18646489. MODEL TRAINING SYSTEM AND METHOD simplified abstract (HUAWEI TECHNOLOGIES CO., LTD.)
Contents
- 1 MODEL TRAINING SYSTEM AND METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MODEL TRAINING SYSTEM AND METHOD - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Model Training System
- 1.13 Original Abstract Submitted
MODEL TRAINING SYSTEM AND METHOD
Organization Name
Inventor(s)
MODEL TRAINING SYSTEM AND METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18646489 titled 'MODEL TRAINING SYSTEM AND METHOD
Simplified Explanation
This patent application describes a model training system that uses MEMS and processors to jointly train a model by transmitting data through an optical transmission channel.
Key Features and Innovation
- System includes MEMS and S×C processors for joint model training.
- MEMS construct optical transmission channel between nodes.
- S×C processors run model training and adjust parameters based on target data.
- Enables efficient and synchronized model training across multiple processors.
Potential Applications
This technology can be applied in:
- Machine learning and AI model training.
- Data analytics and pattern recognition.
- High-performance computing and parallel processing systems.
Problems Solved
- Synchronizing model training across multiple processors.
- Efficient data transmission between nodes.
- Optimizing parameter adjustments for model training.
Benefits
- Faster and more efficient model training.
- Improved accuracy and performance of trained models.
- Scalable for large-scale data processing tasks.
Commercial Applications
- This technology can be used in industries such as:
- Finance for predictive analytics.
- Healthcare for medical image analysis.
- E-commerce for recommendation systems.
Prior Art
Readers can explore prior research on MEMS, optical transmission, and parallel processing systems for related technologies.
Frequently Updated Research
Stay updated on advancements in MEMS technology, optical communication, and parallel computing for potential improvements in model training systems.
Questions about Model Training System
How does the optical transmission channel improve data transfer in model training?
The optical transmission channel allows for high-speed and low-latency data transfer between nodes, enhancing the efficiency of model training.
What are the advantages of using MEMS in the model training system?
MEMS enable the construction of precise and reliable optical transmission channels, ensuring accurate data transmission for synchronized model training.
Original Abstract Submitted
This application provides a model training system and method. The system includes a first group, where the first group includes an MEMS and S×C processors, S is a quantity of nodes in the first group, C is a quantity of processors in one node, and both S and C are positive integers, the MEMS, configured to construct an optical transmission channel between any two of the S nodes, and the S×C processors, configured to jointly train a model. In one iteration of joint model training, the S×C processors are configured to run model training in respective processors, to obtain respective corresponding data. At least two of the S×C processors transmit target data through the optical transmission channel. A processor that receives the target data may be configured to adjust a parameter for model training in the processor based on the target data.
