2nd Report Of March 2025

Mainnet Performance

• Validator Nodes: 105
• Miner Nodes: 1,182
• New Wallets: +44

Project Updates

Large Model Initialization

Optimization of Morpheus as the Base Large Model for AI Agents: 50%

• Optimized computational efficiency to reduce latency in training and inference while enhancing large-scale task processing capabilities.
• Introduced distributed training mechanisms to ensure Morpheus operates efficiently across multiple GPU/TPU nodes, increasing computational throughput.
• Completed model compression and quantization to reduce memory usage, ensuring efficient performance on resource-constrained devices.
• Conducted performance testing and fine-tuning to ensure stability across diverse hardware platforms.

Language Understanding, Reasoning, and Communication Abilities: 50%

• Enhanced Features: Introduction of foundational personality modules (logical, emotional, creative) for personalized agent development: 5%

Integration of DeepSeek V3’s MOE Model Framework: 50%

• Completed large-scale distributed training of the MOE model to handle vast datasets.
• Implemented MOE model applications in multi-task learning, supporting expert selection for different tasks.
• Conducted large-scale dataset performance evaluation, balancing training speed and accuracy.

Support for Distributed Privacy Computing (Paused)

Agent Model Center (MVP)

Initial Version Deployment: 39%

• Developed AI Agent training tools, including data preprocessing, training monitoring, and optimization strategies.
• Provided custom hyperparameter tuning to help users optimize training and model performance.
• Integrated automated training and model evaluation features for streamlined debugging and validation.
• Implemented parallel training mechanisms to support large-scale training tasks efficiently.

Extension of Compatible Baseline Models: 23%

• Enhanced training workflows for DeepSeek V3 and other baseline models, optimizing data preprocessing, training configurations, and model tuning.
• Developed automated model deployment features to simplify the production launch process.
• Introduced real-time monitoring and feedback mechanisms to track model performance during training.
• Improved inference efficiency for deployed models, ensuring high-performance operation in production environments.

AI Agent MVP

• Web 3.0 Mentor MVP: First version completed
• Second MVP: Under research

Launch of Brainwave Distributed Database

• Deployment of NeuraMATRIX’s first ecosystem application, initiating data collection and anonymization processes: 17%

Others： Submitted listing application to Bitfinex

The Matrix AI Network was founded in 2017. In 2023, we enter Matrix 3.0 blending neuroscience with our previous work to realize the vision of the Matrix films.

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Owen Tao (CEO) | Steve Deng (Chief AI Scientist) | Eric Choy (CMTO)