Wall Street: Why did Intel split up Mobileye and go public? Challenges from Chinese counterparts are fierce
Dec 17,2021
A few days ago, Intel Corporation announced that it plans to promote Mobileye's listing in the United States in mid-2022 through an initial public offering (IPO). What are the underlying reasons behind it? In this regard, Robert Castellano, a senior analyst at Seekingalpha, an analysis of Wall Street stock market analysis, made an analysis.
Mobileye currently provides advanced driver assistance systems (ADAS) and corresponding products to more than 30 automakers that have chosen EyeQ as their assisted driving technology. These automakers include Audi, BMW, Fiat Chrysler, General Motors, Honda, and Hyundai. , Kia, Nissan and Volkswagen.
According to Intel's data, Mobileye's annual revenue in 2020 was 967 million U.S. dollars, and in 2019 it was 879 million U.S. dollars, an increase of 10% year-on-year. The company expects to achieve record annual revenue this year, which is expected to be more than 40% higher than 2020. In 2020, Mobileye’s EyeQ chip shipments were 19.3 million, compared with 2.7 million in 2014, representing a compound annual growth rate of 39%.
While Mobileye has attracted many customers, Qualcomm announced its cooperation with BMW at the 2021 Investor Conference. BMW's new cars will use Qualcomm's self-driving platform Snapdragon Ride (including chips) from 2025.
In addition to the performance gap discussed later in this article, Intel’s 3940 chip belongs to the E3900 series, which was released in 2016 using a 14nm process. At first, it was mainly used for consumer-grade chips, and then it was separately classified as car-grade chips. The car-grade chip is the A3900 series, and the cost is about US$40. Qualcomm's S8155 is a mass-produced 7nm automotive-grade chip, which costs about $100.
Most self-driving cars use systems with cameras, radars, laser sensors, and other technical systems to assess road conditions and adjust driving behavior. These vehicles may have adaptive cruise control, lane adjustment, and automatic braking, steering, and acceleration systems.
The level of autonomous driving is inseparable from the computing power of the chip. The autonomous driving industry generally believes that the chip computing power required for level 2 (Trillion Operations Per Second, "TOPS") is less than 10 TOPS, level 3 requires 30 to 60 TOPS, and level 4 requires 100. TOPS or higher, level 5 requires 1000 TOPS or higher. It is precisely because of this that chip computing power has become the core force of competition among various chips.
If a car company uses multiple chips to set up an autonomous driving domain controller, they can reach up to 1024 TOPS, which can support Level 4 autonomous driving.
Although the computing power TOPS of a single chip is a key indicator, it is not the only indicator. Autonomous driving is a complex system that requires vehicle-road cloud collaboration. Therefore, in the autopilot chip competition, in addition to the core, there is also the collaboration of software and hardware, as well as the platform and tool chain.
At present, there are many competitors in the automotive AI chip market, which have adversely affected Intel and Mobileye, including Qualcomm and Nvidia, Tesla and the Chinese company Huawei, Horizon, Black Sesame and Xin Chi Technology.
Seekingalpha also listed detailed information about Mobileye's competitors' products and plans.
Qualcomm
The Intel A3900 series is based on the X86 architecture design and was released in 2016, using a 14nm process. At first, it was mainly used for consumer-grade chips, and then it was separately classified as car-grade chips. The car-grade chip is the A3900 series, and the cost is about US$40. The upgraded version of EyeQ4, EyeQ5, will be released in 2020. EyeQ5 was only installed on Geely's Geely 001 model for the first time in the fourth quarter of this year. EyeQ5 adopts 7nm FinFET process, chip computing capacity is 24 TOPS.
SA8155P is an integrated next-generation car cockpit platform. It is a 7nm system-level chip, designed with custom hardware modules, including an eight-core CPU subsystem, and adopts the fourth-generation Qualcomm Kryo CPU based on the ARMv8 architecture. The system-level chip uses an efficient machine learning architecture, power consumption is less than 7 watts, and the chip's computing capacity can reach 10 TOPS.
