The United States dominates rivals in artificial intelligence development and use, while China is growing rapidly and the European Union is lagging, a research report revealed Monday.
The study by the Information Technology and Innovation Foundation evaluated AI using 30 separate metrics including human talent, research activity, commercial development, and investment in hardware and software.
According to the report based on data found in 2020, China and European Union have 32 and 23.3 points respectively on a 100-point scale, while the United States leads, with an overall score of 44.6 points.
The United States found to be the leader in key areas, such as start-up investment and Research & development funding, according to the researchers.
But China has made enhancements in several areas and last year had more of the world’s 500 most powerful supercomputers than any other nation — 214, compared with 113 for the US and 91 for the EU.
“The Chinese government has made AI a top priority and the results are showing,” said Daniel Castro, director of the think tank’s Center for Data Innovation and lead author of the report.
“The United States and European Union need to pay attention to what China is doing and respond because nations that lead in the development and use of AI will shape its future and significantly improve their economic competitiveness, while those that fall behind risk losing competitiveness in key industries.”
The EU has lagged in the financing of venture capital and private equity while faring better in terms of research papers published.
The researchers reported that in 2018, China released some 24,929 AI research papers, against 20,418 for the European Union and 16,233 for the United States.
But it said that “average US research quality is still higher than that of China and the European Union.”
The survey also concluded that the United States “is still the world leader in designing chips for AI systems.”
To remain competitive, the report said, Europe needs to boost research tax incentives and expand public research institutes working on AI.
It must raise funding for AI research and deployment for the United States to retain its lead and step up efforts to develop AI talent domestically while attracting top talent from around the world.
U.S, China, and European Union top AI funded startups.
Nuro(Country: USA, Total funding: $1 Billion) is specialized in the development of autonomous delivery vehicles. It commercializes an electric self-driving delivery vehicle designed to transport goods such as food, grocery bags, and other cargo.
UiPath(Country: USA, Total funding: $1 Billion) is a software company dedicated to robotic process automation. It provides a platform for the implementation of process automation and deployment to the cloud. One of the global leaders in both process mining and robotic process automation
SenseTime(Country: CHINA, Total funding: $3.3 Billion) is an AI technology company particularly operating in the field of computer vision. It provides several products and services including facial recognition and biometrics, image and video processing, robot sensors, and autonomous driving with applications in financial services, security, smart cities, culture and entertainment, education, and advertising.
Megvii(Country: CHINA, Total funding: $1.4 Billion) is an image recognition and deep-learning technology company particularly focusing on the Internet of Things – IoT. Especially servicing the public sector, it develops authentication software, an open-source computer vision platform, Face++, as well as a range of solutions for Personal IoT, Smart Cities IoT, and supply chain IoT.
Graphcore(Country: UK, Total funding: $460 Million) is a company developing hardware systems to accelerate machine learning applications. Having created a new processor named the Intelligence Processing Unit, Graphcore products allow AI developers and researchers to run machine learning models much faster than previous hardware generations.
BenevolentAI(Country: UK, Total funding: $292 Million) is a technology company focusing on accelerating the journey from data to medicines. It uses a computational and experimental technology platform for R&D programs to lower drug development costs, decrease failure rates, and increase the speed at which medicines are generated.