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Generative Network Intelligence and Optimization Ecosystem – GENIE
GENIE (Generative Network Intelligence and Optimisation Ecosystem) aims to revolutionize network infrastructure management by proposing an approach combining the strengths of Large Language Models (LLMs) and network domain-specific expertise. This novel solution addresses the limitations of conventi
TowaRds Energy Efficient diStributed learning for 6G – TREES
TREES aims to reduce the carbon footprint of 6G networks by integrating distributed federated learning (DFL), as a tool for predicting orchestration actions and improving energy efficiency. DFL is an Artificial Intelligence (AI) paradigm, one of whose advantages is that it consumes less energy. To a
Semantic Communication for Future Networks – COMSEMA
Wireless networks are currently witnessing a radical shift from a purely data-oriented architecture to service and intelligent-based architectures, allowing hence the support of a diverse set of verticals. Thanks to the development of AI, future networks are expected to incorporate an even larger se
Trustworthy and Reliable Artificial intelligence for VEhicuLar networks – TRAVEL
Future networks are expected to be a platform of “connected intelligence “solving human and societal challenges. This concept, referred to as "native artificial intelligence (AI)", is regarded as one of the pillars of 6G. In this paradigm, intelligence will be integrated at various levels of the com
Transcending the Usual Rationale for the Future of Ubiquitous NETworks – TURFU-NET
The TURFU-NET project orchestrated by Quentin Bramas at the University of Strasbourg represents a pioneering initiative set to redefine network management and optimization through the integration of cutting-edge neurosymbolic Artificial Intelligence (AI). Spanning four years, this collaborative effo