Qualcomm's fourth-generation Snapdragon automotive digital cockpit platform SA8295P uses 5nm process technology, with a chip computing capacity of up to 30 TOPS.
SA8155P is an integrated next-generation car cockpit platform. It is a 7nm system-level chip, designed with custom hardware modules, including an eight-core CPU subsystem, and adopts the fourth-generation Qualcomm Kryo CPU based on the ARMv8 architecture. The system-level chip uses an efficient machine learning architecture, power consumption is less than 7 watts, and the chip's computing capacity can reach 10 TOPS. Qualcomm's fourth-generation Snapdragon automotive digital cockpit platform SA8295P uses 5nm process technology, with a chip computing capacity of up to 30 TOPS.
Nvidia
The Xavier processor has a programmable CPU, GPU and deep learning accelerator, and the chip's computing capacity can reach 30 TOPS. Nvidia's next-generation autopilot chip Orin chip will also begin mass production in 2022. The single computing power of the Orin chip is 254 TOPS, which is 10 times higher than the computing power of EyeQ5. NVIDIA Atlan's single system-on-chip computing capacity can reach 1000 TOPS (it is expected to provide samples to developers in 2023).
Huawei
Huawei is positioning it as a Tier 1 supplier and building a "5G automotive ecosystem" with the goal of the high-end autonomous driving market, which cannot be ignored.
The computing power of Huawei Ascend 310 chip can reach 16 TOPS, while the power consumption is only 8 watts. Ascend 610 has a chip computing capacity of up to 160 TOPS and is used for level 3 and level 4 autonomous driving. The 610 processor has a 64-bit quad-core CPU architecture and an advanced 4G LTE system, which can balance the power consumption and performance of high-end smartphones.
horizon
Horizon Robotics was established in 2015 to manufacture AI chips for autonomous vehicles and machines. It has also customized software for these chips, which can be installed on devices such as cars and smart speakers. Horizon Robotics announced its third automotive-grade AI chip Journey 5 and real-time in-car operating system TogetherOS. Journey 5's single-chip AI computing capacity can reach 128 TOPS. The target partners for the debut of Journey 5 are leading equipment manufacturers, including SAIC, Great Wall Motors, Jianghuai Automobile, Ideal Motors, Changan Automobile and BYD.
Black sesame
Black Sesame Intelligent Technology's new autonomous driving chip A1000 Pro is popular with record-setting computing performance among such chips produced by local companies. According to Black Sesame Intelligent Technology, the A1000 Pro is based on the company's A1000 chip, which has been optimized with a standard computing capacity of up to 106 TOPS and a maximum of 196 TOPS in acceleration mode. Black Sesame Intelligent Technology cooperates with companies such as NIO, SAIC, BYD, Dongfeng Motor, FAW Group and Bosch to provide solutions for L2/L3 advanced driver assistance systems and autonomous driving sensing systems.
Xin Chi Technology
Xin Chi Technology is a semiconductor company headquartered in China, focusing on next-generation high-performance automotive regulatory chip solutions. The V9T chip launched in 2021 can drive up to 1 TOPS. In 2022, Xin Chi Technology will launch the autonomous driving chip V9P/U, which has a computing capacity of 10 to 200 TOPS. The product has a higher degree of integration of computing power and can support Level 3 autonomous driving. In 2023, Xin Chi Technology will launch a V9S autopilot chip with higher computing capabilities. The chip was developed for the central computing platform architecture. The computing capacity is up to 500-1000 TOPS, which can support autonomous taxis for level 4 or level 5 autonomous driving. At present, Xin Chi Technology's V9 (automatic driving) adopts a 16nm process. This level of technology has fallen behind in the field of consumer electronics, but in the automotive industry, 16nm technology is still the mainstream trend.
