# Subnet 1 Apex

## Quickstart

* Visit the [Apex website](https://apex.macrocosmos.ai/)
* Miners:
  * Read through:
    * [Current Competitions](/subnets/subnet-1-apex/subnet-1-current-competitions.md)
    * [Miner Setup](/subnets/subnet-1-apex/subnet-1-base-miner-setup.md) and [Apex CLI](/subnets/subnet-1-apex/subnet-1-base-miner-setup/apex-cli.md) guides
    * [Incentive Mechanism](/subnets/subnet-1-apex/incentive-mechanism.md)
* Validators:
  * Read through the [Validator Setup](/subnets/subnet-1-apex/validating.md) guide

## Introduction

Decentralized intelligence offers a powerful new way to approach complex algorithmic and agentic optimization problems by leveraging the collective reasoning and computational capacity of distributed networks. Through collaboration and competition among independent nodes, SN1 can generate solutions for complex mathematical and algorithmic problems that were once too large or intricate for any single entity to handle.

<figure><img src="/files/WnR2W3qdj1Hc7CCKIxhs" alt=""><figcaption></figcaption></figure>

These algorithmic and agentic systems focus on solving independent tasks, addressing bottlenecks, and optimising processes across all levels of complexity. The value of this approach lies not only in solving abstract equations or algorithms but in translating those solutions into real-world impact.

### Matrix Compression Challenge <a href="#compression-of-activations-challenge" id="compression-of-activations-challenge"></a>

The first major milestone to tackle is Matrix Compression or Compression of Activations, a challenge that lies at the heart of efficient distributed intelligence. By solving this problem we can enable **network load optimisation**: significantly reduce communication and memory overhead during large-scale training or inference, enabling smoother collaboration between decentralised nodes and faster model optimisation.

Read through the activation compression challenge overview and evaluation metrics in [Current Competitions](/subnets/subnet-1-apex/subnet-1-current-competitions.md).

### Subnet 9 IOTA Use Case <a href="#subnet-9-iota-use-case" id="subnet-9-iota-use-case"></a>

When the Subnet 1 Matrix Compression competition results in successful solutions, Subnet 9 IOTA stands to gain significant benefits in both performance and scalability. Efficient compression techniques will drastically reduce communication overhead between nodes, allowing faster and more synchronised training across the decentralised network. This improvement not only enhances computational throughput but also lowers the energy and bandwidth requirements for participating validators, making the subnet more sustainable and cost-efficient.

### Open Source Approach <a href="#open-source-approach" id="open-source-approach"></a>

Open-sourcing such a solution amplifies its global benefits allowing developers, researchers, and industries to build upon a shared foundation, accelerate innovation, and ensure transparency and accessibility. This open collaboration not only democratises advanced computation but also strengthens real-world infrastructure by making intelligent, resource-efficient systems available to all.

### What's Next <a href="#what-is-next" id="what-is-next"></a>

Apex subnet is set to unlock innovation at scale by hosting multiple competitions at once, empowering the community to solve several challenges in parallel. This multi-competition model transforms the subnet into a vibrant hub of creativity and collaboration, where diverse minds can contribute breakthrough ideas from different fields simultaneously. By dividing miner emissions across dedicated competition pools, Apex ensures that every area of exploration receives the support it needs — fuelling a constant flow of progress and discovery.&#x20;

<figure><img src="/files/j4LbwDqHKk72qyk69yLA" alt=""><figcaption></figcaption></figure>

### Other related resources

* [Website](https://apex.macrocosmos.ai/)
* [Apex X (Twitter)](https://x.com/Apex_SN1)
* [GitHub](https://github.com/macrocosm-os/apex)
* [Substack](https://macrocosmosai.substack.com/t/language-models)
* [Bittensor Discord](https://discord.com/channels/799672011265015819/1161764867166961704)
* [Macrocosmos Discord](https://discord.com/channels/1238450997848707082)
* [Cosmonauts - Macrocosmos Telegram](https://t.me/macrocosmosai)
* [Macrocosmos X (Twitter)](https://x.com/MacrocosmosAI)


---

# 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.macrocosmos.ai/subnets/subnet-1-apex.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.