Nvidia corporation (20240160905). TECHNIQUES FOR COMPRESSING NEURAL NETWORKS simplified abstract
Contents
- 1 TECHNIQUES FOR COMPRESSING NEURAL NETWORKS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TECHNIQUES FOR COMPRESSING NEURAL NETWORKS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
TECHNIQUES FOR COMPRESSING NEURAL NETWORKS
Organization Name
Inventor(s)
TECHNIQUES FOR COMPRESSING NEURAL NETWORKS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240160905 titled 'TECHNIQUES FOR COMPRESSING NEURAL NETWORKS
Simplified Explanation
The patent application describes apparatuses, systems, and techniques for compressing neural networks. In one embodiment, one or more first neural networks are used to select one or more compressed neural networks based on accuracy and performance.
- Neural networks compression technology
- Selection of compressed neural networks based on accuracy and performance
Potential Applications
The technology could be applied in various fields such as:
- Image recognition
- Natural language processing
- Autonomous vehicles
Problems Solved
This technology addresses the following issues:
- Large neural network sizes
- High computational requirements
- Memory constraints
Benefits
The benefits of this technology include:
- Improved efficiency
- Reduced computational resources
- Faster inference times
Potential Commercial Applications
This technology could be utilized in industries such as:
- Healthcare
- Finance
- Manufacturing
Possible Prior Art
One example of prior art in neural network compression is the use of pruning techniques to reduce the size of neural networks while maintaining performance levels.
Unanswered Questions
How does this technology compare to existing neural network compression methods?
The article does not provide a direct comparison to other compression techniques.
What are the specific accuracy and performance metrics used to select compressed neural networks?
The article does not detail the specific metrics used for selection.
Original Abstract Submitted
apparatuses, systems, and techniques to compress neural networks. in at least one embodiment, one or more first neural networks are used to cause one or more compressed neural networks to be selected based, at least in part, on accuracy and performance of the one or more compressed neural networks.
