Abstract
Large Multimodal Models (LMMs) like OpenAI's GPT4o and Google's Gemini, introduced in 2024, process multiple modalities, enabling significant advances in multimodal interaction. Inspired by frameworks for self-driving cars and AGI, this paper proposes "Levels of Multimodal Interaction" to guide research and development. The four levels are: basic multimodality (0), single modalities in turn-taking; combined multimodality (1), fused interpretation of multiple modalities; humanlike (2), natural interaction flow with additional communication signals; and beyond humanlike (3), surpassing human capabilities and include underlying hidden signals with the potential for transformational human-AI integration. LMMs have progressed from Level 0 to 1, with Level 2 next.
Level 3 sets a speculative target that multimodal interaction research could help achieve, where interaction becomes more natural and ultimately surpasses human capabilities. Eventually, such Level 3 multimodal interaction could lead to greater human-AI integration and transform human performance. This anticipated shift, in turn, introduces considerations, particularly around safety, agency and control of AI systems.