This is the fourth consecutive year that Baidu Research has released its top 10 tech trends Outlook
Our choice of these 10 trends relied on several key considerations:
First, the core technology foundation continues to solidify.
Deep learning platforms, together with AI big models, have constructed a solid foundation for industrial intelligence, paving the way for further industrial intelligence upgrades. The integration of digital intelligence and the real world provides broad market space and strong incentives for the consolidation of the underlying technology. Privacy computing has become an important cornerstone in the development of data security governance and data element marketization.
Second, AI’s cross-domain integration ability is growing stronger.
The development of AI technology brings huge value for cross-domain and cross-disciplinary integration and innovation, represented by Al for Science. AI for Science is developing as an increasingly mature tool and system to transform concepts into real-world applications, driving a scientific research paradigm shift and the development of new industries. AI-enabled robots are being increasingly used in work scenarios that require large amounts of the workforce to improve labor productivity.
Third, intelligent innovation is increasingly pragmatic.
Based on a solid intelligent foundation, the digital economy and the real economy are accelerating their integration and promoting the upgrade of the industrial system. At the same time, new innovation directions represented by web 3.0, the metaverse, autonomous driving, AI-generated content and quantum technology will also move rapidly in their development and applications.
Baidu Research is sharing its predictions for tech trends in 2023 with the aim of finding a clear direction for the practical application of AI and technology. We hope that this will help us to identify the right path, promote sustainable development, and strive for technological self-reliance.
Baidu Research's Top 10 Tech Trends
Trend 1: Big Model Building – Big models for industries emerge, providing intelligent upgrades across a wide range of sectors.
AI big models are evolving in the direction of cross-language, cross-task and cross-modality, becoming a major trend in today’s AI development. Based on deep learning platforms, the efficiency of big model technology is continuously improving, with strong generalization potential and high-level standardization, leading to an increasingly lower threshold for AI development and application. With the growing maturity of the underlying big model technology, "industry big models" have begun to be applied in the fields of aerospace, finance and energy, with an AI infrastructure built around the needs of each specific industry, resulting in an "AI + industry" structure. Baidu expects that as industry big models play a role in a growing number of fields in the future, the result will be the emergence of a wider industry big model ecosystem, making "inclusive AI" a reality through the AI-driven intelligent upgrade of thousands of industries.
Trend 2: Digital-Real Convergence - The increasing demand for AI infrastructure drives deeper integration of digital technology with the real economy.
China's 14th Five-Year Plan and Vision 2030 both place a strong focus on the development of the digital economy, seeing this sector as a source of tremendous untapped innovative power and space for growth. Today, intelligent computing centers, deep learning platforms and AI models are already developing to form a new AI infrastructure, providing a foundation for digital transformation in a range of industries and fields in the real economy, particularly the manufacturing industry. In the next few years, the construction of this new AI infrastructure is set to become one of the important pillars of the development of the digital economy and a focus of investment by local governments, significantly contributing to regional economic development and industrial upgrading. As AI infrastructure expands into more scenarios, we expect to see the rise of new products and new business models with industrial applicability.
Trend 3: Virtual-Real Symbiosis - Web 3.0 technology creates a new type of online space, leading to disruptive innovation in the metaverse industry.
Newly emerging digital infrastructure and tools have allowed for the creation of a content-rich virtual world, which has evolved from being parallel to the physical world to being increasingly integrated with the physical world. This trend is set to accelerate and deepen in 2023, driven by new breakthroughs in many key digital technologies.
Web 3.0 technologies will create a new multi-centered, more open, fair and secure web space where users can exchange information and value with more safety. Virtual simulation and AI technologies will allow for the creation of more accurate and intelligent digital twins in shopping, manufacturing, leisure and other fields. AI-generated content will bring a new model of content creation for drawing, painting, and other media. Combined with the immersive experience services brought by VR/AR and the high-speed data transmission capability provided by 5G, the availability of a wide-ranging and rich metaverse industry is expected to accelerate, hosting product and service models that provide a new wave of disruptive innovation.
“The progress of big models has allowed us to fully experience the charm of AI technology in fields such as text, image, and video creation. Take film production as an example: If you master this content creation ability, you can almost complete many important tasks and become a talented creator. With your own designed ‘virtual actors’, you can become a truly ‘independent’ film producer and director,” said Dr. Hua Wu, Chair of the Baidu Technical Committee.
Trend 4: Autonomous Driving - Autonomous driving sees new upgrades, leading progress in intelligent transportation.
As autonomous driving enters urban settings, both the difficulty of perceiving complex environments and the difficulty of processing massive amounts of data are seeing major improvements. Traditional small models are no longer able to meet the requirements of high-level autonomous driving, making AI big models the latest focus of autonomous driving technology. This AI big model technology enables self-driving cars to effectively expand semantic recognition data and improve the efficiency of long-tail problem-solving exponentially. This rapid progress in technology means that in 2023, the commercialization of autonomous driving in major cities in China will see simultaneous growth in both the scope of operation and fleet size, elevating the market penetration rate of intelligent vehicles with autonomous driving capabilities to new levels. The intelligent vehicle industry will decisively move from an experimental stage to full maturity.
