HiDream.ai Founder Mei Tao Proposes Agentic Omnimodal World Model: Large Language, Multimodal, and Embodied Routes Will Ultimately Converge
At the 2026 World's Top Scientists Forum, Mei Tao proposed that three AI technology routes—Large Language Models (LLMs), multimodal models, and embodied models—will converge into an 'Agentic Omnimodal World Model,' consisting of a decision-making brain, a world simulator, and embodied context operating in synergy within a unified Token space.
Digital intelligence can already write code, perform mathematics, and generate videos, yet physical intelligence still stumbles when attempting to grasp a simple cup. This gap is one of the most frequently cited structural challenges in the current AI landscape. At the Second International Conference on Engineering Intelligence held during the 2026 World's Top Scientists Forum in November, Mei Tao, founder and CEO of the AI company HiDream.ai, offered a concrete architectural response: the three technology routes—large language models, multimodal models, and embodied large models—are not isolated from one another but will ultimately converge in the long term toward what he terms the Agentic Omnimodal World Model.
Mei Tao breaks this architecture down into three functional components. First is the LLM, which serves as the agent's decision-making brain, responsible for understanding intent, generating reasoning, and formulating task plans. Second is the Omni-Model, or general world model, which acts as a world simulator: based on the intent provided by the LLM, it simulates the operation of the physical world, deduces the consequences of actions, and anticipates next steps. Third is the Embodied Context, which interfaces with the real physical environment, executes embodied actions, and feeds back real-world observational data to calibrate the world model.
The key proposition for their synergy is 'One Token Space, One World'—achieving unity between the mental world and the physical world within the same Token space. This means that all modalities, including text, images, video, spatial data, pose, force/touch, and sensor inputs, share a single representation rather than operating independently. HiDream's proprietary native omni-modal (Unified Transformer) architecture serves as the engineering foundation for this proposition.