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At the 2025 China Mobile Cloud Intelligence Computing Conference, Yang Jie, Chairman of China Mobile Communications Corporation, revealed that by 2030, artificial intelligence (AI) tasks are projected to account for 60% of total network traffic. This indicates an increasing reliance on AI technologies in future networks, demanding more advanced compute network infrastructure. Yang Jie pointed out that the "rebound effect" of computing power is gradually emerging, with inference computing power expected to grow four times faster than training computing power by 2030. This shift will drive new demands for computing power services.

News is spreading in the AI field that Jie Junyuan, a former AI expert from ByteDance, has officially joined Chixun Intelligent, an embodied AI startup, as the head of its embodied intelligence department. This change not only injects strong momentum into Chixun Intelligent's technical team but also paves the way for the future development of embodied AI. Jie Junyuan is a highly respected figure in the field of artificial intelligence. He graduated from the University of Science and Technology of China and received his doctorate from the University of Washington. He has published papers at several top academic conferences, and these papers...

Chinese Go champion Ke Jie made his debut on Douyin, challenging artificial intelligence and ultimately achieving victory in 'Clash of the Golden Shovel.' Ke Jie humorously compared Go to 'Clash of the Golden Shovel,' sparking interaction among netizens. The livestream garnered 3 million likes, with peak online viewers exceeding 50,000, ranking 3rd in the Douyin gaming livestream charts. The development of artificial intelligence technology has made 'Ke Jie vs AI' a hot topic of entertainment. Ke Jie stated that by competing against machines, human players can learn more and improve their skills.

The CogVLM-17B, developed through a collaboration between Tsinghua University and Zhipu AI, is a domestic multimodal model with outstanding performance. CogVLM-17B can not only recognize objects in images but also distinguish between fully visible and partially visible objects. The model employs a unique deep fusion method, achieving deep alignment of image features and text features through four key components. CogVLM-17B outperforms Google's models in various fields and is aptly referred to as the '14-sided warrior', showcasing its multimodal capabilities.