Development Trends of AI Chip Products and Strategies of Leading Brands

Table of Contents

1. Types of AI Chip Products

2. Characteristics and Development Trends of Neural Network Chips
2.1 Neural Network Systems Can Mimic Human Brain Using VLSI
2.2 Neural Network Chips Enables More Powerful AI Applications Through Deep Learning Algorithms

3. Strategies of Leading Brands in Different Applications
3.1 GPU-centric NVIDIA Xavier Chip Dedicated to Supporting Autonomous Driving
3.2 AMD Instinct Chips Committed to Improving Computing Performance
3.3 The Acquisition of Xilinx by AMD Helps Fill AMD's FPGA Product Gap
3.4 Intel Launches Agilex with F/I/M Series Targeting Different Applications Following the Acquisition of Altera
3.5 Intel Introduces NPU Products to Collaborate with Partners for the Development of Neural Network Computing
3.6 Apple and Samsung Incorporate NPU in Their Mobile Processors
3.7 Tesla's Autonomous Driving Chips Uses an NPU as Computing Core

4. Analyst's Perspective

Appendix
List of Companies

List of Tables
Table 1 Classification of AI Chip products by Application and Computing Mode
Table 2 Simulation of Silicon Neurons Mimicking Brain Neuron Operations
Table 3 AI Processor Types
Table 4 Autonomous Driving Processors of Nvidia
Table 5 Comparison of AMD CDNA Architecture GPU Products
Table 6 Intel Agilex Chips
Table 7 Comparison of Apple AI ICs and Samsung SoCs

List of Figures
Figure 1 The Illustration of Biological Neural Systems and Neural Network Systems
Figure 2 The Role of Neural Network and Deep Learning in AI
Figure 3 Thee Features of Deep Learning
Figure 4 Nvidia Xavier Chip Architecture
Figure 5 The Illustration of Apple Smartphone SoC Configuration
Figure 6 Tesla Hardware 3 FSD and Chip Architecture