Matrix AI Network

<h3 id="mainnet-performance">Mainnet Performance</h3><ul><li>Validator Nodes: 105</li><li>Miner Nodes: 1,182</li><li>New Wallets: &#43;44</li></ul><p></p><img src="https://academy-public.coinmarketcap.com/srd-optimized-uploads/46d25e0c955c4a02aeb02eabd2b6e615.png" /><p></p><h3 id="project-updates">Project Updates</h3><h3 id="large-model-initialization">Large Model Initialization</h3><p><strong>Optimization of Morpheus as the Base Large Model for AI Agents: 50%<br /></strong></p><ul><li>Optimized computational efficiency to reduce latency in training and inference while enhancing large-scale task processing capabilities.</li><li>Introduced distributed training mechanisms to ensure Morpheus operates efficiently across multiple GPU/TPU nodes, increasing computational throughput.</li><li>Completed model compression and quantization to reduce memory usage, ensuring efficient performance on resource-constrained devices.</li><li>Conducted performance testing and fine-tuning to ensure stability across diverse hardware platforms.</li></ul><p><strong>Language Understanding, Reasoning, and Communication Abilities: 50%</strong></p><ul><li><strong>Enhanced Features: </strong>Introduction of foundational personality modules (logical, emotional, creative) for personalized agent development: 5%</li></ul><p><strong>Integration of DeepSeek V3&#39;s MOE Model Framework: 50%</strong></p><ul><li>Completed large-scale distributed training of the MOE model to handle vast datasets.<br />Implemented MOE model applications in multi-task learning, supporting expert selection for different tasks.<br />Conducted large-scale dataset performance evaluation, balancing training speed and accuracy.</li></ul><h3 id="support-for-distributed-privacy-computing-paused-br-br-agent-model-center-mvp">Support for Distributed Privacy Computing (Paused) <br /><br />Agent Model Center (MVP)</h3><p><strong>Initial Version Deployment: 39%</strong></p><ul><li>Developed AI Agent training tools, including data preprocessing, training monitoring, and optimization strategies.<br />Provided custom hyperparameter tuning to help users optimize training and model performance.<br />Integrated automated training and model evaluation features for streamlined debugging and validation.<br />Implemented parallel training mechanisms to support large-scale training tasks efficiently.</li></ul><p><strong>Extension of Compatible Baseline Models: 23%</strong></p><ul><li>Enhanced training workflows for DeepSeek V3 and other baseline models, optimizing data preprocessing, training configurations, and model tuning.<br />Developed automated model deployment features to simplify the production launch process.<br />Introduced real-time monitoring and feedback mechanisms to track model performance during training.<br />Improved inference efficiency for deployed models, ensuring high-performance operation in production environments.</li></ul><h3 id="ai-agent-mvp">AI Agent MVP</h3><ul><li><strong>Web 3.0 Mentor MVP: </strong>First version completed</li><li><strong>Second MVP: </strong>Under research</li></ul><p>Launch of Brainwave Distributed Database</p><ul><li>Deployment of NeuraMATRIX’s first ecosystem application, initiating data collection and anonymization processes: 17%</li></ul><p><strong>Others&#xff1a; Submitted listing application to Bitfinex</strong></p>

2nd Report Of March 2025 - Matrix AI Network

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Matrix AI Network

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