This is not a competition between two companies or laboratories, but a clash of civilizations (Shutterstock)
This is an age of conflict, but the conflicts between superpowers are no longer traditional. The equation of strength is no longer measured by the number of tanks or the range of intercontinental missiles. Now, the balance is determined by the scale of digital clouds, the speed of processors, and the accuracy of algorithms.
In a world where the map is shifting from geography to data, one of the most dangerous and profound confrontations in contemporary history is taking place: the struggle for leadership in artificial intelligence between the United States and China.
This is not a competition between two companies or laboratories, but a clash of civilizations, spanning from secret research centers' basements to the floors of the Pentagon, from Beijing's skyscrapers to university towns, filled with the intellect of a new generation. Artificial intelligence, its language models, combat drones, and complex systems have become the lens through which the civilizational gap between the two countries is measured.
China has clearly committed to surpassing the United States by 2030 to achieve global leadership in the field of artificial intelligence. The United States responded quickly: providing funding support, a fierce processor race, and large-scale alliances with Silicon Valley companies.
This article tells the story of this complex conflict, analyzing its tools and areas of engagement: from cyber fronts to battlefields, from the basements of scientific laboratories to algorithms that shape public opinion. We will delve into the depth of strategic shifts and examine the new battlegrounds.
The First Battlefield: Software and Information
In the contemporary technological arms race, both China and the United States are actively integrating artificial intelligence into the core of their military architectures, especially in command, control, communications, computers, intelligence, surveillance, and reconnaissance (C4ISR) systems.
But China's vision goes beyond merely modernizing existing systems; in its strategic thinking, artificial intelligence and big data are the cornerstone for supporting decision-making, setting goals, and even launching so-called "cognitive warfare or consciousness warfare."
Under this framework, the Chinese military refers to the next phase of military operations as "intelligentized warfare," an integrated framework where artificial intelligence connects sensors and launch platforms, automatically processes battlefield information, and even attacks the enemy's decision-making process itself.
In practice, Chinese defense companies have already begun promoting systems that embody this vision, such as the "Intelligent Precision Strike System" by North Industries. This system automatically schedules drones during People's Liberation Army exercises, using real-time data to "simulate the battlefield, track targets, formulate attack plans, distribute fire information, and execute follow-up strikes." These experiments demonstrate Beijing's ambitious attempt to blur the boundaries between human and machine roles.
In a video from the recent Zhuhai military exhibition, it can be seen that almost the entire target tracking and strike planning process has been automated, with only manual approval being the final authorization. Chinese commentators claim that these AI-driven interconnected weapons and sensor systems constitute what they call a "dynamic kill network," covering all battlefields including land, sea, and air.
In short, China's pursuit of artificial intelligence is not only aimed at accelerating routine tasks, but also at shaping the thoughts of the adversary.
A war analyst is overseeing the coordination of military team actions, using digital devices and virtual reality glasses to command combat forces (Shutterstock)
Strategic analysts explain that the writings on "intelligent warfare" in China explicitly focus on "cognitive warfare or consciousness warfare," which uses artificial intelligence to "directly control the enemy's will."
In contrast, the U.S. military is also heavily investing in artificial intelligence tools for information-age warfare, but its strategic motivations differ. The Pentagon currently states that it aims to achieve "decision advantage" for battlefield commanders by expanding the use of artificial intelligence and data analysis across all branches of the military.
The core of this trend is the U.S. major initiative, such as Joint All-Domain Command and Control (JADC2), aiming to connect satellites, ships, aircraft, cyber assets, and ground forces into a single, seamless integrated network.
Artificial intelligence is seen as the pillar of this system; algorithms will integrate intelligence from various domains (drones, sensors, satellites, cyber intercepts, etc.) and present it to commanders in summaries and instant insights.
Another example is the results of the now-ended collaboration project "Maven" between Google and the Pentagon, which used machine vision technology in drones and satellites on the battlefield to automatically detect people, vehicles, or missiles in real-time video.
At an artificial intelligence symposium held in early 2024, the Pentagon's AI director Craig Martel urged participants to imagine "a world where a battlefield commander can see everything they need to see... without waiting for reports or presentations."
In other words, artificial intelligence will directly and immediately shape the commander's situational awareness. The U.S. military is also testing AI-driven cyber operations, such as automatic network vulnerability scanning or predictive threat analysis.