Tesla
The fully autonomous driving chip (FSD chip, formerly Autopilot Hardware 3.0) is an autonomous driving chip designed by Tesla and launched in early 2019 for use in the company's internal cars. Tesla claims that the goal of the chip is level 4 and level 5 autonomous driving. It is manufactured using Samsung's 14nm process technology. The FSD chip includes 3 quad-core Cortex-A72 clusters, a total of 12 CPUs, operating at 2.2 GHz, a Mali G71 MP12 GPU, operating at 1 GHz, two neural processing units, operating at 2 GHz, and various Other hardware accelerators.
Tesla's self-driving cars will be driven by a computer based on its two new AI chips, each with a CPU, GPU and deep learning accelerator. The computer has a computing power of up to 144 TOPS, allowing it to collect data from a series of surround cameras, radar, ultrasound, and power deep neural network algorithms.
The following table shows the chip versions (current and planned versions) of these companies, as well as the TOPS of the chips. According to our report titled "Hot Integrated Circuits: Artificial Intelligence ("AI") Market Analysis, 5G, CMOS Image Sensors and Memory Chips", the computing power of NVIDIA ORIN chips can reach 200 TOPS, which is 9 times more than EyeQ5. Both Journey 5 of Horizon Robot and Ascend 610 of Huawei exceed EyeQ5 in computing power.
According to Intel's data, Mobileye's annual revenue in 2020 was 967 million U.S. dollars, and in 2019 it was 879 million U.S. dollars, an increase of 10% year-on-year. The company expects to achieve record annual revenue this year, which is expected to be more than 40% higher than 2020. In 2020, Mobileye’s EyeQ chip shipments were 19.3 million, compared with 2.7 million in 2014, representing a compound annual growth rate of 39%.
While Mobileye has attracted many customers, Qualcomm announced its cooperation with BMW at the 2021 Investor Conference. BMW's new cars will use Qualcomm's self-driving platform Snapdragon Ride (including chips) from 2025.
In addition to the performance gap discussed later in this article, Intel’s 3940 chip belongs to the E3900 series, which was released in 2016 using a 14nm process. At first, it was mainly used for consumer-grade chips, and then it was separately classified as car-grade chips. The car-grade chip is the A3900 series, and the cost is about US$40. Qualcomm's S8155 is a mass-produced 7nm automotive-grade chip, which costs about $100.
Most self-driving cars use systems with cameras, radars, laser sensors, and other technical systems to assess road conditions and adjust driving behavior. These vehicles may have adaptive cruise control, lane adjustment, and automatic braking, steering, and acceleration systems.
The level of autonomous driving is inseparable from the computing power of the chip. The autonomous driving industry generally believes that the chip computing power required for level 2 (Trillion Operations Per Second, "TOPS") is less than 10 TOPS, level 3 requires 30 to 60 TOPS, and level 4 requires 100. TOPS or higher, level 5 requires 1000 TOPS or higher. It is precisely because of this that chip computing power has become the core force of competition among various chips.
If a car company uses multiple chips to set up an autonomous driving domain controller, they can reach up to 1024 TOPS, which can support Level 4 autonomous driving.
Although the computing power TOPS of a single chip is a key indicator, it is not the only indicator. Autonomous driving is a complex system that requires vehicle-road cloud collaboration. Therefore, in the autopilot chip competition, in addition to the core, there is also the collaboration of software and hardware, as well as the platform and tool chain.
At present, there are many competitors in the automotive AI chip market, which have adversely affected Intel and Mobileye, including Qualcomm and Nvidia, Tesla and the Chinese company Huawei, Horizon, Black Sesame and Xin Chi Technology.
Seekingalpha also listed detailed information about Mobileye's competitors' products and plans.
Qualcomm
The Intel A3900 series is based on the X86 architecture design and was released in 2016, using a 14nm process. At first, it was mainly used for consumer-grade chips, and then it was separately classified as car-grade chips. The car-grade chip is the A3900 series, and the cost is about US$40. The upgraded version of EyeQ4, EyeQ5, will be released in 2020. EyeQ5 was only installed on Geely's Geely 001 model for the first time in the fourth quarter of this year. EyeQ5 adopts 7nm FinFET process, chip computing capacity is 24 TOPS.
