# 2nd Report Of January 2025

<figure><img src="/files/YEtNUNTtEjwEG0KVoWtm" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/4ex9XsWD09WQm50zmj2j" alt=""><figcaption></figcaption></figure>

### Mainnet Performance

* Validator Nodes: 107
* Miner Nodes: 1,235
* New Wallets: +49

### Project Updates

1. **Large Model Initialization**

* **Optimization of Morpheus as the Base Large Model for AI Agents:** 17%
* * Analyzed the architecture and bottlenecks of Morpheus, identifying limitations in AI Agent development (e.g., response time, scalability, and parallel computing capabilities).
  * Introduced new modules and features to support reinforcement learning, task scheduling, and state management for AI Agents.
  * Adjusted the training framework to enable large-scale multitask learning and complex behavior decision modeling.
  * Created the first Demo Agent.
* **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:** 16%
* * Implemented the Experts Network and Routing Mechanism for the MOE model.
  * Built a foundational distributed training environment to ensure parallel training across different experts in the MOE model.

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: 11%**
* * Designed unified API interfaces to enable users to easily upload, train, deploy, and manage AI Agents.
  * Developed security and permissions management features to ensure the safety of user models and data on the platform.
  * Integrated baseline models provided by MATRIX to ensure platform flexibility and scalability.
* **Extension of Compatible Baseline Models: 9%**
* * Integrated DeepSeek V3 as one of the baseline models in the Agent Model Center.
  * Designed unified API interfaces for seamless uploading and management of DeepSeek V3 and other baseline models.
  * Implemented features for DeepSeek V3, including data input, model training, model evaluation, and inference interfaces.

4. **AI Agent MVP**

* Providing a Morpheus-based AI Agent MVP for user testing: 0%.

5. **Launch of Brainwave Distributed Database**

* Deployment of NeuraMATRIX’s first ecosystem application, initiating data collection and anonymization processes: 12%.

6. **Others**

{% embed url="<https://x.com/MatrixAINetwork/status/1881915776330043804>" %}

{% embed url="<https://medium.com/@matrixainetwork/2nd-report-of-january-2025-c945173376ad>" %}

{% embed url="<https://coinmarketcap.com/community/post/350519749>" %}

{% embed url="<https://coinmarketcap.com/community/articles/678fe57dabb7374be790c314/>" %}

<br>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.matrix.io/bi-weekly-reports/2nd-report-of-january-2025.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
