17737888. NEURAL NETWORK TRAINING BASED ON CAPABILITY simplified abstract (NVIDIA Corporation)
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 Unanswered Questions
- 1.11 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 17737888 titled 'NEURAL NETWORK TRAINING BASED ON CAPABILITY
Simplified Explanation
The patent application abstract describes apparatuses, systems, and techniques to train one or more neural networks using a processor with circuits based on capabilities.
- Neural networks are trained using a processor with specialized circuits.
- The training process is based on the capabilities of the neural networks.
Potential Applications
This technology could be applied in various fields such as:
- Artificial intelligence
- Machine learning
- Robotics
- Data analysis
Problems Solved
This technology helps in:
- Improving the efficiency of neural network training
- Enhancing the performance of neural networks
- Streamlining the process of developing AI systems
Benefits
The benefits of this technology include:
- Faster training of neural networks
- Higher accuracy in AI applications
- Increased productivity in machine learning tasks
Potential Commercial Applications
The potential commercial applications of this technology could be seen in:
- AI software development companies
- Robotics companies
- Data analytics firms
- Autonomous vehicle manufacturers
Possible Prior Art
One possible prior art could be the use of specialized hardware accelerators for neural network training, which have been developed by various companies in the past.
Unanswered Questions
How does this technology compare to existing methods of neural network training?
This article does not provide a direct comparison with existing methods of neural network training, leaving the reader to wonder about the advantages and disadvantages of this new approach.
What specific capabilities are considered during the training process?
The abstract mentions training based on capabilities, but it does not specify what these capabilities are or how they are determined, leaving a gap in understanding for the reader.
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.