Essentially, the U.S. approach is to use artificial intelligence as a "force multiplier." It can automatically perform tedious analyses, detect patterns in massive sensor data, and quickly provide recommendations so that human commanders can make decisions faster and more effectively. (For example, the U.S. Air Force has developed a prototype for an AI "toolbox" for cloud command and control, which can use AI tools to analyze data such as radio communication or mobile target detection).
Despite the intense competition, both sides are aware of the potential dangers. U.S. planners worry about over-reliance on these technologies or vulnerability to enemy cyber attacks, while PLA analysts warn that overconfidence in achieving "cognitive advantage" could lead to misleading decisions that mislead leadership. However, Chinese official publications undoubtedly show that they are actively integrating artificial intelligence into their information operations and psychological warfare.
A study by RAND on the Chinese People's Liberation Army's military theory showed that China has regarded "psychological warfare" as a key component of modern warfare, and has used advanced tools such as big data analysis and brain scanning technology to predict or influence the behavior of the enemy.
Chinese military theory reflects its increasing emphasis on "cognitive warfare," with the goal of controlling the opponent's cognition and decision-making as a key to victory. This trend is reinforced by the efforts of new military branches such as the Information Support Forces and the Strategic Support Forces. These units integrate capabilities in cyberspace, outer space, and electronic intelligence, applying artificial intelligence to propaganda, counter-information dissemination, and electronic warfare.
In contrast, U.S. official military theory remains relatively restrained when dealing with information warfare. U.S. joint doctrine focuses on "information operations," including psychological warfare, electronic warfare, and cyber deception, but its framework is mainly defensive and strategic. The U.S. investment focus is on countering foreign disinformation campaigns and using artificial intelligence to detect deepfakes and malicious bots.
Moreover, U.S. generals focus on technologies that help soldiers observe and shoot, rather than explicitly targeting the mind. Currently, the U.S. official strategy documents have not explicitly proposed the concept of "controlling the enemy's will." Nevertheless, the core technologies used by both sides—such as data mining, sentiment analysis, and targeted information delivery—are roughly similar. U.S. defense agencies fund research on artificial intelligence cognition—such as the U.S. Defense Advanced Research Projects Agency (DARPA)'s research on human perception and AI-based lie detection technology—and counter AI-based propaganda.
Defense Advanced Research Projects Agency (DARPA) (Social Media)
The Second Battlefield: Weapons and Equipment
Both China and the United States are seeking to integrate artificial intelligence into physical military hardware to create a new generation of autonomous and semi-autonomous weapons, ranging from aerial to ground, from aerial drones to "robot dogs" and ground-guided vehicles. This move aims to reduce soldier risk and expand military power.
In the field of autonomous drones, the competition is particularly intense. Both Chinese and U.S. militaries have a variety of drones for surveillance, attack, and camouflage missions.
China is a major exporter of drones, with Chengdu Aircraft Industry Group (CAIC) producing Wing Loong and CH series armed drones, which have been exported to conflict zones (such as Ukraine and the Middle East).
By contrast, the U.S. military uses not only experimental platforms like the MQ-25 Stingray, an autonomous refueling aircraft, but also MQ-9 Reaper and MQ-1 Predator drones for precision strikes.
However, this vision goes beyond the use of individual drones, proposing the concept of "drone swarms." According to a report by Associated Press in January 2024, military planners from both China and the United States are preparing for a new type of warfare in which AI-driven aerial and underwater drones "cooperate like bees" to overwhelm enemies with overwhelming advantages.
In this scenario, an operator can simultaneously command dozens of drones, which are pre-programmed to perform reconnaissance, attacks, or re-direction tasks without precise micro-management. An example of this relatively low-cost and efficient technology was the drone swarm attack on Russian missile launchers in Ukraine in mid-2025.
For these reasons, Chinese media and analysts assert that drone swarms are "inevitable" and that developing drone swarms is imperative. In fact, recent reports from Taiwan indicate that the Chinese military has accumulated tens of thousands of drones and is exploring incorporating unmanned boats and submarines into its arsenal.
In response, the U.S. Department of Defense has clearly funded the production of thousands of inexpensive disposable drones to form a deterrent around hotspots. The Pentagon believes that countering the opponent's large drone swarms requires the deployment of numerous low-cost drones on potential battlefields. General Samuel Pappalardo, Commander of the U.S. Indo-Pacific Command, stated that the plan would turn the Taiwan Strait into "a hell without pilots."
