From the application of third-generation semiconductor materials, AI-driven R&D of medicines and vaccines, to automatic optimization of the data management systems and data intelligence-powered agriculture, technology breakthroughs are expected to accelerate and make impacts across sectors in the economy and the society at large. Here are the top 10 predictions for trends that will help shape the tech sector in 2021 and beyond:
The application of third-generation semiconductor materials
Third-generation semiconductor materials, represented by gallium nitride (GaN) and silicon carbide (SiC), boast high-temperature resistance, high breakdown voltage, high frequency, high power, and high radiation resistance. However, for a long time, the application of these materials has been limited only to a narrow scope of fields due to their complex processing methods and high costs. In recent years, breakthroughs in material growth and device fabrication have helped reduce the costs of third-generation semiconductor materials, making a wider range of applications possible.
Quantum error correction and practical utility of quantum computing
In 2020, investors worldwide flocked to the quantum computing field, related technologies and ecosystems thrived, and numerous quantum computing platforms rose to prominence. For this year, this trend will garner further attention from all corners of society. Quantum computing must deliver enough value to make it worthwhile.
Breakthroughs in carbon-based materials
Flexible electronics deliver stable performance even after mechanical deformations such as bending, folding, and stretching. They are preferred in wearable devices, electronic skins, and flexible screens. In the past, flexible materials were simply not flexible enough or could not compete with rigid silicon-based materials in terms of electrical characteristics, which limited their commercial use. In recent years, groundbreaking developments in carbon-based materials have allowed flexible electronics to go far beyond their previous capabilities.
AI accelerates the R&D of medicines and vaccines
Artificial intelligence (AI) technology has been widely adopted to interpret medical images and manage medical records while its application in vaccine development and the clinical research of drugs is still in the pilot stage. As new AI algorithms are emerging and computing power is reaching new heights, this technology will make it easier to complete the R&D of medicines and vaccines that were previously very time-consuming and costly.
Brain–computer interface technology allows us to go beyond the limits of the human body
Brain-computer interface technology is essential for new-generation human-machine interactions and collaborative intelligence between humans and machines. A brain-computer interface forms a direct communication pathway between the brain and an external device. It acquires, analyzes, and translates brains signals to control machines. In the future, brain-computer interface technology will help control robotic arms more precisely than ever before and help patients who are fully conscious but cannot speak or move to overcome their physical limitations.
Data processing will become autonomous and self-evolving
The rapid development of cloud computing and exponential growth in the amount of data has posed daunting challenges to computing task processing, storage cost control, and cluster management during traditional data processing. AI and machine learning will be adopted in a variety of fields, such as intelligent cold/hot data separation, anomaly detection, intelligent modeling, resource scheduling, parameter tuning, stress testing data generation, and index recommendation. This way, costs for computing, processing, storage, and O&M will be reduced.
Cloud-native architectures featuring distribution, scalability, and flexibility look to be the cure. They allow enterprises to utilize and manage their heterogeneous hardware devices and cloud computing resources more effectively. Cloud-native methodologies, toolsets, best practices, products, and techniques allow developers to focus only on creating new applications. In the future, chips, development platforms, applications, and even computers will be cloud-native.
Agriculture will be powered by data intelligence
Today, new-generation digital technologies, including the Internet of Things (IoT), AI, and cloud computing, are being applied to the agriculture industry throughout the production process to retail. New-generation sensors help obtain real-time farmland data. Big data analytics and AI expedite the processing of large amounts of agricultural data. Agricultural practitioners can monitor crops, implement precision breeding, and allocate environmental resources on demand.
Industrial intelligence has been mainly used to meet partial requirements because its implementation is costly and complicated, data at the supply side is isolated, and the ecosystem is immature. These factors helped build a picture in which we can see industrial intelligence leap from single-point implementation to industry-wide implementation. This is true particularly in manufacturing industries that have mature IT systems. It will make an impact on a large scale, applying to the supply chain, production, asset management, logistics, and sales.
Intelligent operations centers for smart cities
Smart city initiatives were first launched a decade ago and have sparked a significant improvement in city governance through digital technologies. Both UAE and KSA are some of the emerging economies that have great ambitions to transform their cities into smart ones. When coping with the COVID-19 outbreak, a number of smart cities faced challenges. Therefore, intelligent operations centers are widely accepted and deployed to maximize the usage of data resources and promote global, fine-grained, and real-time governance and public services.