Camelot Protocol

A. Protocol Architecture

The Camelot Protocol comprises a hybrid blockchain model including one public chain and one private chain. The public chain operates on a Proof of Contribution (PoC) consensus mechanism, where users (miners) contribute computing power (GPU resources) to assist in training AI models in return of corresponding rewards.

b. Definition of Users, Mobile Devices of AI Application, and Agent

• Users: They contribute GPU resources to this computationally-intensive task of training AI models. They participate in the PoC consensus mechanism on the public chain and receive rewards based on their contributions.

• Mobile Devices of AI Application: These devices provide a massive volume of AI training tasks to Camelot's Agents.

• Agent: This is a Platform-as-a-Service (PaaS) component responsible for handling the AI training process. It interacts with both private and public chains, coordinates tasks, manages resources, and ensures the efficient utilization of GPU capabilities provided by users.

c. Explanation of the Role of GPU Computing in the Network

GPU computing plays a crucial role in the Camelot Protocol. The primary task executed by this network is training AI models, which is a computationally intensive process requiring massive GPU resources. Users provide these GPU resources, and agents ensure that these resources are effectively utilized for AI training tasks. Through the PoC mechanism on the public chain, the computing power contributed by each user is tracked and verified, forming the basis of reward distribution. By decentralizing GPU resources and utilizing them for AI training, the Camelot Protocol can handle large-scale, complex AI tasks while maintaining security, privacy, and transparency.