[Paper Review] Artificial Intelligence for the Metaverse: A Survey

Thien Huynh‐The, Quoc‐Viet Pham+4 more|arXiv (Cornell University)|Feb 15, 2022

Virtual Reality Applications and Impacts72 citations

TL;DR

A comprehensive survey of how artificial intelligence underpins the metaverse, covering six technical aspects (NLP, machine vision, blockchain, networking, digital twin, neural interface), AI-powered applications, and future directions.

ABSTRACT

Along with the massive growth of the Internet from the 1990s until now, various innovative technologies have been created to bring users breathtaking experiences with more virtual interactions in cyberspace. Many virtual environments with thousands of services and applications, from social networks to virtual gaming worlds, have been developed with immersive experience and digital transformation, but most are incoherent instead of being integrated into a platform. In this context, metaverse, a term formed by combining meta and universe, has been introduced as a shared virtual world that is fueled by many emerging technologies, such as fifth-generation networks and beyond, virtual reality, and artificial intelligence (AI). Among such technologies, AI has shown the great importance of processing big data to enhance immersive experience and enable human-like intelligence of virtual agents. In this survey, we make a beneficial effort to explore the role of AI in the foundation and development of the metaverse. We first deliver a preliminary of AI, including machine learning algorithms and deep learning architectures, and its role in the metaverse. We then convey a comprehensive investigation of AI-based methods concerning six technical aspects that have potentials for the metaverse: natural language processing, machine vision, blockchain, networking, digital twin, and neural interface, and being potential for the metaverse. Subsequently, several AI-aided applications, such as healthcare, manufacturing, smart cities, and gaming, are studied to be deployed in the virtual worlds. Finally, we conclude the key contribution of this survey and open some future research directions in AI for the metaverse.

Motivation & Objective

• Provide a concise overview of AI techniques (ML and DL) and learning paradigms applicable to the metaverse.
• Survey AI-driven methods across six technical aspects to assess their potential for metaverse platforms.
• Identify AI-powered applications and real-world projects applying AI to the metaverse.
• Discuss future research directions to advance AI for immersive virtual worlds.

Proposed method

• Review conventional and advanced AI/ML techniques (supervised, unsupervised, semi-supervised, reinforcement learning; DL architectures like RNN, CNN, SOM, autoencoders).
• Map AI methods to six metaverse-relevant technical aspects: NLP, machine vision, blockchain, networking, digital twin, neural interface.
• Discuss AI-enabled applications (healthcare, gaming, manufacturing, smart cities, etc.) and exemplar metaverse projects.
• Highlight potential future research directions and open challenges in AI for the metaverse.

Experimental results

Research questions

• RQ1 What is the role of AI across key metaverse technical layers (NLP, vision, blockchain, networking, digital twin, neural interface)?
• RQ2 How are AI methods applied to real-world metaverse applications and projects?
• RQ3 What future research directions are most promising to advance AI-enabled metaverse platforms?
• RQ4 What are the implications of integrating AI with XR/VR, blockchain, and networking for immersive experiences?

Key findings

• AI techniques, including ML and DL, underpin core metaverse capabilities across six technical aspects.
• AI-enabled methods support natural language agents, computer vision for XR, secure and scalable networking, and digital twin/neural interface integrations.
• The survey discusses AI-powered applications in healthcare, manufacturing, smart cities, gaming, E-commerce, real estate, and DeFi within virtual worlds.
• Several metaverse projects demonstrate AI-enhanced immersive experiences and user-oriented services.
• Future research directions are proposed to guide AI integration in scalable, secure, and interoperable metaverse platforms.