Micron technology, inc. (20240289597). TRANSFORMER NEURAL NETWORK IN MEMORY simplified abstract
Contents
TRANSFORMER NEURAL NETWORK IN MEMORY
Organization Name
Inventor(s)
Stewart R. Watson of Boise ID (US)
Dmitry Vengertsev of Boise ID (US)
Ameya Parab of Millburn NJ (US)
TRANSFORMER NEURAL NETWORK IN MEMORY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240289597 titled 'TRANSFORMER NEURAL NETWORK IN MEMORY
The abstract of this patent application describes the implementation of a transformer neural network in a memory using a resistive memory array. The memory array consists of programmable memory cells that store weights of the neural network and perform operations accordingly.
- Implementation of a transformer neural network in a memory using a resistive memory array
- Programmable memory cells store weights of the neural network
- Memory array performs operations consistent with the transformer neural network
Potential Applications: - Artificial intelligence - Machine learning - Data processing
Problems Solved: - Efficient storage and retrieval of neural network weights - Improved performance of transformer neural networks
Benefits: - Faster processing speeds - Reduced energy consumption - Enhanced accuracy in data analysis
Commercial Applications: Title: "Enhanced Memory Array for Neural Networks" This technology can be utilized in various industries such as: - Healthcare for medical imaging analysis - Finance for fraud detection - Automotive for autonomous driving systems
Prior Art: Researchers can explore prior art related to resistive memory arrays and neural network implementations to understand the existing technology landscape.
Frequently Updated Research: Stay updated on advancements in resistive memory technology and transformer neural networks to leverage the latest innovations in this field.
Questions about Transformer Neural Network Implementation in Memory:
1. How does the resistive memory array improve the performance of the transformer neural network?
- The resistive memory array enhances performance by efficiently storing and retrieving weights of the neural network, leading to faster processing speeds.
2. What are the potential challenges in implementing a transformer neural network in a memory using programmable memory cells?
- Some challenges may include optimizing memory cell programming for specific neural network architectures and ensuring compatibility with existing memory technologies.
Original Abstract Submitted
apparatuses and methods can be related to implementing a transformer neural network in a memory. a transformer neural network can be implemented utilizing a resistive memory array. the memory array can comprise programmable memory cells that can be programed and used to store weights of the transformer neural network and perform operations consistent with the transformer neural network.
