1，Small sample size

For example, in classification problems, each category only requires a small number of samples, and the recognition accuracy can reach a practical level。

2，Compact network

The network weight is more efficient, that is, it can be used in a strong cloud, but also run in a resource intensive edge computing environment。

3，Stronger generalization

Suloki artificial intelligence technology, based on small sample neural networks, requires very few samples and has strong generalization ability, which is also the essence of neural networks。

Main application scenarios：

In theory, the scenarios where deep learning can be applied, including suloki artificial intelligence technology, can also be applied; However, from a practical perspective, suloki artificial intelligence technology still focuses on scenarios with limited sample sizes or very high dataset construction costs, such as metaverse 3D content。

Artificial Intelligence Simulation Training Environment