Apple inc. (20240273335). CUSTOMIZABLE CHIP FOR AI APPLICATIONS simplified abstract
Contents
CUSTOMIZABLE CHIP FOR AI APPLICATIONS
Organization Name
Inventor(s)
Saman Naderiparizi of Seattle WA (US)
Mohammad Rastegari of Bothell WA (US)
Sayyed Karen Khatamifard of Seattle WA (US)
CUSTOMIZABLE CHIP FOR AI APPLICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240273335 titled 'CUSTOMIZABLE CHIP FOR AI APPLICATIONS
Simplified Explanation: This patent application describes a computing device that includes a programmable logic device implementing a convolutional neural network, where each compute block of the device corresponds to a convolutional layer of the network.
Key Features and Innovation:
- Computing device with a programmable logic device implementing a convolutional neural network.
- Each compute block corresponds to a convolutional layer of the network.
- Memory blocks store data and parameters for each layer of the network.
Potential Applications: This technology can be used in various fields such as image recognition, natural language processing, and autonomous vehicles.
Problems Solved: This technology addresses the need for efficient and optimized implementation of convolutional neural networks in computing devices.
Benefits:
- Improved performance and accuracy in tasks such as image recognition.
- Efficient use of resources in implementing convolutional neural networks.
- Flexibility to adapt to different network architectures.
Commercial Applications: This technology has potential commercial applications in industries such as healthcare, security, and manufacturing where image recognition and data analysis are crucial.
Questions about Convolutional Neural Networks: 1. How does this technology improve the efficiency of implementing convolutional neural networks? 2. What are the key advantages of using a programmable logic device for implementing convolutional neural networks?
Frequently Updated Research: Stay updated on the latest advancements in convolutional neural networks and their applications in various industries to leverage the full potential of this technology.
Original Abstract Submitted
in one embodiment, a computing device includes an input sensor providing an input data; a programmable logic device (pld) implementing a convolutional neural network (cnn), wherein: each compute block of the pld corresponds to one of a multiple of convolutional layers of the cnn, each compute block of the pld is placed in proximity to at least two memory blocks, a first one of the memory blocks serves as a buffer for the corresponding layer of the cnn, and a second one of the memory blocks stores model-specific parameters for the corresponding layer of the cnn.
