Alibaba Cloud Provides its Forecast of the Leading Tech Trends of 2021
Alibaba DAMO Academy, the global research initiative by Alibaba Group, provides its forecast of the leading trends that would shape the tech industry in the year ahead. From the application of third-generation semiconductor materials, AI-driven R&D of medicines and vaccines, to automatic optimization of data management system and data intelligence-powered agriculture, technology breakthroughs are expected to accelerate and make impacts across sectors in the economy and the society at large.
The following are highlights from the Academy’s predicted top 10 tech trends in 2021:
The application of third-generation semiconductor materials, represented by GaN and SiC, will expand to new industries
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 application possible. For example, SiC-based devices are used for automobile inverters and GaN-based fast chargers are emerging in the market. In the next five years, the world will witness third-generation semiconductor materials spring up in areas such as 5G base stations, new energy vehicles, ultra-high-voltage power grids, and data centers.
Quantum error correction and practical utility of quantum computing will be the top priority of the “post-quantum-supremacy” era
The year 2020 is the first year to pass after quantum supremacy was achieved. In 2020, investors worldwide flocked to the quantum computing field, related technologies and ecosystems thrived, and numerous quantum computing platforms rose to prominence. In 2021, this trend will garner further attention from all corners of society. Quantum computing must deliver enough value to make it worthwhile. The mission in the “post-quantum-supremacy” era must be aligned across the industry: to tackle critical scientific and engineering problems through collaborative innovation and to pave the way for quantum error correction and practical utility, two milestones in quantum computing.
Breakthroughs in carbon-based materials will stimulate growth of flexible electronics
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. For example, carbon nanotubes are now used to produce large-scale integrated circuits that deliver better performance than silicon-based circuits of the same size. Graphene, a promising carbon-based material for flexible electronics, has also been put into large-scale production.
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 R&D of medicines and vaccines that were previously very time-consuming and costly. Compound screening, disease model generation, target identification, lead compound discovery, and lead drug optimization are some of the areas in which the technology excels.
The integration will reduce repetitive work and improve R&D efficiency. The beneficiaries will be the wider public, who can enjoy better medical care and pharmaceuticals in the near future.
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. This technology is the pillar and driving force of neural engineering. It analyses how the human brain works from a higher dimension. 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 have posed daunting challenges to computing task processing, storage cost control, and cluster management during traditional data processing. Manual management and tuning are unable to process massive amounts of data in diversified, complicated scenarios.
Therefore, AI-based automatic optimization of data management system will inevitably be the best choice for future 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. Autonomous, self-evolving data management systems will be made available.
Cloud-native technologies will reshape IT systems
Long product development cycles and low R&D efficiency in traditional software development have long been a source of pain. Cloud-native architectures featuring distribution, scalability, and flexibility look to be the cure. They allow enterprises to utilize and manage their heterogenous hardware devices and cloud computing resources more effectively. Cloud-native methodologies, tool sets, 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. The benefits that cloud-native technologies will bring are too numerous to mention. Just to name a few, the technologies help abstract away many layers of infrastructure components such as networks, servers, and operating systems, reduce computing costs, improve technology efficiency, lower barriers to developing applications on the cloud, and expand the scope of cloud applications.
Agriculture will be powered by data intelligence
Traditional agriculture can suffer from inefficiencies caused by poor land use and a disconnection between the production and retail sides.
Today, new-generation digital technologies, including 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. In addition, technologies such as 5G, IoT, and blockchain are utilized to control and trace the transportation of agricultural products, ensuring their safety and reliable delivery. With these new-generation digital technologies, agriculture is no longer highly dependent on the natural conditions and will be driven by intelligent data analytics.
Industrial intelligence leaps from single-point implementation to industry-wide implementation
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. After the outbreak of COVID-19 in early 2020, the remarkable resilience of the digital economy drew great attention from enterprises, digital technologies developed and spread rapidly, and more investments were injected into the construction of new infrastructure. 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. The industries include automobile, consumer electronics, high quality clothing, steel, cement, and chemical industries. Industrial intelligence will spring up in every corner and help closed-loop decision making in these industries. It will make an impact on a large scale, applying to the supply chain, production, asset management, logistics, and sales.
Intelligent operations centers will be a must for cities in the future
Smart city initiatives were first launched a decade ago and have sparked a significant improvement in city governance through digital technologies. However, when coping with the COVID-19 outbreak, a number of smart cities faced challenges. This is why 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. In addition, as the Artificial Intelligence of Things
(AIoT) becomes mature and widely applied and spatial computing technologies are improved, operations centers will be more intelligent. By keeping “digital twins” of cities, intelligent operations centers consider each city as a unified system and deliver city-wide services capabilities. Intelligent operations centers will become the digital infrastructure of cities in the future.