18747834. COMMUNICATION METHOD AND APPARATUS simplified abstract (Huawei Technologies Co., Ltd.)
Contents
COMMUNICATION METHOD AND APPARATUS
Organization Name
Inventor(s)
Xiaomeng Chai of Shanghai (CN)
Yiqun Wu of Boulogne Billancourt (FR)
COMMUNICATION METHOD AND APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18747834 titled 'COMMUNICATION METHOD AND APPARATUS
The patent application describes a method and apparatus to enhance the performance of an artificial intelligence model by reducing transmission overheads of training data.
- The method involves obtaining data and information from a node, where the information indicates a data augmentation method for the data.
- A training dataset for the model is then determined based on the data and information obtained from the node.
Potential Applications:
- This technology can be applied in various fields such as machine learning, deep learning, and artificial intelligence research.
- It can be used in industries where large amounts of data need to be processed efficiently.
Problems Solved:
- Reducing transmission overheads of training data.
- Improving the performance of artificial intelligence models.
Benefits:
- Enhanced performance of artificial intelligence models.
- Efficient processing of large datasets.
- Reduction in training data transmission overheads.
Commercial Applications:
- This technology can be utilized in industries such as healthcare, finance, and e-commerce for data analysis and predictive modeling.
Questions about the Technology: 1. How does this method improve the performance of artificial intelligence models? 2. What are the potential implications of reducing transmission overheads of training data in various industries?
Frequently Updated Research:
- Stay updated on advancements in data augmentation techniques and their impact on artificial intelligence model training.
Original Abstract Submitted
This disclosure provides a communication method and apparatus, to reduce transmission overheads of training data and improve performance of an artificial intelligence model. The method includes: obtaining first data and first information from a first node, where the first information indicates a data augmentation manner of the first data; and determining a first training dataset of a model based on the first data and the first information.