1st Report Of March 2025

March 7, 2025

Mainnet Performance

• Validator Nodes: 107

• Miner Nodes: 1,201

• New Wallets: +57

Project Updates

1. Large Model Initialization

• Optimization of Morpheus as the Base Large Model for AI Agents: 47%

• Developed a multi-task learning module, enabling Morpheus to train across different tasks in parallel, improving efficiency and application scope.

• Optimized task scheduling and resource allocation mechanisms to ensure efficient parallel execution in multi-task and multi-agent systems.

• Completed the design and testing of a multi-task training framework to ensure Morpheus’ stability and performance in complex environments.

• Language Understanding, Reasoning, and Communication Abilities: 0%

• Enhanced Features: Introduction of foundational personality modules (logical, emotional, creative) for personalized agent development: 0%.

• Integration of DeepSeek V3’s MOE Model Framework: 43%

• Expanded the system architecture to support multi-expert models efficiently.

2. Support for Distributed Privacy Computing

• Expanding the MANTA computing framework to support privacy-preserving training and inference required by AI agents: 0%.

• Optimizing the MANTA computing framework for MOE model training and inference required by DeepSeek V3: 0%.

3. Agent Model Center (MVP)

• Initial Version Deployment: 31%

• MATRIX AI provided pre-initialized Agent Tools, enabling users to assemble AI Agents using the platform.

• Integrated core AI model functionalities such as classification, regression, and reinforcement learning, ensuring seamless operation on the platform.

• Designed an AI Agent development framework that allows users to create and train custom AI Agents.

• Introduced scalable agent functionality modules, including state management, behavior decision-making, and strategy optimization.

• Extension of Compatible Baseline Models: 33%

• Integrated DeepSeek V3 as one of the baseline models in the Agent Model Center.

• Expanded system architecture to support multiple baseline models, ensuring interoperability.

• Implemented a model-switching mechanism, allowing users to seamlessly switch between different baseline models.

• Optimized data input and output interfaces for diverse model requirements, ensuring smooth data flow.

• Enhanced multi-model parallel training performance, optimizing resource allocation and scheduling.

4. AI Agent MVP

• Providing a Morpheus-based AI Agent MVP for User Testing: 40%

• Launched the first AI Agent: Web 3.0 Mentor.

5. Launch of Brainwave Distributed Database

• Deployment of NeuraMATRIX’s first ecosystem application, initiating data collection and anonymization processes: 22%.

6. Others

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