TY - JOUR
T1 - Large Generative AI Models for Telecom
T2 - The Next Big Thing?
AU - Bariah, Lina
AU - Zhao, Qiyang
AU - Zou, Hang
AU - Tian, Yu
AU - Bader, Faouzi
AU - Debbah, Merouane
N1 - Publisher Copyright:
IEEE
PY - 2024
Y1 - 2024
N2 - The evolution of generative artificial intelligence (GenAI) constitutes a turning point in reshaping the future of technology in different aspects. Wireless networks in particular, with the blooming of self-evolving networks, represent a rich field for exploiting GenAI and reaping several benefits that can fundamentally change the way how wireless networks are designed and operated nowadays. To be specific, large GenAI models are envisioned to open up a new era of autonomous wireless networks, in which multi-modal GenAI models trained over various Telecom data, can be fine-tuned to perform several downstream tasks, eliminating the need for building and training dedicated AI models for each specific task and paving the way for the realization of artificial general intelligence (AGI)- empowered wireless networks. In this article, we aim to unfold the opportunities that can be reaped from integrating large GenAI models into the Telecom domain. In particular, we first highlight the applications of large GenAI models in future wireless networks, defining potential use-cases and revealing insights on the associated theoretical and practical challenges. Furthermore, we unveil how 6G can open up new opportunities through connecting multiple on-device large GenAI models, and hence, paves the way to the collective intelligence paradigm. Finally, we put a forward-looking vision on how large GenAI models will be the key to realize self-evolving networks.
AB - The evolution of generative artificial intelligence (GenAI) constitutes a turning point in reshaping the future of technology in different aspects. Wireless networks in particular, with the blooming of self-evolving networks, represent a rich field for exploiting GenAI and reaping several benefits that can fundamentally change the way how wireless networks are designed and operated nowadays. To be specific, large GenAI models are envisioned to open up a new era of autonomous wireless networks, in which multi-modal GenAI models trained over various Telecom data, can be fine-tuned to perform several downstream tasks, eliminating the need for building and training dedicated AI models for each specific task and paving the way for the realization of artificial general intelligence (AGI)- empowered wireless networks. In this article, we aim to unfold the opportunities that can be reaped from integrating large GenAI models into the Telecom domain. In particular, we first highlight the applications of large GenAI models in future wireless networks, defining potential use-cases and revealing insights on the associated theoretical and practical challenges. Furthermore, we unveil how 6G can open up new opportunities through connecting multiple on-device large GenAI models, and hence, paves the way to the collective intelligence paradigm. Finally, we put a forward-looking vision on how large GenAI models will be the key to realize self-evolving networks.
KW - Artificial intelligence
KW - Data models
KW - Solid modeling
KW - Three-dimensional displays
KW - Visualization
KW - Wireless networks
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=85182358411&partnerID=8YFLogxK
U2 - 10.1109/MCOM.001.2300364
DO - 10.1109/MCOM.001.2300364
M3 - Article
AN - SCOPUS:85182358411
SN - 0163-6804
SP - 1
EP - 7
JO - IEEE Communications Magazine
JF - IEEE Communications Magazine
ER -