Algorithm

Our proprietary algorithms utilize GPU resources to enhance computational efficiency and maximize returns for our users. By leveraging advanced machine learning models and optimization techniques, we ensure that your staked ETH grows effectively. The algorithm continuously adapts to market conditions and computational demands, delivering unparalleled performance in AI training, cloud mining, and digital rendering.

At VectorAI, our proprietary algorithm is designed to maximize returns for users while optimizing the utilization of GPU resources across our decentralized network. Here’s a closer look at how our algorithm works, including some of the mathematical principles that drive it.

1. GPU Resource Allocation

Our system dynamically allocates GPU resources based on the demand for computational tasks, such as AI training, cloud mining, and digital rendering. This allocation is governed by a utility function U(x)U(x)U(x), which maximizes the overall efficiency:

U(x)=∑i=1n(wi⋅pi(xi)ci(xi))U(x) = \sum_{i=1}^{n} \left( \frac{w_i \cdot p_i(x_i)}{c_i(x_i)} \right)U(x)=i=1∑n​(ci​(xi​)wi​⋅pi​(xi​)​)

where:

• xix_ixi​ is the allocation for the iii-th task,

• wiw_iwi​ is the weight representing the importance of each task,

• pi(xi)p_i(x_i)pi​(xi​) is the performance outcome of allocating xix_ixi​ resources to task iii,

• ci(xi)c_i(x_i)ci​(xi​) is the cost associated with this allocation.

2. Staking Optimization

The returns for staked ETH are calculated using a compound interest model, where your staked amount grows based on the profits generated by the GPU tasks. The formula used is:

A=P(1+rn)ntA = P \left(1 + \frac{r}{n}\right)^{nt}A=P(1+nr​)nt

where:

• AAA is the amount of money accumulated after nnn years, including interest.

• PPP is the principal amount (the initial amount of ETH staked).

• rrr is the annual interest rate (yield from GPU tasks).

• nnn is the number of times that interest is compounded per year.

• ttt is the time in years.

3. Real-Time Adaptation

The algorithm continuously adapts to changes in the market and computational demands by analyzing real-time data inputs. This ensures optimal GPU usage and maximizes the growth of staked ETH.