Matilda Bailey is a Networking specialist who focuses on the latest technologies and trends in cellular, wireless and next-gen solutions.
Can you explain how symbiosis between 5G-A and AI technologies can stimulate double-digit growth in both DOU and ARPU? What specific advancements in AI and 5G-A do you think will drive this growth? How will this growth impact the average mobile subscriber?
The integration of 5G-A and AI technologies is anticipated to drive double-digit growth in both data of usage and average revenue per user by creating a more efficient, responsive, and personalized network experience. Key advancements include AI-enhanced network management, machine learning for predictive maintenance, and edge computing that brings processing power closer to the user. These innovations will enable faster data speeds, lower latency, and more reliable connections, ultimately enriching the mobile experience for subscribers and encouraging greater data consumption, which in turn fosters revenue growth.
You mentioned that we are rapidly entering a fully intelligent world. How is this intelligence placing new demands on networks? What kind of network upgrades are required to meet these new demands? Can you give examples of intelligent applications that are demanding these new network capabilities?
As AI applications become more prevalent, they demand increasingly sophisticated network capabilities. This drives the necessity for upgrades such as transitioning from 5G NSA to 5G SA, adopting Control and User Plane Separation (CUPS), and ensuring Guaranteed Bit Rate (GBR). Intelligent applications like AI-powered health monitoring, autonomous vehicles, and smart city infrastructures require low latency, high reliability, and vast network coverage to function effectively.
How is AI changing human-machine interaction? What are the latest advancements in HMI? Can you provide an example of how AI-powered voice assistants are making interactions more natural?
AI is revolutionizing human-machine interaction by enabling more natural and intuitive communication methods beyond text, including voice, gestures, and even expressions. Recent advancements in HMI include multi-modal interfaces and real-time processing capabilities. For example, AI-powered voice assistants can understand and respond to natural language with high accuracy, offering personalized assistance and seamless user experiences that are more interactive and engaging.
Why is guaranteed latency so crucial for supporting these new AI applications? What network transitions will carriers need to make to provide guaranteed latency? How can technologies like CUPS and GBR help in achieving lower latency?
Guaranteed latency is vital because many new AI applications, such as real-time gaming, remote surgery, and autonomous driving, require immediate response times. To provide this, carriers need to advance from 5G NSA to 5G SA and implement technologies like CUPS, which separates the control plane and user plane to reduce latency, and GBR, which ensures consistent data rates for critical applications. These transitions will support the high-speed, low-latency requirements of next-gen AI applications.
How will AI transform content production and distribution? What role do you see for AIGC technology in content production? How will AI-powered recommendations impact content distribution?
AI will revolutionize content production and distribution by automating and optimizing these processes. AIGC (AI-Generated Content) technology can create high-quality, complex content such as 2D and 3D videos quickly and efficiently. AI-powered recommendations will make content distribution more targeted and personalized, enhancing user engagement and satisfaction. This increased efficiency and personalization will significantly boost the volume of content being produced and consumed, driving up network traffic.
What kind of network improvements will be necessary to handle the surge in network traffic due to AI-driven content production and distribution? What specific upgrades in spectrum, network capacity, and bandwidth will carriers need to implement?
To manage the anticipated surge in network traffic, carriers will need to expand their spectrum allocations, enhance network capacity, and increase both uplink and downlink bandwidth. This will involve investments in more advanced antennas, higher spectrum bands, and improved infrastructure to support the higher data volumes and speeds required by AI-driven content production and distribution.
In your keynote, you discussed the need for experience-centric network coverage. What does this mean exactly? How will this differ between urban areas and rural regions? What role will cloud phones and cloud drives play in this?
Experience-centric network coverage focuses on ensuring that users receive a consistent and high-quality network experience tailored to their environment and needs. In urban areas, this may involve denser network infrastructures to manage high user concentrations, whereas in rural regions, it may require expanded coverage to reach remote users. Cloud phones and cloud drives will play a crucial role by enabling users to remotely access powerful computing resources, thereby enhancing the overall digital experience regardless of location.
How will intelligent in-vehicle applications affect network coverage requirements? What are the challenges in providing continuous and reliable network coverage in cities, highways, and the countryside?
Intelligent in-vehicle applications will demand continuous and reliable network coverage to function effectively, particularly for applications involving navigation, safety, and entertainment. The challenges include ensuring seamless handover between different network cells, managing connectivity across various terrains, and maintaining signal strength in highly dynamic environments such as highways. Carriers will need to invest in extensive infrastructure and optimization techniques to meet these requirements.
With the growing complexity of networks, how can carriers transition towards application-oriented O&M? Can you explain how AI agents can aid in operations enablement and network maintenance? What are digital twins, and how do they contribute to predictive maintenance?
As networks become more complex, transitioning to application-oriented O&M is crucial. AI agents can enhance operations enablement and network maintenance by using advanced algorithms to predict user needs, diagnose issues, and optimize network performance in real-time. Digital twins—virtual replicas of physical network elements—allow carriers to simulate and analyze network behavior, identify potential faults, and conduct predictive maintenance, thus improving efficiency and reducing downtime.
How are carriers already monetizing experience as opposed to just traffic? Can you give examples of custom services launched for specific customer segments like business travelers or live streamers? How are carriers expanding into the B2B2C market?
Carriers are moving beyond monetizing traffic to focusing on user experience by offering custom services tailored to specific customer needs. Examples include premium data plans with guaranteed speeds for business travelers, or specialized streaming packages for live streamers. In the B2B2C market, carriers are partnering with various industries to provide integrated services, such as AI-driven customer support solutions in collaboration with insurance companies, thereby creating new revenue streams and enhancing customer satisfaction.
You mentioned that Chinese carriers are working with multiple industries to provide AI New Calling services. How successful has this initiative been? What kind of growth in income have they experienced from these services?
The initiative to provide AI New Calling services has been highly successful for Chinese carriers, who have seen significant income growth from industry collaborations. By offering customized AI-based communication solutions through Open APIs, these carriers have increased their revenue from industry customers by tenfold. This success underscores the vast potential of integrating AI with traditional telecom services to meet specific business needs and drive new sources of revenue.