In short, although it is unclear which side currently has the technological advantage, both sides view drone swarm tactics as a new arms race similar to the Cold War. As one analyst described it, "Controlling drone swarms... will be much harder than controlling nuclear weapons," especially if they fall into the hands of non-state actors.
Both countries' robotics companies have launched various forms of guided vehicles (Social Media)
On the ground, both countries' robotics companies have launched various forms of guided vehicles, some resembling animals, others resembling boxes, with the most notable being quadruped "robot dogs."
In the United States, companies such as Ghost Robotics and Boston Dynamics have collaborated with the military for base security and reconnaissance. For example, in early 2023, the U.S. Air Force deployed quadruped robots at bases such as Tyndall and Cape Cod for patrols around the base area.
These American robots are equipped with sensors (such as thermal imagers and radar) and non-lethal deterrents such as pepper spray or alarms, but the current U.S. policy prohibits them from carrying lethal weapons. By contrast, Chinese companies are more bold.
In a television military exercise in 2024, Chinese People's Liberation Army soldiers practiced "assault operations" with the help of a robot dog manufactured by a Chinese company called Unitree Technology. The robot dog was equipped with a standard assault rifle and could autonomously enter buildings to suppress targets from a distance.
Videos from Kestrel Defense, a Chinese company, also showed quadruped robots dropped from drones, equipped with machine guns, suicide bombs, or grenade launchers. Analysts note that in order to keep up with China's development, the U.S. military is "frantically arming quadruped robots."
The naval hardware competition looks like a marathon of prototypes and pilot projects (Anadolu Agency)
This competition is not limited to canine robots but extends to a broader range of unmanned ground vehicles. For example, the U.S. Army has tested the "Mule" vehicle, which can serve as an automated equipment carrier and an unmanned tank. Challenges such as DARPA's "Subterranean Challenge" and recent military exercises have demonstrated the ability of U.S. wheeled and tracked robots (such as the wheeled version of the Atlas robot) to penetrate rubble and caves.
China also has similar projects. Major defense companies such as China North Industries Corporation and AVIC are developing tracked ground vehicles for accompanying infantry, throwing smoke grenades, or carrying sensors into hazardous areas, especially in urban environments. They also have prototypes of humanoid robots.
Additionally, China leads in the field of underwater drones, testing unmanned surface vessels and submarines. Chinese media reported on the sea trials of autonomous stealth attack boats and reconnaissance submarines, which are said to be completely guided by artificial intelligence algorithms.
Meanwhile, the U.S. Navy is developing prototype clusters of surface and underwater drones, such as the "Orca" and "Ghost Fleet Overlord" projects.
In general, the hardware competition seems to be a marathon of prototypes and pilot projects. Both armies regularly showcase their robotic teams in military exercises. In China, the "Golden Dragon" exercises of the People's Liberation Army use armed robot dogs and quadcopters equipped with jammers to survey urban environments.
In the United States, news releases and budget requests from each branch of the military emphasize dozens of tests of robot dogs and drones. Within just three years, the U.S. military has expanded the use of robot dogs from limited experiments to "increasingly diverse applications," becoming a "force multiplier."
Amidst this context, cooperation with Silicon Valley and other global tech companies stands out. On the U.S. side, companies such as Shield AI, Raytheon, and Ghost Robotics are collaborating with the U.S. Department of Defense.
Chinese tech giants also have dedicated departments for developing military robots.
In short, the technological gap between the two sides has narrowed. The U.S. continues to develop unique platforms (such as Boeing's fighter escort drones or Boston Dynamics' heavy robots), while China's mass-produced low-cost robots (including drones and ground vehicles) and its vast domestic market are rapidly expanding their deployment.
As one defense analyst warned, the progress made by both sides in intelligent weapon hardware "will determine global stability." The more widespread the proliferation of autonomous weapons, the greater the risk of accidental escalation or uncontrollable spread.
Progress in intelligent weapon equipment has "made this issue a global stability issue" (European Press Agency)
The Third Battlefield: Non-War Models and Applications
In fields far from tanks and aircraft, the competition in scientific advancements in artificial intelligence is evident, especially in the fields of generative artificial intelligence and large language models (LLMs). Chatbots and intelligent services have become symbols of leadership and technological superiority among nations.
