Moore’s law states that the number of transistors in a semiconductor will double every two years. For decades, this theory has stood to be true. However, with processors’ size being already too small to challenge the laws of physics, this law may see its last days soon. Regardless, this does not mean that the semiconductor industry will stop innovations. Major players in the industry like Intel are investing billions of dollars in R&D programs each year to come up with more powerful chips that can power the next generation of consumer electronics. Added to that, with the rise of IoT, AI, machine learning, and big data, it’s high time the semiconductor industry ramps up its innovation game. With so much happening in the world of technologies, what trends are set to pick up speed in the semiconductor industry?
Rise of artificial intelligence
Businesses view AI as a source of differentiation from their competition. The next generation of AI is set to be incorporated into self-driving cars, autonomous drones, surgical robots, and smartphones. As a result, semiconductor companies are racing to meet the demands that arise from such innovations. Semiconductor chips consume a vast amount of power to perform such AI-intensive tasks. Graphics chips, which were originally developed for gaming are now being used for machine learning. Companies have gone as far as developing custom chips especially for machine learning and AI.
Going smaller but stronger
Intel, in 2017, announced that they would be working on 10nm chips. The new chip is set to deliver a 2.7x improvement in transistor density compared to the current 14nm chips. However, Intel is not alone in this rat race for the 10nm chips. Taiwan Semiconductor Manufacturing (TSM) and Samsung also have ambitious plans to shift to a 7nm node which could compete with Intel’s 10nm node in the power front. However, such a battle would only be beneficial to the consumers as they can get their hands on powerful gadgets.
Using analytics to optimize semiconductor processes
It is reported that a majority of semiconductor development projects are unable to meet their initial production schedules. Fabrication plants often overestimate their ability to handle complex tasks or underestimate the time required to complete the work. Analytics can help eliminate this guesswork of estimating project completion date along with manpower needs. The use of analytics can provide insights into equipment health to gain maximum performance out of it. Additionally, analytics can also help to predict process failure in a production step and prevent significant losses in the early stage of production.
The semiconductor industry is closer to the deployment of the 5G technology than ever. The need for extremely high data rates and low latency will force companies in the semiconductor industry to make high-speed and high-efficiency devices. Such demands will outline the need for a compound semiconductor. The semiconductor industry will be impacted as end-user devices and base stations will need to manage multiple-input and multiple-output (MIMO) and beam-steering technologies.