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

Walid Saad, Omar Hashash, Christo Kurisummoottil Thomas, Christina Chaccour, Merouane Debbah, Narayan Mandayam, Zhu Han

TL;DR

The paper envisions a new beyond-6G paradigm: AGI-native wireless networks driven by a telecom brain that combines perception, a causal HD world model, and intent/goal-driven planning to achieve common sense and generalization. Grounded in metaverse-enabled digital twins, the approach uses hyper-dimensional computing and category theory to map symbolic world representations into scalable HD vectors, enabling analogical reasoning and intuitive physics for robust planning. It introduces IIT-inspired planning, two planning modes (intent- and objective-driven), and memory to support rapid analogical reasoning, while outlining sensing, perception, and memory modules, as well as DT/avatar holographic teleportation use cases. The work also provides a roadmap with physics-based world models, humanity-centric guardrails, and open interfaces to turn AGI-native wireless networks into practical, autonomous beyond-6G infrastructure with wide-reaching implications for XR, DTs, and cognitive avatars.

Abstract

Building future wireless systems that support services like digital twins (DTs) is challenging to achieve through advances to conventional technologies like meta-surfaces. While artificial intelligence (AI)-native networks promise to overcome some limitations of wireless technologies, developments still rely on AI tools like neural networks. Such tools struggle to cope with the non-trivial challenges of the network environment and the growing demands of emerging use cases. In this paper, we revisit the concept of AI-native wireless systems, equipping them with the common sense necessary to transform them into artificial general intelligence (AGI)-native systems. These systems acquire common sense by exploiting different cognitive abilities such as perception, analogy, and reasoning, that enable them to generalize and deal with unforeseen scenarios. Towards developing the components of such a system, we start by showing how the perception module can be built through abstracting real-world elements into generalizable representations. These representations are then used to create a world model, founded on principles of causality and hyper-dimensional (HD) computing, that aligns with intuitive physics and enables analogical reasoning, that define common sense. Then, we explain how methods such as integrated information theory play a role in the proposed intent-driven and objective-driven planning methods that maneuver the AGI-native network to take actions. Next, we discuss how an AGI-native network can enable use cases related to human and autonomous agents: a) analogical reasoning for next-generation DTs, b) synchronized and resilient experiences for cognitive avatars, and c) brain-level metaverse experiences like holographic teleportation. Finally, we conclude with a set of recommendations to build AGI-native systems. Ultimately, we envision this paper as a roadmap for the beyond 6G era.

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

TL;DR

The paper envisions a new beyond-6G paradigm: AGI-native wireless networks driven by a telecom brain that combines perception, a causal HD world model, and intent/goal-driven planning to achieve common sense and generalization. Grounded in metaverse-enabled digital twins, the approach uses hyper-dimensional computing and category theory to map symbolic world representations into scalable HD vectors, enabling analogical reasoning and intuitive physics for robust planning. It introduces IIT-inspired planning, two planning modes (intent- and objective-driven), and memory to support rapid analogical reasoning, while outlining sensing, perception, and memory modules, as well as DT/avatar holographic teleportation use cases. The work also provides a roadmap with physics-based world models, humanity-centric guardrails, and open interfaces to turn AGI-native wireless networks into practical, autonomous beyond-6G infrastructure with wide-reaching implications for XR, DTs, and cognitive avatars.

Abstract

Building future wireless systems that support services like digital twins (DTs) is challenging to achieve through advances to conventional technologies like meta-surfaces. While artificial intelligence (AI)-native networks promise to overcome some limitations of wireless technologies, developments still rely on AI tools like neural networks. Such tools struggle to cope with the non-trivial challenges of the network environment and the growing demands of emerging use cases. In this paper, we revisit the concept of AI-native wireless systems, equipping them with the common sense necessary to transform them into artificial general intelligence (AGI)-native systems. These systems acquire common sense by exploiting different cognitive abilities such as perception, analogy, and reasoning, that enable them to generalize and deal with unforeseen scenarios. Towards developing the components of such a system, we start by showing how the perception module can be built through abstracting real-world elements into generalizable representations. These representations are then used to create a world model, founded on principles of causality and hyper-dimensional (HD) computing, that aligns with intuitive physics and enables analogical reasoning, that define common sense. Then, we explain how methods such as integrated information theory play a role in the proposed intent-driven and objective-driven planning methods that maneuver the AGI-native network to take actions. Next, we discuss how an AGI-native network can enable use cases related to human and autonomous agents: a) analogical reasoning for next-generation DTs, b) synchronized and resilient experiences for cognitive avatars, and c) brain-level metaverse experiences like holographic teleportation. Finally, we conclude with a set of recommendations to build AGI-native systems. Ultimately, we envision this paper as a roadmap for the beyond 6G era.
Paper Structure (22 sections, 3 equations, 18 figures, 1 table)

This paper contains 22 sections, 3 equations, 18 figures, 1 table.

Table of Contents

  1. Introduction
  2. Where will the current network evolution lead us to?
  3. Common sense: A key missing link in AI-native wireless systems
  4. Proposed Vision and Contributions
  5. Prior works: Limitations and motivation
  6. Proposed vision: AGI-native wireless networks
  7. Contributions
  8. Designing the Telecom Brain: A Synergy of AGI and the Metaverse
  9. Sensing: How can we capture the physical world over wireless networks?
  10. Perception: From data to representations
  11. Disentangling learnable and spurious data
  12. Causal vs. generalizable representation learning for abstractions
  13. World model: Causality meets HD computing
  14. Action-planning: Intents vs. objectives
  15. Intent-driven planning
  16. ...and 7 more sections

Figures (18)

  • Figure 1: Overview of the evolution of wireless networks from 6G to the beyond 6G era converging towards our envisioned, next-generation AGI-native networks and their corresponding use cases.
  • Figure 2: Organization of the sections in this paper.
  • Figure 3: Illustrative figure showcasing the physical constraints facing wireless enablers in the evolution from 6G-Advanced towards the next-generation of wireless networks. Note that this figure is illustrative only and does not purport to showcase exact quantitative numbers.
  • Figure 4: Illustrative figure showcasing the four essential pillars of common sense.
  • Figure 5: Illustrative figure showcasing the operation of an AGI-native telecom brain and its different modules. This design is inspired from the AGI architecture in LeCun2022OR, but it refines it for our communication network purposes.
  • ...and 13 more figures