| 1 |
Description requirements of a specification |
- A specific means for implementing AI inventions (learning data/pre-processing/learning model, etc.) should be presented and described in a specification.
- A correlation between input data and output of a learning model should be described.
- Where data pre-processing technology is featured, a correlation between raw data and learning data should be specifically described.
- Reinforcement learning based AI technology should have an agent, environment, condition, actions and rewards as required features.
- AI-applied inventions may describe a general training model name (Description method).
|
| 3 |
Novelty/ Inventive step |
- Where AI technology is not specifically described, it is regarded as simple use of a disclosed AI technology.
- Specific means, such as pre-processing, learning model, learning data, etc., is specified, and if it is recognized that the means brings about ‘unexpected advantageous effect’, the inventive step is acknowledged.
- Where BM technology is simply systemized with a disclosed AI technology, the inventive step is denied.
- Where output data of an AI invention is specifically utilized and unexpected advantageous effect are produced accordingly, the inventive step is acknowledged.
- Where the industrial field is different, such aspects or effect is considered (e.g., the change of the industrial field or overcoming of technological difficulties)
|
