Technical Architecture

The architecture of HEI is composed of four major layers that work in unison to deliver a robust, optimized framework for the intelligent agent ecosystem:

• Data Layer: The data layer contains multimodal datasets that include user profiles, interaction histories, voice, image, and video content, all of which are utilized for the training of both the pHLM and Xem agents. Through continuous feedback and interactions, this data optimizes Xem's responses to better align with user expectations and preferences.

• Model Layer: The model layer includes both general models (large-scale pretrained models for common knowledge) and personalized hybrid large models (pHLMs). General models provide foundational knowledge, while pHLMs dynamically adjust interactions and responses based on specific user profiles, ensuring a tailored experience.

• Xem Layer: This layer is responsible for the creation, initialization, training, and fine-tuning of Xem agents. It also manages agent-to-agent interactions, task collaboration, and autonomous learning through external feedback loops. This layer allows agents to evolve and improve based on both user feedback and the wider ecosystem.

• API Layer: The API layer serves as the interface between developers and the core services of the HEI platform. By providing standardized APIs, it allows seamless integration of Xem agents into other systems and facilitates the management of data, agents, communications, and security protocols.