> For the complete documentation index, see [llms.txt](https://cerebro-3.gitbook.io/cerebro-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cerebro-3.gitbook.io/cerebro-docs/ai-inference-rewards-system.md).

# AI Inference Rewards System

The first phase of Cerebro is the Inference Rewards System.

The mechanism is designed around a simple relationship:

Trading activity → Fees → AI credits → AI inference

When the token is traded, fees are generated.

A portion of those fees can be allocated toward AI inference credits.

Eligible holders accumulate credits according to the distribution rules of the protocol.

Those credits can then be used for supported AI inference services.

This creates a different type of token utility.

Instead of rewarding participants exclusively with more tokens, Cerebro aims to convert part of the economic activity surrounding the token into access to a useful resource.

#### Example

Assume the ecosystem generates $100,000 in trading volume.

If the applicable trading fee is 1%:

$100,000 × 1% = $1,000 in fees

If 50% of those fees are allocated to AI inference:

$1,000 × 50% = $500 of AI allocation

That allocation can then be distributed as inference credits to eligible participants.

The actual parameters are determined by the Cerebro protocol.


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