Baidu Research, a leading AI research lab initiated by Baidu, provides its forecast of top 10 tech trends for 2022. This is the third consecutive year Baidu Research has released its outlook on tech trends on the frontier of innovation.
The top 10 tech trends shared by Baidu Research span a wide range of topics including: Large-scale Pre-training Model, AI for Science, AI-powered Computational Biology, Privacy Computing, Integration of Quantum Hardware and Software, Autonomous Driving, Deep Space Exploration, Human-machine Symbiosis, Green AI, and Inclusive AI.
“Artificial intelligence has become a key driving force of innovation and development, due to its rapidly evolving core technologies, stronger cross-domain connectivity, and the expanding collection of core industry applications. In this time of uncertainty, it is our hope that AI will illuminate the road of innovation and propel the ship of development,” said Haifeng Wang, CTO of Baidu and Head of Baidu Research.
The top 10 tech trends center on three key pillars: AI core technologies, interdisciplinary & cross-domain research, and industrial & social values.
AI core technologies are making continuous breakthroughs, with more proven cases in integrated innovation. In interdisciplinary and cross-domain research, AI constitutes a shared variable for scientific research and technological development. AI is also accelerating the development of relevant industries such as autonomous driving, robotics, aerospace and healthcare. It has also played a key role in driving progress towards goals such as carbon emissions reduction and social inclusion.
This is the third consecutive year Baidu Research shares its yearly tech trend forecast. Previously, its forecast on trends like Digital and Virtual Humans and Digital Transportation have become a reality.
#1 Large-scale Pre-training Model: The large-scale pre-training model reflects a trend of knowledge enhancement, unified cross-modal modeling, and multi-learning, reducing dependence on labeled data and accelerating real-world applications.
#2 AI for Science: AI for Science has emerged as a new area of research with the potential to change the paradigm of scientific research.
#3 AI-Powered Computational Biology: Computational biology based on AI technology continues to develop rapidly, achieving breakthroughs in multiple foundational research and application scenarios.
#4 Privacy Computing: Privacy computing has attracted growing attention. It will provide fuller utilization of data and create an infrastructure that builds stronger user confidence.
#5 Integration of Quantum Hardware and Software: The integration of hardware and software in quantum computing is being more widely implemented, as real-life demand accelerates the merging and innovation in between quantum computing and other industries.
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#6 Autonomous Driving: Autonomous driving technology is entering a new driverless stage, as multiple “Robocar” models connect technology with application scenarios.
#7 Deep Space Exploration: AI and aerospace technology are unlocking new possibilities for the intelligent exploration of deep space.
#8 Human-machine Symbiosis: Social distancing restrictions have added impetus to human-machine symbiosis. The combination of virtual and real intelligent interaction will soon become a part of work and life.
#9 Green AI: AI development increasingly takes into account green and low-carbon, helping to achieve carbon peaking and carbon neutrality goals.
#10 Inclusive AI: AI will become more inclusive, with an emphasis on value creation allowing more attention to be focused on the needs of SMEs and minority groups.