Baidu Research, the research arm of the Chinese tech giant, has published a study highlighting the top ten technology trends for 2023.
Trends identified by Baidu Research include building large AI models, the convergence of digital, virtual and real technologies, autonomous transportation, robotics, scientific and quantum computing, privacy computing, AI for sustainable development, and growing interest in the ethics and governance of AI. The report highlights the potential of AI for industrial modernization and social progress, as well as addressing sustainability challenges.
Trend 1: creating large models
This trend refers to the use of large and complex AI models, known as “big models,” across industries to improve productivity. Large models based on deep learning platforms are capable of working with a wide range of tasks and languages. This makes them useful in many industries, such as aerospace, finance and energy.
The maturation of big model technology is facilitating the development and application of AI in new areas, leading to the emergence of a big model industry ecosystem and making “inclusive AI” a reality, modernizing thousands of industries.
Inclusive AI, on the other hand, is the idea of making AI accessible and useful to all people, regardless of their background, socioeconomic status or location. It aims to ensure that AI systems are developed and used in a fair, transparent and non-discriminatory manner and meet the needs of all members of society. Inclusive AI also aims to ensure that anyone can participate in the development, implementation and management of AI and benefit from its use.
Trend 2: convergence of digital and real technologies
Growing demand for AI infrastructure is driving deeper integration of digital technologies with the real economy. China’s 14th Five-Year Plan and 2030 Development Outlook places great emphasis on the development of the digital economy, as the sector is seen as providing huge untapped innovation opportunities and room for growth. Intelligent computing centers, deep learning platforms and AI models are now laying the foundation for digital transformation in a number of industries and areas of the real economy, especially in the manufacturing industry.
Trend 3: symbiosis of virtual and real
Web 3.0 technology is creating a new type of online space, leading to disruptive innovation in the metaverse. New digital infrastructure and tools make it possible to create a rich virtual world that moves from being parallel to the physical to becoming increasingly integrated with it.
According to Baidu researchers, Web 3.0 technologies can create a new multicentric, more open and fair web space where users can share information more securely. Virtual modeling and AI technologies will enable the creation of more accurate and intelligent digital twins in shopping, manufacturing, leisure and other areas. Neural networks offer a new model for creating content in the field of graphic and other media.
Trend 4: autonomous transport
Autonomous transport will gain new capabilities, which will lead to progress in this area. As autonomous vehicles move from highways to cities, the complexity of perception and decision-making increases.
Further improvement of technologies is necessary, so in the future the development of autonomous cars will be determined by the demand for more modern technologies, such as V2X (vehicle-to-everything – transport for everything), V2G (vehicle-to-grid – [energy] from transport to the network) and V2 °C (vehicle-to-cloud – from transport to the cloud), as well as the integration of new technologies such as 5G and Edge Computing.
The latter is translated into Russian as “edge computing.” It is a data processing method in which calculations are performed on devices at the edge of the network rather than in a large data center or cloud. This allows for faster processing and lower latency because data does not have to be sent to a remote location for processing and returned back. Simply put, it’s a way to bring the power of the cloud closer to where the data is collected. Autonomous cars that are equipped with powerful computers for assessing the situation on the roads can also act as such a mini-data center.
Trend 5: Robotics
The adoption of industrial robotics is accelerating, addressing labor shortages. Countries around the world are facing aging societies and the ongoing effects of a global pandemic, and many industries will face long-term workforce shortages in the future. Many countries are actively developing automation technologies as a possible solution to the problem.
The maturity of key technologies such as artificial intelligence, big data and cloud computing has provided a constant and powerful impetus to the development of automation, and AI-enabled robots of all kinds are showing the potential to improve real-time perception, intelligent decision making and optimal control.
Trend 6: Scientific Computing
Neural networks have become an aid in scientific research, changing the paradigm of interdisciplinary research. The success of models such as AlphaFold has shown that AI can have a huge impact on scientific computing and is changing the research paradigm in many disciplines. Developers are increasingly using AI technologies to solve scientific problems that are too complex and difficult to solve using traditional methods.
Trend 7: Quantum Computing
Breakthroughs in core technologies continue to drive the industrialization of quantum computing. In 2023, significant advances are expected in the field of quantum computing. The performance of quantum chips will improve, the ease of use of the cloud quantum computing platform will increase, and the barrier to entry into this field will decrease.
The development of quantum algorithms with practical value is expected, serving areas such as artificial intelligence, materials modeling, fintech and biopharmaceuticals. As these and other technologies improve, market demand for quantum software and hardware integrated solutions will grow.
Trend 8: Confidential Computing
This trend refers to the use of technology to ensure the protection and privacy of personal data. Privacy computing ensures data interoperability across platforms and allows organizations to balance getting value from large amounts of data with security and trust.
Confidential computing platforms are increasingly being used in areas such as finance, communications, medicine and the internet to protect data and enable secure data exchange. Attention to computing privacy has become increasingly important as the market value of data increases and more laws are passed to ensure information security.
Trend 9: AI for Sustainable Development
AI technology is increasingly being used to address environmental and sustainability issues. Researchers see this trend as increasingly important as the world faces climate change and resource depletion. AI helps eliminate these problems by generating new solutions in the areas of energy efficiency in buildings, green transport and environmental monitoring.
Optimization and decision making using neural networks can help reduce energy consumption and carbon emissions, and improve resource management and conservation.
Trend 10: AI ethics and governance
Neural networks are becoming more widespread, and the world is faced with ethical issues such as data privacy, bias in AI results, and transparency of algorithms. To address these issues, a framework for the ethics and governance of AI is being developed.
These frameworks will be critical to ensuring the responsible and ethical use of AI, the fair distribution of benefits from neural networks, and the management and mitigation of risks.
Baidu Research is the research organization of Baidu, a leading Chinese-language Internet search service provider. She conducts cutting-edge research in a number of areas such as natural language processing, computer vision and big data, with a particular focus on developing technologies that can be used to improve real-world applications of AI.
The organization publishes research papers and reports on technology trends, and collaborates with other companies in the development and application of AI technologies.
