Nvidia corporation (20240095536). NEURAL NETWORK TRAINING BASED ON CAPABILITY simplified abstract
Contents
- 1 NEURAL NETWORK TRAINING BASED ON CAPABILITY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 NEURAL NETWORK TRAINING BASED ON CAPABILITY - 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 Original Abstract Submitted
NEURAL NETWORK TRAINING BASED ON CAPABILITY
Organization Name
Inventor(s)
Xingqin Lin of San Jose CA (US)
Lopamudra Kundu of Sunnyvale CA (US)
Christopher Hans Dick of San Jose CA (US)
NEURAL NETWORK TRAINING BASED ON CAPABILITY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095536 titled 'NEURAL NETWORK TRAINING BASED ON CAPABILITY
Simplified Explanation
The patent application describes apparatuses, systems, and techniques to train one or more neural networks using a processor with specific circuits.
- Neural networks are trained based on capabilities.
- The processor includes circuits to facilitate training.
- Training is done at least in part based on capabilities.
Potential Applications
This technology could be applied in various fields such as:
- Healthcare for medical diagnosis and treatment recommendations.
- Finance for fraud detection and risk assessment.
- Autonomous vehicles for object recognition and decision-making.
Problems Solved
This technology helps in:
- Improving accuracy and efficiency of neural network training.
- Enhancing the capabilities of neural networks in various applications.
- Streamlining the process of training neural networks.
Benefits
The benefits of this technology include:
- Faster and more accurate neural network training.
- Enhanced performance of neural networks in real-world applications.
- Increased adaptability and scalability of neural networks.
Potential Commercial Applications
This technology could be commercially applied in:
- Software development for AI-driven applications.
- Data analytics companies for predictive modeling.
- Robotics industry for autonomous systems development.
Possible Prior Art
One possible prior art for this technology could be the use of specialized hardware accelerators for neural network training, such as GPUs or TPUs.
What are the specific capabilities that the neural networks are trained based on?
The abstract mentions that the neural networks are trained based on one or more capabilities. However, it does not specify what these capabilities are. It would be interesting to know the specific capabilities that are used for training neural networks in this context.
How do the circuits in the processor facilitate the training of neural networks?
The abstract mentions that the processor includes circuits to cause the training of neural networks. It would be beneficial to understand how these circuits work and what role they play in the training process. This information could provide insights into the technical aspects of the innovation.
Original Abstract Submitted
apparatuses, systems, and techniques to cause one or more neural networks to be trained. in at least one embodiment, a processor includes one or more circuits to cause one or more neural networks to be trained based, at least in part, on one or more capabilities.