SA8155P is an integrated next-generation car cockpit platform. It is a 7nm system-level chip, designed with custom hardware modules, including an eight-core CPU subsystem, and adopts the fourth-generation Qualcomm Kryo CPU based on the ARMv8 architecture. The system-level chip uses an efficient machine learning architecture, power consumption is less than 7 watts, and the chip's computing capacity can reach 10 TOPS.
Qualcomm's fourth-generation Snapdragon automotive digital cockpit platform SA8295P uses 5nm process technology, with a chip computing capacity of up to 30 TOPS.
SA8155P is an integrated next-generation car cockpit platform. It is a 7nm system-level chip, designed with custom hardware modules, including an eight-core CPU subsystem, and adopts the fourth-generation Qualcomm Kryo CPU based on the ARMv8 architecture. The system-level chip uses an efficient machine learning architecture, power consumption is less than 7 watts, and the chip's computing capacity can reach 10 TOPS. Qualcomm's fourth-generation Snapdragon automotive digital cockpit platform SA8295P uses 5nm process technology, with a chip computing capacity of up to 30 TOPS.
Nvidia
The Xavier processor has a programmable CPU, GPU and deep learning accelerator, and the chip's computing capacity can reach 30 TOPS. Nvidia's next-generation autopilot chip Orin chip will also begin mass production in 2022. The single computing power of the Orin chip is 254 TOPS, which is 10 times higher than the computing power of EyeQ5. NVIDIA Atlan's single system-on-chip computing capacity can reach 1000 TOPS (it is expected to provide samples to developers in 2023).
Huawei
Huawei is positioning it as a Tier 1 supplier and building a "5G automotive ecosystem" with the goal of the high-end autonomous driving market, which cannot be ignored.
The computing power of Huawei Ascend 310 chip can reach 16 TOPS, while the power consumption is only 8 watts. Ascend 610 has a chip computing capacity of up to 160 TOPS and is used for level 3 and level 4 autonomous driving. The 610 processor has a 64-bit quad-core CPU architecture and an advanced 4G LTE system, which can balance the power consumption and performance of high-end smartphones.
horizon
Horizon Robotics was established in 2015 to manufacture AI chips for autonomous vehicles and machines. It has also customized software for these chips, which can be installed on devices such as cars and smart speakers. Horizon Robotics announced its third automotive-grade AI chip Journey 5 and real-time in-car operating system TogetherOS. Journey 5's single-chip AI computing capacity can reach 128 TOPS. The target partners for the debut of Journey 5 are leading equipment manufacturers, including SAIC, Great Wall Motors, Jianghuai Automobile, Ideal Motors, Changan Automobile and BYD.
Black sesame
Black Sesame Intelligent Technology's new autonomous driving chip A1000 Pro is popular with record-setting computing performance among such chips produced by local companies. According to Black Sesame Intelligent Technology, the A1000 Pro is based on the company's A1000 chip, which has been optimized with a standard computing capacity of up to 106 TOPS and a maximum of 196 TOPS in acceleration mode. Black Sesame Intelligent Technology cooperates with companies such as NIO, SAIC, BYD, Dongfeng Motor, FAW Group and Bosch to provide solutions for L2/L3 advanced driver assistance systems and autonomous driving sensing systems.
Xin Chi Technology
Xin Chi Technology is a semiconductor company headquartered in China, focusing on next-generation high-performance automotive regulatory chip solutions. The V9T chip launched in 2021 can drive up to 1 TOPS. In 2022, Xin Chi Technology will launch the autonomous driving chip V9P/U, which has a computing capacity of 10 to 200 TOPS. The product has a higher degree of integration of computing power and can support Level 3 autonomous driving. In 2023, Xin Chi Technology will launch a V9S autopilot chip with higher computing capabilities. The chip was developed for the central computing platform architecture. The computing capacity is up to 500-1000 TOPS, which can support autonomous taxis for level 4 or level 5 autonomous driving. At present, Xin Chi Technology's V9 (automatic driving) adopts a 16nm process. This level of technology has fallen behind in the field of consumer electronics, but in the automotive industry, 16nm technology is still the mainstream trend.
