Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G

Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G

29 Apr 2024 | Walid Saad, Fellow, IEEE, Omar Hashash, Graduate Student Member, IEEE, Christo Kurisummoottil Thomas, Member, IEEE, Christina Chaccour, Member, IEEE, Mériouane Debbah, Fellow, IEEE, Narayan Mandayam, Fellow, IEEE, and Zhu Han, Fellow, IEEE
This paper presents a vision for AGI-native wireless systems that go beyond 6G, aiming to enable next-generation wireless networks with artificial general intelligence (AGI) capabilities. The paper argues that current AI-native wireless systems, which rely on conventional AI tools like auto-encoders and neural networks, are insufficient to meet the complex requirements of emerging wireless use cases such as the metaverse, holographic teleportation, and cognitive avatars. These use cases demand real-time, high-quality, and reliable communication, computing, and AI capabilities that traditional wireless technologies cannot provide. To address these challenges, the paper proposes a new approach to AI-native wireless systems that incorporates common sense, enabling them to generalize and adapt to unforeseen scenarios. The proposed AGI-native wireless systems are built on three fundamental components: a perception module, a world model, and an action-planning component. The perception module abstracts real-world elements into generalizable representations, which are then used to create a world model based on principles of causality and hyper-dimensional (HD) computing. This world model is viewed as an HD causal vector space that aligns with the intuitive physics of the real world, a cornerstone of common sense. The world model enables analogical reasoning and manipulation of abstract representations, and drives the action-planning component of the AGI-native network. The action-planning component uses brain-inspired methods such as integrated information theory and hierarchical abstractions to enable intent-driven and objective-driven planning. The paper also discusses three use cases related to human users and autonomous agents: analogical reasoning for next-generation digital twins (DTs), synchronized and resilient experiences for cognitive avatars, and brain-level metaverse experiences exemplified by holographic teleportation. Finally, the paper concludes with a set of recommendations to ignite the quest for AGI-native systems, envisioning this paper as a roadmap for the next-generation of wireless systems beyond 6G.This paper presents a vision for AGI-native wireless systems that go beyond 6G, aiming to enable next-generation wireless networks with artificial general intelligence (AGI) capabilities. The paper argues that current AI-native wireless systems, which rely on conventional AI tools like auto-encoders and neural networks, are insufficient to meet the complex requirements of emerging wireless use cases such as the metaverse, holographic teleportation, and cognitive avatars. These use cases demand real-time, high-quality, and reliable communication, computing, and AI capabilities that traditional wireless technologies cannot provide. To address these challenges, the paper proposes a new approach to AI-native wireless systems that incorporates common sense, enabling them to generalize and adapt to unforeseen scenarios. The proposed AGI-native wireless systems are built on three fundamental components: a perception module, a world model, and an action-planning component. The perception module abstracts real-world elements into generalizable representations, which are then used to create a world model based on principles of causality and hyper-dimensional (HD) computing. This world model is viewed as an HD causal vector space that aligns with the intuitive physics of the real world, a cornerstone of common sense. The world model enables analogical reasoning and manipulation of abstract representations, and drives the action-planning component of the AGI-native network. The action-planning component uses brain-inspired methods such as integrated information theory and hierarchical abstractions to enable intent-driven and objective-driven planning. The paper also discusses three use cases related to human users and autonomous agents: analogical reasoning for next-generation digital twins (DTs), synchronized and resilient experiences for cognitive avatars, and brain-level metaverse experiences exemplified by holographic teleportation. Finally, the paper concludes with a set of recommendations to ignite the quest for AGI-native systems, envisioning this paper as a roadmap for the next-generation of wireless systems beyond 6G.
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