# 2nd Report Of October 2025

<figure><img src="/files/x7AfOuXB6l0rIYvrMS2g" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/ZuDvMGp4paPr4roUSoRI" alt=""><figcaption></figcaption></figure>

#### Mainnet Performance

* Validator nodes: 101
* Miner nodes: 1,008
* Wallets (net change): +77

***

#### Project Progress

**1. Large Language Model Development**

* Optimized **Morpheus** as the foundational large language model for AI Agents **— 97%** (remaining: integration and debugging with the Agent Model Center).
* Introduced **DeepSeek V3’s Mixture-of-Experts (MoE)** framework to improve base-model training efficiency **— 96%**.

**2. Distributed Privacy Computing Support**

* Extended the **MANTA** compute system to support privacy-preserving training and inference required by Agents — 0% (on hold).
* Adapted MANTA to support MoE-based training and inference **for DeepSeek V3 — 0%** (on hold).

**3. Agent Model Center (MVP)**

* Deployed the **first version** of the Model Center, initialized with Agent Tools from **MATRIX AI**, enabling users to assemble custom Agents **— 100%.**
* Added a **reinforcement learning simulation environment** to construct multi-agent scenarios.
* Integrated collaboration metrics as training feedback to optimize inter-agent cooperation.
* Expanded compatible baseline models for the Agent Model Center; introduced **DeepSeek V3** as one of the supported benchmarks **— 90%**.

**4. AI Agent (MVP)**

* Released a **Morpheus-based AI Agent MVP** for user testing **— 98%**.

**5. Brainwave Distributed Database (NeuraMATRIX)**

* Launched **NeuraMATRIX**, the first ecosystem application; started user data collection and anonymized preprocessing **— 50%**.

**6. Others**

* Optimized **multi-layer semantic embedding** algorithms to maintain logical consistency across multi-turn dialogues.
* Refined the **Intelligent Contract quantitative database** schema to support structured off-chain asset storage and vectorized retrieval.

{% embed url="<https://coinmarketcap.com/community/post/369868187>" %}

{% embed url="<https://matrixainetwork.medium.com/2nd-report-of-october-2025-02582a330d60>" %}

{% embed url="<https://coinmarketcap.com/community/articles/68f798e8d74e9407b7a45299>" %}

{% embed url="<https://x.com/MatrixAINetwork/status/1980640124754096467>" %}


---

# 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-october-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.
