# 2nd Report Of December 2025

### Mainnet Performance

* Validator nodes: 102
* Miner nodes: 1,009
* Wallets (net change): +53

### Project Progress

#### Large Language Model Development

* Optimized Morpheus as the foundational large language model for AI Agents — 100% (Integration and debugging with the Agent Model Center remains).
* Introduced DeepSeek V3's Mixture-of-Experts (MoE) framework to improve base-model training efficiency — 99%.

#### 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).

#### 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%.

1. Introduced "redundant agent automatic circuit breaking" and "island agent automatic fusion" mechanisms to improve overall system autonomy and stability.
2. Designed and implemented the Agent Matrix system, supporting on-demand activation, collaboration, and management of multiple Agents.

* Expanded compatible baseline models for the Agent Model Center; introduced DeepSeek V3 as one of the supported benchmarks — 94%.

#### AI Agent (MVP)

* Released a Morpheus-based AI Agent MVP for user testing — 100%.

#### Brainwave Distributed Database (NeuraMATRIX)

* Launched NeuraMATRIX, the first ecosystem application; started user data collection and anonymized preprocessing — 60%.

#### Others

* Published the comprehensive direction report for the BioData Blockchain.


---

# 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-december-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.