In 2017, the CES and MWC exhibitions marked a turning point as self-driving cars became the central focus of the tech industry. These vehicles offered a glimpse into the future of consumer electronics, and semiconductor companies, long interested in the automotive sector, quickly moved to seize the opportunity. Intel made a bold move by acquiring Mobileye, a leader in computer vision chips, for $15 billion. NVIDIA followed suit, partnering with Bosch to develop an artificial intelligence system aimed at revolutionizing autonomous driving.
The traditional automotive industry chain is being restructured, with a growing emphasis on semiconductor investments. As self-driving technology and vehicle connectivity advance, the role of semiconductors in cars is becoming more critical. In 2020, many manufacturers set clear deadlines for achieving full autonomy, signaling the arrival of a new era. ADAS (Advanced Driver Assistance Systems) and connected car infrastructure are now essential components, pushing the industry toward greater electronic integration.
Vehicle components are increasingly becoming more electronic, with systems like navigation, entertainment, and safety features such as reverse radar and ADAS gaining prominence. This shift has led to a rise in investment from semiconductor and electronic component manufacturers, who are now focusing heavily on automotive electronics development.
Major players like Texas Instruments, Renesas, and NXP have already established themselves as key suppliers in automotive electronics. However, companies traditionally focused on PCs and mobile devices—such as Intel, Qualcomm, and NVIDIA—have also entered the market. To secure a place in the ADAS central processor space, these companies have been forming strategic alliances, investing in R&D, and even making major acquisitions. Their goal is to build strong "Computer Vision" capabilities, which are essential for the next generation of autonomous vehicles.
Why is computer vision so important? It enables machines to interpret visual data and respond accordingly, a crucial element for autonomous driving. With higher-resolution cameras and increasing image data in ADAS systems, semiconductor manufacturers must provide more powerful processors to handle complex visual tasks.
Traditional architectures like X86 or ARM-based Cortex-A processors are not optimized for such tasks, often leading to inefficiencies. That’s why companies like Intel and ARM are investing heavily in technologies that enhance their ability to process visual data efficiently.
Intel has taken multiple steps to strengthen its position in computer vision. In May, it acquired Itseez, a company known for its advanced object detection algorithms used in driver assistance systems. Later, it bought Movidius, a leader in mobile image processing, and recently acquired Mobileye, which brings expertise in machine vision, deep learning, and high-precision mapping. These moves show Intel's serious commitment to dominating the self-driving market.
Qualcomm and NVIDIA have also made significant strides. Qualcomm strengthened its position by acquiring NXP, enhancing its capabilities in DSP technology to improve computer vision performance. Its Snapdragon 835 chip includes a Hexagon 68 DSP, allowing more efficient and accurate visual processing. NVIDIA, on the other hand, leverages its GPU power, continuously improving its computing capabilities. The Xavier processor, built on a 16nm FinFET process, offers 20 TOPS of performance, making it ideal for complex AI tasks.
In conclusion, achieving true self-driving requires high-resolution imaging and powerful computer vision processing. Companies like Intel, NVIDIA, and Qualcomm are each taking unique approaches to meet this demand. Through partnerships, acquisitions, and technological innovation, they are positioning themselves to lead the future of autonomous vehicles. Who will ultimately win the race remains to be seen.
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