Tesla
The fully autonomous driving chip (FSD chip, formerly Autopilot Hardware 3.0) is an autonomous driving chip designed by Tesla and launched in early 2019 for use in the company's internal cars. Tesla claims that the goal of the chip is level 4 and level 5 autonomous driving. It is manufactured using Samsung's 14nm process technology. The FSD chip includes 3 quad-core Cortex-A72 clusters, a total of 12 CPUs, operating at 2.2 GHz, a Mali G71 MP12 GPU, operating at 1 GHz, two neural processing units, operating at 2 GHz, and various Other hardware accelerators.
Tesla's self-driving cars will be driven by a computer based on its two new AI chips, each with a CPU, GPU and deep learning accelerator. The computer has a computing power of up to 144 TOPS, allowing it to collect data from a series of surround cameras, radar, ultrasound, and power deep neural network algorithms.
The following table shows the chip versions (current and planned versions) of these companies, as well as the TOPS of the chips. According to our report titled "Hot Integrated Circuits: Artificial Intelligence ("AI") Market Analysis, 5G, CMOS Image Sensors and Memory Chips", the computing power of NVIDIA ORIN chips can reach 200 TOPS, which is 9 times more than EyeQ5. Both Journey 5 of Horizon Robot and Ascend 610 of Huawei exceed EyeQ5 in computing power.
ADAS is defined by one of the following six characteristic levels (L0-L5):
In 2020, the penetration rate of Level 2 autonomous driving in China will reach 15%. This means that nearly 4 million new cars are equipped with Level 2 autopilot systems. It is estimated that by 2030, self-driving cars will account for more than 40% of the total mileage, and the penetration rate of fully automatic new cars will reach 10%.
Wall Street predicts that from 2019 to 2030, the penetration rate of Chinese self-owned brand passenger cars from ADAS to Level 3 will increase from 20% to 75%. This means that the size of the chip market will increase from about US$50 million to more than US$1.5 billion. Chinese cars are less affected by the "shortage" of semiconductors. Similarly, Chinese independent brands will also use domestically-made automotive chips.
The strong demand in the Chinese market is critical to Mobileye and its competitors, because Huawei and Chinese start-ups will weaken Mobileye's market leadership. In summary, China Horizon Robotics is cooperating with leading equipment manufacturers, including SAIC, Great Wall Motors, Jianghuai Automobile, Ideal Motors, Changan Automobile and BYD-the original equipment manufacturers are all based in China.
SAIC is not only an investor in Horizon Robotics, but also an investor in Black Sesame Technology. In August 2020, SAIC stated that it has invested in more than a dozen leading domestic chip companies including Horizon Robotics and Black Sesame Technology.
From a global perspective, by 2025, only 15% of the world's vehicles will have no ADAS automatic driving system, and in 2020 this proportion will be 42%, and 40% of the vehicles will be equipped with a level 1 automatic driving system. Importantly, by 2025, 36% of vehicles will be equipped with L2 autonomous driving systems, an increase from 10% in 2020. Only 9% of vehicles have autonomous driving systems with Level 3 or higher features. Intel announced on December 7, 2021 that the company is planning to publicly list Mobileye's self-driving cars. Frankly speaking, this is not a "notorious" moment for Intel.
Autonomous driving technology is still in its infancy stage of development, and is far from reaching a mature stage. This makes the automotive autopilot chip market fiercely competitive, and Mobileye has been establishing partnerships with automotive companies for many years. Mobileye's system-level chip shipments were 19.3 million, while Horizon's chip shipments were nearly 500,000.
