Emerging AI Chip Application Trends in Smart Automotive Electronics
The global semiconductor market in 2023 faced numerous adverse factors, including talent shortages, geopolitical risks, and rising interest rates. These challenges collectively contributed to a slowdown in market growth. However, despite these headwinds, specific segments within the semiconductor industry, particularly automotive applications, experienced notable advancements. International companies are increasingly focusing on enhancing autonomous driving capabilities and improving in-car service experiences. This progress heavily relies on AI chips that boost computational speed, which is essential for handling the extensive data processing and analysis required by future vehicles during operation. This report provides an overview of global trends in smart automotive electronics, examines how semiconductors can play a role in automotive development, and explores the development of leading AI chipmakers in smart auto electronics, including Nvidia, Qualcomm, and Tesla.
1. GLOBAL TRENDS IN SMART AUTOMOTIVE ELECTRONICS
1.1 Automotive Industry Moving Towards CASE
2. SEMICONDUCTORS AS KEY DRIVERS OF AUTOMOTIVE DEVELOPMENT
2.1 Increased Demand for AI Computing Power in Smart Cars
3.LEADING BRANDS' AI CHIPS FOR SMART AUTO ELECTRONICS
3.1 Nvidia
3.2 Qualcomm
3.3 Tesla
4. MIC PERSPECTIVE
4.1 Trends towards Electric and Smart Automobiles Driving AI Chip Demand
4.2 Computational Demand for Automotive AI Chips Moving towards Edge Computing
4.3 International Players Leveraging In-house AI Chips to Gain Competitive Edge
Appendix
List of Companies
1.1 Automotive Industry Moving Towards CASE
2. SEMICONDUCTORS AS KEY DRIVERS OF AUTOMOTIVE DEVELOPMENT
2.1 Increased Demand for AI Computing Power in Smart Cars
3.LEADING BRANDS' AI CHIPS FOR SMART AUTO ELECTRONICS
3.1 Nvidia
3.2 Qualcomm
3.3 Tesla
4. MIC PERSPECTIVE
4.1 Trends towards Electric and Smart Automobiles Driving AI Chip Demand
4.2 Computational Demand for Automotive AI Chips Moving towards Edge Computing
4.3 International Players Leveraging In-house AI Chips to Gain Competitive Edge
Appendix
List of Companies
LIST OF FIGURES
Figure 1: Computing Architecture of Nvidia's Cockpit-driving Integration Solution
Figure 2: Snapdragon Ride SoC
Figure 3: Snapdragon Ride Vision
Figure 4: Tesla's Central Computer Architecture
Figure 1: Computing Architecture of Nvidia's Cockpit-driving Integration Solution
Figure 2: Snapdragon Ride SoC
Figure 3: Snapdragon Ride Vision
Figure 4: Tesla's Central Computer Architecture