In the U.S. camp, well-known companies such as OpenAI's ChatGPT, Google's Gemini, and Anthropic's Claude stand out. In China, local artificial intelligence companies have also launched their own major products, such as DeepSeek, a chatbot launched by a startup based in Hangzhou, Baidu's ErnieBot, Alibaba's Coin, iFlytek's SparkDesk, and SenseNova by SenseTime, among others.
The comparison of these models is not only based on their technical capabilities - such as language understanding, logical reasoning, and multilingual abilities - but also on characteristics influenced by political factors.
In terms of actual performance, Chinese models have made significant leaps. For example, DeepSeek, a startup established in 2024 and headquartered in Zhejiang, released its DeepSeek R1 model, which has billions of parameters and claims to have mathematical and reasoning capabilities comparable to the latest models of OpenAI.
The developers of this model claim that DeepSeek performs 7% to 14% better than ChatGPT and Claude in reasoning tests, and its training cost is only a fraction of its competitors (approximately $60 million, compared to over $1 billion for competitors). Similarly, during the 2024 China Artificial Intelligence Conference, local companies announced that their models are comparable to Western models, and even superior to them.
Baidu announced that its ErnieBot model is equivalent to GPT-4 in English proficiency; Alibaba stated that its CoinMax model scores comparable to GPT-4 Turbo; iFlytek released SparkDesk 4.0, which achieved "significant progress" in text generation, reasoning, and multilingual understanding compared to GPT-4 Turbo. Notably, Baidu and Alibaba often rely on internal performance metrics, prompting Western experts to be cautious when evaluating these claims. However, these claims at least confirm that large Chinese language models are rapidly catching up.
To illustrate its economic impact and threat, technology media reported that the DeepSeek smartphone application immediately topped the U.S. app store upon its release, temporarily weakening investor confidence in chip giant NVIDIA, and triggering a $2 trillion stock market crash.
However, the similarities between the two camps go beyond technical capabilities and extend to their fundamental principles.
U.S. models filter content (such as blocking hate speech, self-harm instructions, etc.), but usually allow open political discussions, provided these discussions comply with their principles. For example, analysts claim that when users ask ChatGPT about a historical event, they receive an informative answer. However, this statement contradicts real-world experience, as when the question involves the Palestinian issue, ChatGPT avoids answering, even distinguishing between the rights of Palestinians and Israelis. Therefore, content control and censorship constitute their common core themes.
The difference lies in their market penetration rates. U.S. models such as ChatGPT, Gemini, and Claude, along with their counterparts, are widely adopted globally, used to support billions of monthly conversations, develop enterprise tools, improve search engine optimization, and assist in writing. In China, the use of local models has experienced explosive growth in the past year. According to official media reports, the download count of Alibaba's "Coin" application doubled within two months, reaching 20 million downloads.
Despite the tense geopolitical situation, DeepSeek has rapidly spread, reflecting global attention. DeepSeek has gained widespread user recognition in China and even in other countries, although some countries such as Australia and Italy have temporarily banned it for security reasons.
Notably, there is a clear paradox: due to regulatory restrictions, U.S. artificial intelligence giants are almost absent from the Chinese consumer market, while Chinese companies are actively promoting their technologies overseas. They support solution providers and establish partnerships in emerging markets. For example, Huawei provides integrated solutions that combine AI tools with its telecommunications network equipment in Africa.
Artificial intelligence is accelerating the exploration of new treatments (Getty Images)
Indeed, the impact of artificial intelligence is not limited to the military and consumer service sectors; it is transforming the scientific and engineering fields of the United States and China. From drug development, material design to physics simulations, researchers in both fields are using machine learning techniques to solve the most complex problems.
For example, in the fields of drug development and biomedicine, artificial intelligence is accelerating the exploration of new therapies. In the United States, dozens of biotech companies are using deep learning techniques to design drug molecules or predict protein structures.
AlphaFold, developed by Google's DeepMind, is the most famous example, especially after its founder won the Nobel Prize in Chemistry for AlphaFold. AlphaFold can predict protein folding with remarkable accuracy and is widely applied in global drug development.
Institutions such as the National Institutes of Health (NIH) and the National Science Foundation (NSF) are funding major artificial intelligence projects in genomic research, personalized medicine, and pandemic prevention - for example, the U.S. Department of Defense's Advanced Research Projects Agency (DARPA) Pandemic Prevention Platform. Los Alamos and Argonne national laboratories are exploring the application of artificial intelligence in biological monitoring and vaccine design.
