Semiconductors are materials that have an electrical connectivity between that of conductor material (generally metals) and non-conductor materials. Semiconductors are an essential component of electronic devices, predominantly central processing units (CPU), AI accelerators, and high-performance graphics processing units (GPU).  

Fully autonomous vehicles are vehicles that can drive themselves without human input. There are five levels of vehicle autonomy ranging from Level 1 to 5. The promise of AVs models is great – they could bring mobility to sections of the market that have never had access such as children, disabled people, and those otherwise unable to drive themselves. In addition, AVs could enable a brace of new businesses in the commercial space such as ride-hail services using robotaxis, on-demand freight logistics services, or mobile retail and service spaces that can be brought directly to the customer.   

However, the challenge of commercialising autonomous vehicles has proven equally great. The leap taken from level 1 autonomy to level 2, for example, is small compared to the jump in complexity needed for level 3 ‘eyes-off’ AV operation. These systems then look laughably simple compared to the level of complexity that will be demanded by truly self-driving level 4 and level 5 models, which might not even include controls for human drivers. Semiconductors will be essential in developments to achieve level 5 truly self-driving vehicles.  

Nevertheless, not all companies are equal when it comes to their capabilities and investments in the key themes that matter most to their industry. Understanding how companies are positioned and ranked in the most important themes can be a key leading indicator of their future earnings potential and relative competitive position.  

According to GlobalData’s thematic research report, Autonomous Vehicles, leading adopters of AVs include: NVIDIA, ASML, Amazon, Tesla, Alibaba, Baidu and Alphabet.  

Insights from top ranked companies  

NVIDIA  

NVIDIA has parlayed its GPU technology developed for the gaming industry into the core embedded supercomputer platform of choice for hyperscale data centres, crypto-currency mining rigs, and deep learning neural networks. In addition, it clearly intends on forming the AI processor core of the automotive industry of the future.  

Baidu Apollo, Audi, and Volvo have all partnered with NVIDIA to use its GPU technology in their vehicles. In addition, NVIDIA will supply Daimler with its Drive Orin platform – similar to Tesla’s Autopilot system-on-a-chip. This will equip Daimler’s cars with the hardware needed for self-driving but allow the company to trial a few different software providers without being tied to one.  

Baidu  

Long dubbed ‘China’s Google’, Baidu has emerged as China’s top AI operation. Currently, it focuses much of its AI efforts into its open-source operating system for AVs. Baidu’s Apollo self-driving platform hopes to do for smart cars what Google Android did for smartphones. Baidu is working with NVIDIA, Continental, Bosch, and Microsoft (the latter bringing its Azure cloud platform to the party) to help turn Apollo into the world’s leading open-source self-driving platform for third party original equipment manufacturers (OEMs). In April 2020, Baidu’s Apollo platform saw the launch of the ‘Apollo Go’ self-driving taxi service in Hunan province, China. This expanded to cover Beijing in September 2020 and Guangzhou in February 2021. 

By April 2021, the Beijing operation had been fully commercialised. In August 2021, Baidu added its self-designed Apolong II self-driving minibus to the Apollo Go platform, merging its robotaxi plans with its commercialised service. Later that same month, the company showed a concept for a level 5 self-driving car – one that can handle the dynamic driving task in all circumstances. 

Tesla  

Tesla is an audacious, PR-savvy agenda setter in the auto and alternative energy sectors. The company is at the forefront of AV technology through its Level 2 Autopilot and Full-Self Driving features. Unlike many rivals, Tesla has based its AV systems on 360-degree camera vision and ultrasonic sensors, using its own AI image processing to determine the safe path forward.  

Furthermore, Tesla can credibly claim to sit alongside Waymo, Baidu and Cruise in the vanguard of auto brain building. Using its network of cars equipped with Autopilot, Tesla claims to have racked up more than one billion miles of data which can enhance its machine learning system – although it’s unclear as to how many of those miles were covered with Autopilot actually engaged. 

To further understand the key themes and technologies disrupting the technology industry, access GlobalData’s latest thematic research report on Autonomous Vehicles.   

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