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In recent years, the digital economy has promoted a new driving force for global economic development, and it is also a new engine for China's high-quality development. Relying on digital technology to achieve a new round of industrial transformation and seize the commanding heights of the global value chain has become the focus of competition among countries. China proposes to build a digital China and strive to build new advantages in national competition.
In order to better understand the development of global digital technology, Alibaba Research Institute and Zhipu AI recently jointly released the "2023 Global Digital Technology Development Research Report" . Based on the data of the AMiner science and technology intelligence platform, the report uses bibliometric methods to create a "portrait" of the frontiers of digital technology research, revealing the degree of innovation activity, and summarizes the top ten trends of global digital technology in 2023 on the basis of systematic and objective analysis methods.
1. Ten trends of global digital technology
Through the continuous tracking of the Top 1 core papers in the field of digital technology from 2012 to 2021, the report screened out ten hot cutting-edge technologies in the field of digital technology: biological big data, generative adversarial networks (GANs), immersive Extended Reality (XR), quantum computers, AI cracking protein and genetic structures, mobile edge networks, explainable AI, federated learning, hybrid computing and energy blockchain technology --
Trend 1: Biological Big Data
With the continuous in-depth exploration of living systems and the emergence and development of various other high-throughput omics technologies, the scope of bioinformatics research has continued to expand. Various omics data (transcriptome, proteome, non-coding RNA group, Epigenetic group, metabolome, metagenomic group, etc.) and interpretation at the level of biological systems continue to expand, and life sciences start from qualitative description to achieve dynamic, accurate and quantitative interpretation.
Trend 2: Generative Adversarial Network Algorithms
As a popular direction in the field of artificial intelligence, generative adversarial networks (Generative adversarial networks) have been widely used in image and vision, speech and language, information security and other fields. In the future, with the continuous iteration of deep learning represented by GANs, AIGC will flourish, and the output effect may gradually be realistic and close to human works.
Trend 3: Immersive Extended Reality Entertainment Platform
Extended reality is the key device for connecting virtuality and reality in the metaverse. With the continuous development of the extended reality industry chain and technology, and the gradual prosperity of content applications, the entire metaverse entertainment ecology is continuously enriched, and the immersive extended reality entertainment platform is expected to usher in an explosion.
Trend 4: Development of quantum prototypes and dedicated processors
At present, the development of quantum computers has transitioned from the basic research stage dominated by universities and research institutes to the "quantum hegemony" research stage dominated by innovative companies such as Google and IBM. With the continuous emergence of quantum computer development results, the problem of universal quantum computer development will be solved in the next five years, and quantum processors that can be actually used will be landed.
Trend 5: AI decoding protein structure
In 2021, AlphaFold, Deepmind's protein decoding prediction system, was born. At the same time, the company also announced the structure of about 350,000 proteins, and this achievement was selected as one of the top ten scientific breakthroughs of 2021 by Science. With the continuous development of artificial intelligence technology, the problem of modeling proteins with intrinsic disorder properties and proteins whose structure is changed by post-translational modification or environmental conditions is expected to be solved in the future.
Trend Six: Mobile Edge Computing Network
With the rise of the Internet of Things, 5G, industrial automation, and smart manufacturing, mobile edge computing between physical entities and industrial connections is playing an increasingly important role, and has gradually achieved centralization and intelligence. Its low latency, Features such as high bandwidth, personalization, high security, and high privacy meet the needs of distributed services and automatic industrial control.
Trend 7: Explainable AI
Due to the diversity of values and value systems in human society, explainable artificial intelligence will be developed in the future to strengthen the understanding between humans and machines, so that artificial intelligence technology can jump out of the "black box" and establish interpretable, understandable, and Trusted artificial intelligence systems have become a trend.
Trend Eight: Federated Learning Technology Based on Algorithmic Models and Security and Privacy
In recent years, federated learning, as an important technology to solve the problem of data islands, has attracted widespread attention in the industry and has been widely used in finance, healthcare, and smart cities. In the future, the development of federated learning technology will be associated with multiple fields such as edge computing, blockchain, and network security, so as to better utilize its privacy, efficiency, and convenience.
Trend Nine: Hybrid Computing
With the development of the Internet of Everything market, the industry has gradually realized that a single computing method cannot solve all problems. Field-specific high-efficiency application components, so as to better meet the high-efficiency processing needs of wireless interconnection, video processing, image recognition, intelligent manufacturing and other fields.
Trend Ten: Energy Blockchain
Aiming at the problems existing in each module in the Energy Internet application system, blockchain technology can rely on its own chain characteristics and unique block structure to integrate into all levels of the Energy Internet to solve related problems in the Energy Internet system. In the future, the creation of a blockchain integrated energy system can effectively promote the production of clean energy and the timely and efficient consumption and utilization of energy, improve the comprehensive utilization rate of regional energy, and achieve the goal of energy conservation and environmental protection on the basis of ensuring economy and stability.
2. Comparison of global digital science and technology research strength
In addition to cutting-edge new technologies, the report also focuses on the global comparison of scientific research strength in the field of digital technology. The report found that from the perspective of the "quantity and quality" of global digital technology papers, the overall influence of digital technology papers in China and the United States is roughly equal. Although there is still a 4% gap between the number of papers in the field of digital technology in China (506,775) and the United States (525,794), the average number of citations in China is 4 times more than that in the United States, which shows that the overall influence of papers in the field of digital technology in China is comparable to that in the United States. About the same.
