Matrix AI Network

<h3 id="mainnet-performance">Mainnet Performance</h3><p>• Validator Nodes: 107</p><p>• Miner Nodes: 1,201</p><p>• New Wallets: &#43;57</p><p></p><p></p><img src="https://academy-public.coinmarketcap.com/srd-optimized-uploads/7bd475e456a1401bacff49cdb0c7d773.png" /><p></p><h3 id="project-updates">Project Updates</h3><h4>1. Large Model Initialization</h4><p><strong>• Optimization of Morpheus as the Base Large Model for AI Agents: 47%</strong></p><p>• Developed a multi-task learning module, enabling Morpheus to train across different tasks in parallel, improving efficiency and application scope.</p><p>• Optimized task scheduling and resource allocation mechanisms to ensure efficient parallel execution in multi-task and multi-agent systems.</p><p>• Completed the design and testing of a multi-task training framework to ensure Morpheus’ stability and performance in complex environments.</p><p><strong>• Language Understanding, Reasoning, and Communication Abilities: 0%</strong></p><p>• <strong>Enhanced Features:</strong> Introduction of foundational personality modules (logical, emotional, creative) for personalized agent development: 0%.</p><p><strong>• Integration of DeepSeek V3’s MOE Model Framework: 43%</strong></p><p>• Expanded the system architecture to support multi-expert models efficiently.</p><h4>2. Support for Distributed Privacy Computing</h4><p>• Expanding the MANTA computing framework to support privacy-preserving training and inference required by AI agents: 0%.</p><p>• Optimizing the MANTA computing framework for MOE model training and inference required by DeepSeek V3: 0%.</p><h4>3. Agent Model Center (MVP)</h4><p><strong>• Initial Version Deployment: 31%</strong></p><p>• MATRIX AI provided pre-initialized Agent Tools, enabling users to assemble AI Agents using the platform.</p><p>• Integrated core AI model functionalities such as classification, regression, and reinforcement learning, ensuring seamless operation on the platform.</p><p>• Designed an AI Agent development framework that allows users to create and train custom AI Agents.</p><p>• Introduced scalable agent functionality modules, including state management, behavior decision-making, and strategy optimization.</p><p>• Extension of Compatible Baseline Models: 33%</p><p>• Integrated DeepSeek V3 as one of the baseline models in the Agent Model Center.</p><p>• Expanded system architecture to support multiple baseline models, ensuring interoperability.</p><p>• Implemented a model-switching mechanism, allowing users to seamlessly switch between different baseline models.</p><p>• Optimized data input and output interfaces for diverse model requirements, ensuring smooth data flow.</p><p>• Enhanced multi-model parallel training performance, optimizing resource allocation and scheduling.</p><h4>4. AI Agent MVP</h4><p><strong>• Providing a Morpheus-based AI Agent MVP for User Testing: 40%</strong></p><p>• Launched the first AI Agent: Web 3.0 Mentor.</p><h4>5. Launch of Brainwave Distributed Database</h4><p>• Deployment of NeuraMATRIX’s first ecosystem application, initiating data collection and anonymization processes: 22%.</p><h4>6. Others</h4>

1st Report Of March 2025

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Matrix AI Network

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