmacy and medicine and include innovative AI-driven drug design and healthcare.

This Special Issue aims to provide a fresh and up-to-date publication venue for researchers and practitioners to share novel and high-quality contributions related to all aspects of Generative AI, from associated technologies and advancements to novel fields of applications and related tools and lessons learned from performance evaluation and experiences over large-scale testbeds.

Topics of interest for the Special Issue include, but are not limited to, the following:

• Generative AI for digital twinning;
• Generative AI for edge computing and edge-based Generative AI;
• Metaverse applications exploiting Generative AI;
• Generative AI under runtime and dynamic quality (e.g., time latency) constraints;
• Internet and B5G infrastructure support for Generative AI;
• Privacy and security of Generative AI impactive federated learning and trusted execution environments;
• Benchmarking Generative AI solutions in different scientific and application domains, including AI-guided drug design and healthcare;
• Generative AI’s use of software tools.
• Applications and case studies. 

Prof. Dr. Claus Jacob
Prof. Dr. Paolo Bellavista
Dr. Ognjen Arandjelović
Guest Editors

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• generative AI
• digital twins
• edge computing
• cloud continuum
• AI in medicine