The real difference lies in the computing power. Although Mobileye's computing power is only 24 TOPS, the Journey 5 chip of Horizon Robot has 128 TOPS. The chip computing power required for level 2 autonomous driving is less than 10 TOPS, level 3 autonomous driving requires 30 to 60 TOPS, and level 4 requires more than 100 TOPS. This means that the horizon robot established in 2015 and Mobileye established in 1999 can achieve level 4 autonomous driving, while Mobileye stops at level 2 autonomous driving.
Mobileye and self-driving cars are not the strategic direction set by CEO Gelsinger for Intel. The later it goes public, the greater the resistance that Mobileye will face, and he is also worried about the lower IPO valuation.
This split is an important decision made by Intel, because Intel is engaged in the chip business, the company will use IPO funds to establish a new fab. In addition, STMicroelectronics designs EyeQ chips, and TSMC produces EyeQ chips. In recent years, Intel’s CPU share has lost to AMD and has fallen into a low period. In any case, this will not affect Intel’s goal of getting rid of the low period.
In 2020, the penetration rate of Level 2 autonomous driving in China will reach 15%. This means that nearly 4 million new cars are equipped with Level 2 autopilot systems. It is estimated that by 2030, self-driving cars will account for more than 40% of the total mileage, and the penetration rate of fully automatic new cars will reach 10%.
Wall Street predicts that from 2019 to 2030, the penetration rate of Chinese self-owned brand passenger cars from ADAS to Level 3 will increase from 20% to 75%. This means that the size of the chip market will increase from about US$50 million to more than US$1.5 billion. Chinese cars are less affected by the "shortage" of semiconductors. Similarly, Chinese independent brands will also use domestically-made automotive chips.
The strong demand in the Chinese market is critical to Mobileye and its competitors, because Huawei and Chinese start-ups will weaken Mobileye's market leadership. In summary, China Horizon Robotics is cooperating with leading equipment manufacturers, including SAIC, Great Wall Motors, Jianghuai Automobile, Ideal Motors, Changan Automobile and BYD-the original equipment manufacturers are all based in China.
SAIC is not only an investor in Horizon Robotics, but also an investor in Black Sesame Technology. In August 2020, SAIC stated that it has invested in more than a dozen leading domestic chip companies including Horizon Robotics and Black Sesame Technology.
From a global perspective, by 2025, only 15% of the world's vehicles will have no ADAS automatic driving system, and in 2020 this proportion will be 42%, and 40% of the vehicles will be equipped with a level 1 automatic driving system. Importantly, by 2025, 36% of vehicles will be equipped with L2 autonomous driving systems, an increase from 10% in 2020. Only 9% of vehicles have autonomous driving systems with Level 3 or higher features. Intel announced on December 7, 2021 that the company is planning to publicly list Mobileye's self-driving cars. Frankly speaking, this is not a "notorious" moment for Intel.
Autonomous driving technology is still in its infancy stage of development, and is far from reaching a mature stage. This makes the automotive autopilot chip market fiercely competitive, and Mobileye has been establishing partnerships with automotive companies for many years. Mobileye's system-level chip shipments were 19.3 million, while Horizon's chip shipments were nearly 500,000.
The real difference lies in the computing power. Although Mobileye's computing power is only 24 TOPS, the Journey 5 chip of Horizon Robot has 128 TOPS. The chip computing power required for level 2 autonomous driving is less than 10 TOPS, level 3 autonomous driving requires 30 to 60 TOPS, and level 4 requires more than 100 TOPS. This means that the horizon robot established in 2015 and Mobileye established in 1999 can achieve level 4 autonomous driving, while Mobileye stops at level 2 autonomous driving.
Mobileye and self-driving cars are not the strategic direction set by CEO Gelsinger for Intel. The later it goes public, the greater the resistance that Mobileye will face, and he is also worried about the lower IPO valuation.
This split is an important decision made by Intel, because Intel is engaged in the chip business, the company will use IPO funds to establish a new fab. In addition, STMicroelectronics designs EyeQ chips, and TSMC produces EyeQ chips. In recent years, Intel’s CPU share has lost to AMD and has fallen into a low period. In any case, this will not affect Intel’s goal of getting rid of the low period.