Chairman of China Mobile Breakthrough in key technologies of 6G, forming global unified standards

China Mobile Chairman achieves breakthrough in 6G technologies, establishes global unified standards

【PhoneAuto News】On June 28th, PhoneAuto learned that the 2023 MWC Shanghai has opened. At the conference, Yang Jie, Chairman of China Mobile, delivered a keynote speech. He stated that the technological innovation in the global information and communication industry has gone through three stages: source innovation, iterative innovation, and integrated innovation. He proposed three initiatives: promote the deep expansion of 5G applications; promote the evolution and upgrading of technology to form a globally unified 6G standard; promote the interoperability and sharing of capabilities.

Yang Jie, Chairman of China Mobile

Yang Jie mentioned that at present, we should seize the new opportunities for industrial development with integrated innovation. While developing 5G, we also need to promote the simultaneous development and research of 6G, focusing on key areas such as next-generation communication technology approaching the “Shannon Limit”, breaking through key technologies such as new network architecture, sensory calculation integration, and intelligent endogenous.

In addition, Yang Jie also stated that in recent years, the development of new generation information technologies such as 5G, cloud computing, big data, and artificial intelligence has presented an organic integration and systematic innovation development trend, and has accelerated integration into various fields of economy, society, and people’s livelihood, giving rise to new formats and models such as autonomous driving and metaverse, and setting off a new wave of technological innovation. The recent widespread rise of AIGC may trigger a new wave of technological revolution, and this is just the beginning.

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AIGC, collectively referred to as Generative Artificial Intelligence, is an important symbol of the transition from the AI 1.0 era to the AI 2.0 era. It is based on generative adversarial networks and large-scale pre-training models, and uses learning and recognition of existing data to generate relevant content with appropriate generalization ability. The core idea of AIGC technology is that through training models and learning from a large amount of data, it can generate content related to the input conditions. For example, by inputting keywords, AIGC can generate matching articles, images, audios, etc.

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