Trend 5: Robotics - The use of industrial robotics accelerates, addressing labor shortages.
With countries across the globe confronting an aging society and the continued repercussions of the global pandemic, numerous industries are facing the prospect of serious long-term labor shortages in the future. Many countries have been actively developing automation technology as a possible solution. The maturity of key technologies such as artificial intelligence, big data, and cloud computing has injected a constant and powerful impetus into automation development, with AI-enabled robots of all kinds showing potential for major improvements in real-time perception, intelligent decision-making, and optimal control. The growing maturity of AI-enabled robot technology means they can be increasingly used in construction, mining, disaster relief, and other work scenarios that require large amounts of manpower. In addition, increasingly sophisticated humanoid robot products have the potential to act as domestic housekeepers, undertaking simple handling, sweeping, care and other work, helping to eliminate the need for many routine daily chores, unleashing the productivity of the human workforce and improving the overall quality of life.
Trend 6: Scientific Computing - AI technology has become a valuable research aid, transforming the paradigm of multidisciplinary research.
The success of models such as AlphaFold has shown that AI technology can have a huge impact on scientific computing and is changing the research paradigm in many disciplines. More and more scientific computing tools have begun to emerge from AI for Science, as developers attempt to use AI technologies to solve problems that are too complex and difficult to solve by traditional scientific computing, improving system modeling and analysis capabilities in the process. Even more powerful scientific computing tools are poised to emerge in the future, making AI an important scientific research tool with unique value in application fields ranging from physics to chemistry, materials science and medicine.
Trend 7: Quantum Computing - Breakthroughs in core technologies continue to drive the industrialization of quantum computing.
Quantum computing will continue to make major advances in a number of key technology directions in the coming year. Numerous technical lines of quantum chip performance indicators will continue to improve, cloud-native quantum computing platform ease of use will be greatly enhanced, and the development threshold will be further reduced to provide more powerful, rich and professional services. More quantum algorithms with practical value will be developed, serving fields including artificial intelligence, materials simulation, fintech and biopharmaceuticals. With the improvement of these and other technologies, the market demand for quantum software and hardware integrated solutions will grow, driving further integration of quantum computing industry chain resources and showing more commercial application value. At the same time, public attention to quantum information science will continue to increase, and the future of quantum education will further drive the maturity and growth of the quantum market and industry ecosystem.
Trend 8: Privacy Computing - Privacy computing platforms enable data interoperability while balancing value creation with security and trust.
The growing marketization of data is just one of many trends that have highlighted the increasingly urgent need for data security governance in recent years. New policies and laws to safeguard data security have led privacy computing technology to enter a rapid development stage. More and more organizations in fields such as finance, communication, medical care, and the Internet have begun building their own privacy computing platforms, expanding and deepening application scenarios, as well as bringing new demands for data interconnection between different platforms. Such demands suggest the need for a "horizontal and vertical" trusted data circulation network. The development of such networks is poised to drive accelerated iteration in privacy computing technology in the next few years, with new application scenarios emerging as privacy computing platforms become an important cornerstone for promoting data security governance and driving a healthier data market in many industries, helping to shape a data industry that balances value creation, safety and reliability.
Trend 9: Ethics in Technology - Explainable AI technology promotes "mutual trust," making reliable and controllable technology a new competitive advantage.
The rapid growth of artificial intelligence is one of many new developments in science and technology that has presented society with new ethical questions and potential risks, and attracted the concern of governments around the world. In 2022, China issued the landmark "Opinions on Strengthening Ethical Governance of Science and Technology" and submitted a "Position Paper on Strengthening Ethical Governance of Artificial Intelligence" to the United Nations, calling for a principle of "human-centered intelligence for good" to ensure that artificial intelligence remains safe, reliable and controllable. Technology companies and scientists are also actively exploring “explainable” AI technologies, aiming for more effective human-machine communication in the context of value alignment, allowing AI to truly understand human intentions and achieve more predictable AI governance. In a more highly intelligent and digital society, having manageable and controllable AI technology capabilities will become a new competitive advantage for enterprises.
Trend 10: Sustainability - The focus on green, low-carbon, and sustainable energy grows, with key breakthroughs in edge computing and advanced computing.
In recent years, under the influence of sustainable development, promoting energy saving and cost reduction has become an important evolutionary direction for new technologies. In particular, edge computing takes into account the real-time and elasticity of computing, able to reduce the transmission of massive data, saving significant data transmission and energy costs. The synergy work of edge computing, 5G, and AI will enable further development of a low-carbon economy. Advanced computing is improving the scale of computing power, while reducing the cost and improving efficiency at multiple levels, including computing theory, architecture, and system. More new technological breakthroughs are set to emerge focusing on green, low-carbon and sustainable development capabilities, and their application on the ground is expected to bring new potential to promote environmental protection, health, energy and material security, improving the quality of the human living environment.