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  Can anyone help me here? What is the real difference of Ericsson's RedCap on 5G standalone architecture ( in terms of features) in comparison with usual RedCap ? RedCap can be implemented on any network that supports dynamic spectrum sharing (DSS). DSS allows operators to share spectrum between 4G and 5G networks, which can be used to reduce the capacity of a network. In addition, RedCap can also be implemented on networks that do not support DSS. This can be done by using a technique called network slicing. Network slicing allows operators to create virtual networks within a physical network, which can be used to isolate different types of traffic. Overall, RedCap is a versatile technique that can be used to reduce the capacity of any network, regardless of its technology. Whether or not a 5G SA platform is needed will depend on the specific requirements of the network operator. Follow us on  Global 5G Evolution  and  Kaneshwaran Govindasa my click comment box for latest 5G pres

China Mobile released its 2023 Interim Results on August 10, 2023. The company reported strong financial performance, with  #revenue  &  #profit  increasing by 6.8% & 8.4% year-on-year, respectively. The company's strong financial performance was driven by the continued growth of its 5G business. As of June 30, 2023, China Mobile had 722 million 5G package customers, up 108 million from the end of 2022. China Mobile expects its  #5G  business to continue to grow rapidly in the coming years. The company also plans to invest heavily in cloud computing, artificial intelligence, & other new technologies. I would like to highlight on China Mobile's Digital Content segment. Migu Video is a mobile video streaming app developed by China Mobile. It offers a wide variety of content, including movies, TV shows, variety shows, cartoons. The app is available in both China & overseas markets. According to  QuestMobile , Migu Video ranked 6th in terms of monthly active users (

LATEST BLOG:  #Qualcomm  on-device AI processing offers must-have benefits for privacy, performance, personalization, cost, and energy. 📚 Privacy: On-device  #ai   #processing  keeps  #data  on the  #device  itself, which helps to protect user privacy. This is in contrast to cloud-based AI processing, which requires data to be transmitted to the cloud. 📚 Performance: On-device AI processing can provide better performance than cloud-based AI processing, as the model does not have to be transmitted over the network. This can be especially important for applications that require real-time processing, such as  #objectdetection  and  #speechrecognition  recognition. 📚 Personalization: On-device AI processing can be used to  #personalizedexperiences  for users. For example, it can be used to generate recommendations, create  #personalizedcontent  , or adapt the user interface to the user's preferences. 📚 Cost: On-device AI processing can help to  #reduce   #costs  , as it does not re