In addition, the number of papers in the UK and Canada lags far behind China and the United States, but the average citations of their papers are significantly higher than those in China and the United States, which shows that the influence of digital science and technology papers in the two countries still occupies an important position in the world.
China lags significantly behind the United States in research excellence. Top 1% papers cited globally in a certain field (hereinafter referred to as "Top 1% papers") are called "top papers", which represent outstanding academic research achievements in this field. In the field of digital technology, the number of top 1% "top papers" in China (7,096) is significantly less than that of the United States (9,634), and the average citations are also significantly behind the United States.
In addition, it is worth mentioning that the number of digital science and technology papers published by the Chinese Academy of Sciences ranks first in the world. Among the top 10 institutions for the number of digital science and technology papers in the world, the top three institutions are the Chinese Academy of Sciences (59,487), the University of California (49,111) and the French Research University Alliance (UDICE) (48,217); In addition, there is another institution in China, the University of Chinese Academy of Sciences (18,381 articles), which also ranks among the top 10; Harvard University and the U.S. Department of Energy have the highest average citations, the former is 50 times/article, and the latter is 45 times/article. It shows that the two have shown strong research and innovation capabilities in the field of digital technology.
The research shows that China has already experienced a "golden cross" with the United States in terms of the growth of the number of overall papers and the number of Top1% papers. In 2019, China achieved a "golden cross" with the United States in terms of the overall number of papers published, and in 2020, China once again achieved a "golden cross" with the United States in the number of Top1% papers, which shows that China not only surpasses the United States in the total number of papers, but also in The number of "top papers" surpasses that of the United States, and its advantage with the United States is expanding year by year.
From the perspective of global digital technology patents, China is a big country in digital technology patents, and the number of digital technology patents in China is far ahead of the world. China has a total of 387,989 digital technology patents, 2.9 times that of the second-ranked United States, and 1.6 times that of the next nine countries combined. China's overall digital application technology research and development capabilities are second to none in the world.
Among the top 10 institutions for high-value patents in the world, China's Huawei and Alibaba are on the list. South Korea's Samsung, Microsoft and Google are the world's top three high-value patent giants, with 1,061, 630 and 592 patents respectively. The other top 10 institutions are, in order, Qualcomm, Huawei, IBM, Apple, Philips, Alibaba and Sony. China's Huawei and Alibaba have entered the list, but the strength of patent reserves between Chinese digital technology giants and international giants such as Samsung, Microsoft and Google is quite different.
The global digital technology high-value patent reserve strength has maintained a pattern of "one super and many strong" for a long time. Judging from the changes in the number of high-value patents in the past 10 years, the world's major digital technology powers are in a downward trend (one of the reasons is that it takes a long time for the patent value to appear), but the United States and Japan, South Korea, China, Germany and other digital technology powers are still Maintaining a large advantage, it is difficult to expect the latter to catch up with the former in a short period of time.
3. Comparison of the strength of the global digital technology talent pool
The report found that from the perspective of digital technology talents, China has a large talent base, but lacks high-level talents, and lags behind the United States seriously. The total number of global digital technology talents is 775,000, of which China has 128,000, ranking first, accounting for 17% of the global total, 1.5 times that of the second-ranked United States, and 8.3 times that of third-ranked Japan . However, there are only 7,000 high-level digital talents in China (ie, H-index ≥ 20, the same below), accounting for only 9% of the global total, and only 21,000 in the United States, accounting for 25% of the world. 35%. This shows that China has a large base of digital technology talents, but the reserve of high-level talents is insufficient, and it lags far behind the United States.
China's high-level talents are concentrated in universities, while the talent pool of American high-tech companies is not inferior to that of top universities. From the perspective of the distribution of global digital technology talent institutions, the Chinese Academy of Sciences ranks first with 4,722 people, ahead of the second-ranked University of California (2,623 people); there are also Chinese institutions that have entered the top 10 globally Two, namely the University of Chinese Academy of Sciences (1,462 people, sixth place) and Tsinghua University (1,305 people, eighth place).
From the perspective of international scholar cooperation, the cooperation between Chinese and American scholars is the most active bilateral cooperation in the world. But it started cooling down in 2018. From 2012 to 2021, in the field of digital technology, Chinese and American scholars have jointly produced 1,954 papers with Top 1% citations, which is the most fruitful bilateral cooperation in global scientific research (the second is the cooperation between American and British scholars, with a total output of 1,528 articles). However, since 2018, the growth rate of collaborative papers by Chinese and American scholars has been declining.
The report shows that the world's top scientific research teams in digital technology are basically dominated by American institutions. The world's top research teams in digital technology (Top 10) basically come from top universities in the United States (such as Stanford University, Carnegie Mellon University, University of California, Massachusetts Institute of Technology, Columbia University, Cornell University, etc.), technology giants (such as Google, Research institutions under Microsoft, IBM, etc.) (as shown in the table below).
The report shows that the world's top scientific research teams in digital technology are basically dominated by American institutions. The world's top research teams in digital technology (Top 10) basically come from top universities in the United States (such as Stanford University, Carnegie Mellon University, University of California, Massachusetts Institute of Technology, Columbia University, Cornell University, etc.), technology giants (such as Google, Research institutions under Microsoft, IBM, etc.) (as shown in the table below).
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