China has not lagged behind and has made significant progress in this field. Startups such as Yinker Intelligent (based in Hong Kong) and Tencent Labs, along with government enterprises, are collaborating with pharmaceutical giants to apply artificial intelligence technology.
For example, Yinker Intelligent announced in 2024 that its AI drug for treating a rare lung disease has entered Phase II clinical trials simultaneously in China and the United States, making it the first drug fully developed using artificial intelligence worldwide.
The CEO of the company pointed out, "The AI-based approach" significantly shortened the development cycle and "signals a complete transformation of the industry." Research and development in both public and private sectors in China is supporting these breakthroughs. The Ministry of Science and Technology is conducting multiple major projects in AI medical fields (such as smart hospitals and drug target databases).
The National University of Defense Technology, affiliated with the Chinese military, is also conducting medical AI research for field injuries and health monitoring. Overall, analysts point out that the number of clinical trials currently conducted in China has exceeded that in the United States, and its biotechnology sector is beginning to "take the lead" on the global stage. In short, both countries are investing heavily in AI-driven drug development, with China particularly enthusiastic about vaccine design and integrating traditional Chinese medicine into this new model.
AI models play a key role in finding innovative compounds (Northwest University)
In the field of materials engineering, AI models play a key role in finding innovative compounds and optimizing manufacturing processes. The United States launched the "Materials Genome Initiative" in 2011, aiming to accelerate the discovery of new materials using computation and data.
Today, AI methods have become a key pillar of this strategy. National laboratories (such as the materials projects at Lawrence Livermore National Laboratory) are using machine learning techniques to predict the properties of new alloys, polymers, and battery materials.
In academia, research teams at prestigious universities such as MIT and Harvard are using neural networks to design chemical catalysts and simulate crystal growth. China is following closely, with government-funded "Materials Genome" centers that combine supercomputing capabilities with artificial intelligence. For example, Tsinghua University and the Chinese Academy of Sciences are publishing extensive research on machine learning-guided material design.
A recent European analysis noted that "China is leading in AI research, including in materials science." This progress is also reflected in China's industrial sector, with companies such as Huawei and Baidu operating smart factories, and startups like ProbSci in Shanghai using AI to predict material properties. Notably, both countries are utilizing big data projects (such as the U.S. Materials Project Open Database and China's National Materials Database) to power AI models, enhancing their accuracy and effectiveness.
The Chinese Academy of Sciences is applying machine learning technology to fusion research (European News Agency)
In the fields of physics and climate simulation, artificial intelligence is accelerating the process of solving complex mathematical equations. In the United States, major laboratories (such as those of the U.S. Department of Energy, NASA, and NOAA) apply artificial intelligence to climate modeling, astrophysics (such as analyzing space telescope data), and nuclear simulations. The U.S. Department of Energy also funds specialized research partnerships (such as the Climate AI Institute).
Similarly, China is using artificial intelligence in its major scientific projects. The Chinese Academy of Sciences is applying machine learning technology to fusion research - as part of its participation in the International Thermonuclear Experimental Reactor (ITER) project and for analyzing data from large facilities (such as the FAST radio telescope or the Beijing Electron Positron Collider).
For example, in the Sino-U.S. astrophysics project, intelligent algorithms are helping to detect gravitational waves and simulate black hole mergers. In weather forecasting, NOAA and the China Meteorological Administration are integrating AI models to improve forecast accuracy.
The U.S. Army Research Laboratory is also using artificial intelligence to improve supply chain efficiency and maintenance scheduling (Getty Images)
The last key frontier is using artificial intelligence to support military research and development (R&D), not just direct weapon design. Both the U.S. Air Force and the U.S. Defense Advanced Research Projects Agency (DARPA) have initiatives aimed at "accelerating AI innovation," such as using machine learning to design radar systems or using generative algorithms for jet engines.
The U.S. Army Research Laboratory (ARL) is also using artificial intelligence to improve supply chain and maintenance scheduling efficiency. Chinese military R&D institutions are also applying artificial intelligence in their laboratories. The People's Liberation Army's National University of Defense Technology has published blueprints and microchips of warships entirely designed by artificial intelligence. Chinese military think tanks have also published military application research on "AI-enhanced science."
