The high level of reliability associated with semiconductors, along with their compactness and low cost, have greatly supported the incorporation of these devices into numerous different applications ranging from optical sensors to energy systems. More recently, many industries, particularly those involved in the manufacturing of autonomous vehicles and artificial intelligence (AI) devices, have turned to semiconductor engineering as an ideal method to reduce the weight of their products while also enhancing their technological capabilities.
What is Semiconductor Engineering?
The individuals involved in engineering semiconductors are often charged with the complex task of designing, testing, verifying, integrating and manufacturing semiconductors for their target audience. The primary objective of the semiconductor engineer is to develop a device that can be easily integrated into the manufacturer’s component later on in the design process.
Automated Driving and Semiconductors
There are six different levels of vehicle autonomy, ranging from no autonomy at Level 0 to full autonomy at Level 5. The most recent advancements in autonomous driving have introduced Level 3 autonomous cars, which includes those capable of performing all aspects of the driving task while a driver is still present within the vehicle, to today’s roads. Current work in this industry is focused on achieving Level 4, or high automation vehicles, which do not require a human driver to be present at all.
As would be expected, there are extensive complexities and challenges associated with the development of autonomous driving vehicles. Vehicle autonomy relies heavily on the ability of cars to accurately gather information from sensors and make critical decisions in a rapid manner; therefore, the integration of semiconductor technology has proven to be a vital aspect in moving this area of the automotive industry forward.
In traditional vehicles, semiconductors can be found as microcontrollers for controlling emission release and antilock brakes as well as wireless modem chips for achieving internet connection while the car is in motion. The autonomous features of vehicles attributable to semiconductor technology include the chips used to provide the vehicle with “eyes” in the form of cameras and sensors present around their exterior. One of the most recent key players contributing to the application of semiconductors in autonomous vehicles is ON Semiconductor, which could potentially provide new cars with an 8.3-megapixel (MP) camera capable of full self-driving and advanced driver-assistance systems.
As AI technology has evolved over the past decades it has led to a significant increase in specialized technologies efficient in making medical diagnoses, synthesizing new chemicals, identifying the faces of criminals in a crowd, promoting the development of autonomous vehicles and much more. Although AI chips are not currently as advanced as many manufacturers would hope, future work in this area is expected to leverage semiconductor capabilities to improve the performance and reduce the power of these chips.
Researchers anticipate that the effect of future advancements in the AI industry will have dramatic effects on semiconductor engineering processes. More specifically, AI will revolutionize the way in which these devices are designed and interact with other semiconductor components, as well as provide improvements on the tools, hardware and software utilized by semiconductor developers.
The benefits associated with combining AI and semiconductor engineering processes include more rapid performance and processing rate by utilizing sparser algorithms to vary the accuracy of specific functions, as well as conduct processing and memory read/writes as a matrix. By changing the way in which data moves along the semiconductor chip, AI is expected to create an enormous difference in the amount of data that can be processed and stored by these devices in the near future.