# Mining

## 1. Reward Release

First, the 100 million will be allocated as a staking pool for users, and will be linearly released based on the calculation of 10,000 units.

If the total pre-orders are less than 10,000 units, the allocation will be distributed based on the actual number of units ordered, and the remaining portion will be added to the mining reward pool. The remaining will be allocated according to the following proportions:

Task | Percentage | Quantity （Billion） |
---|---|---|

Voice/Text corpus contribution (LingoPod Rewards) | 30% | 16.5 |

APP video/text corpus contribution | 20% | 11 |

LingoTrans speech/text/video translation and proofreading | 30% | 16.5 |

Cross-lingual LLM fine-tuning and pre-training | 10% | 5.5 |

In-house AI model deployment | 10% | 5.5 |

30% of 55 billion, which is 16.5 billion tokens will be released over 20 years according to the following rules, while the remaining will be allocated for various tasks according to technical development . (The specific quality of the uploaded voice corpus will be managed by the community governance contract.)

We will use a decremental release model to release a total of 16.5 billion tokens. This model allows us to determine the monthly release amount, ensuring that the total token supply is gradually released over 20 years.

**Formula Setup**

**Formula Setup**

Set the following parameters:

**Total Supply =**16.5**billion tokens****Release Period months = 240 months**

We will use an arithmetic sequence to set the monthly release amount. The formula is as follows:：

Where:

R1 is the initial monthly release amount

d is the monthly decrement amount

The first 12 months will release 12% of the entire reward.

Given:

**Initial monthly release amount R1 =**134560470.49183798**the monthly decrement amount : d =**0.010000000149011612

The release will be as shown in the figure below.

## 2. LingoPod Rewards and Stabilization Reserve

To mitigate the impact of future price fluctuations on reward earnings, we have established an innovative stabilization fund specifically designed to stabilize reward values.

Parameters:

Daily fixed token release amount 𝑅

Daily token price 𝑃

Daily number of participants 𝑛

Daily number of participants ni for reward task i

m represents number of reward tasks

wi represents the weight of different tasks

n_ref and P_ref represent the the benchmark number of participants and he benchmark price respectively

Token amount in the reward pool 𝑆

𝜆 is the difficulty factor for the number of participants

alpha is the smooth factor for the price impact

Objectives:

Smooth the total value of daily rewards 𝑉, where 𝑉=𝑅⋅𝑃

Store a portion of tokens in the reward pool when the number of participants is low, for future use

Function design: Calculation of the actual daily reward value 𝑉: 𝑉=𝑅⋅𝑃

Adjustment when the number of participants is low, using ln(𝑛) and the difficulty factor 𝜆:

The first part, 1−a1+exp(−b⋅(n−c))1−1+exp(−b⋅(n−c))a, ensures that when we set a benchmark number of people, for example, 1000, the amount of rewards drawn into the stabilization fund increases as the number of participants falls below this benchmark. Once the number of participants drops below a certain threshold, the reward extraction will stabilize and follow a standard rate. The latter part, α⋅log(P/Pref), ensures that when the price falls below the reference price, the stabilization fund will inject rewards into the pool, providing people with more incentives. Here is the example:

A: 0.9883333339127566, B: 0.02335101596185324, C: 135.56550803743016

n=10, y=0.9499999969308052

n=100, y=0.7000000006186333

n=1000, y=0.011666667779574591

n=5000, y=0.011666666087243427

n=10000, y=0.011666666087243427

n=50000, y=0.011666666087243427

n=100000, y=0.011666666087243427

Supplementing rewards from the pool to smooth the value:

where 𝑇 is a smoothing parameter that determines the rate at which rewards are supplemented from the pool.

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