Although both China and the United States are vigorously promoting the development of artificial intelligence and investing heavily, their institutional frameworks are vastly different. In China, scientific research is guided by central strategic planning and generous government funding. The "New Generation Artificial Intelligence Development Plan" (2017) laid the foundation for this strategy, investing billions of yuan in the next decade to develop core artificial intelligence technologies and integrate them into education, computing centers, and national laboratories such as the Beijing Artificial Intelligence Institute. Additionally, China has implemented the "military-civilian integration" strategy to promote military-civilian cooperation.
Artificial intelligence has been included in the priority development areas of the "14th Five-Year Plan" (2021-2025) and the 2030 Science and Technology Innovation Plan. Tech giants and various ministries have actively participated in building professional industrial models and strict regulatory rules, especially in sensitive areas such as medicine and law.
In the United States, government support is decentralized and coordinated through the "National Artificial Intelligence Initiative Act" (2020). The U.S. relies on the leadership of the private sector in Silicon Valley and federal government agencies such as the National Science Foundation (NSF), the National Institutes of Health (NIH), and the Department of Energy (DOE), which have established dozens of specialized institutions with budgets exceeding $1 billion.
The "CHIPS and Science Act" (2022) and the Pentagon budget have also allocated hundreds of billions of dollars, with a new proposal of $32 billion under consideration to strengthen the U.S. advantage over China.
Against this backdrop, the "Star Gate" project is one of the largest investment programs in the history of artificial intelligence. The project has allocated $50 billion to develop advanced computing infrastructure and build large-scale artificial intelligence models. The project is led by OpenAI, supported by SoftBank and Oracle, with participation from tech giants Microsoft, NVIDIA, and Arm, with the goal of keeping the U.S. ahead in the artificial intelligence competition.
Both sides benefit from the openness of the scientific community. A study by the European Commission found that China leads in the proportion of research on AI tools, surpassing the U.S. and EU in quantity, innovation, and qualitative impact.
However, this continued leadership depends on continuous financial investment, infrastructure development, and the establishment of robust regulatory and ethical frameworks to ensure sustainability. Western media highlights risks such as bias, privacy, and existential threats, while Chinese regulatory authorities focus on ensuring social stability and ideological compliance, highlighting the significant gap between the two countries in AI regulation and safety approaches.
The Uncertain Future
The escalating artificial intelligence competition between the U.S. and China has surpassed single areas, touching every aspect of global power and influence. In the military, this competition is beginning to blur the traditional "offensive" and "defensive" boundaries. AI tools will become the main drivers of surveillance and cyberattacks, even becoming the main tools for commanding and influencing the enemy's thoughts, as important as cannons and missiles.
In the hardware domain, we are heading towards a future battlefield filled with autonomous robot forces, drone swarms, and intelligent sensors. This raises profound ethical questions and presents new challenges to global stability.
In the technology domain, this competition means that the next generation of computing technologies - large language models and AI platforms - will be dominated by U.S. and Chinese companies, giving them enormous influence over the content seen and shared by billions of people online.
From a scientific perspective, this competition is expected to bring rapid breakthroughs in important areas such as medicine, energy, and basic research. But it also sparks another arms race: a race for the best talent and access to the most powerful supercomputers.
This competition may accelerate innovation, but it also carries the risk of disrupting the global system. We have already seen that the strategic importance of artificial intelligence is beginning to affect trade wars, the implementation of export restrictions, and the formulation of technical standards.
The risk is that competitive pressure may lead to the deployment of untested AI weapons without consequences, or trigger an "artificial intelligence arms race" similar to the nuclear arms race during the Cold War. For this reason, some experts urge major powers to establish common controls and rules (regarding autonomous weapons, arms control, and data sharing) while competing for influence.
The outcome of this global technology leadership contest is far from settled. The U.S. still holds an advantage in advanced AI hardware design, open research, and tech entrepreneurship. Meanwhile, China has significant advantages in the volume of available data, central government coordination, and the size of its domestic market.
History tells us that major breakthroughs may come from any side (or even from other countries or international laboratories). However, there is no doubt that the artificial intelligence competition between the U.S. and China has now become a key dimension of international security and economic policy. As this competition intensifies, it will not only determine the future of Washington and Beijing, but also shape the rules and standards for the global development of artificial intelligence.
Sources: Al Jazeera
Original: https://www.toutiao.com/article/7535922117934662184/
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