Trust in AI deep dive:Connected
If the use of AI is confined to specific departments or business processes, its true potential cannot be fully realized. True transformation is born from the integration of data and AI—that is, connectivity—that transcends organizational and industry boundaries.
Featured Content: A Journey Through History—Learning from the Past
Events that marked turning points in history raise questions that still resonate with today’s business leaders: the heliocentric theory, the Renaissance, the Titanic, the Silk Road, and the Age of Discovery. This series uses stories from the past as clues to understand the meaning of “trust” in the age of AI.
“AI-RAN” using AI to intelligently manage communication networks
Technology introduction
AI-RAN is a communication network technology that uses AI to optimize the operation of AI services running across radio access networks, edge environments, and cloud infrastructure. The network continuously understands the latency, bandwidth, reliability, and computing requirements of AI applications such as video analytics, robotic control, and remote monitoring. Based on these requirements, it dynamically optimizes radio resources, communication routes, network slices, and edge computing resources. As a result, the network evolves beyond a platform that simply transports data. It becomes an intelligent infrastructure that autonomously adapts to the status and requirements of AI services, enabling more responsive and efficient operations.
Why it matters
This technology enables enterprises and communication service providers to secure the communication quality and computing resources required by AI services in real time. By continuously monitoring traffic conditions, radio quality, device mobility, and AI processing workloads, AI-RAN can anticipate potential service impacts and dynamically control network resources to minimize communication instability and processing delays. This allows organizations in industries such as manufacturing, logistics, infrastructure, and public services to achieve low-latency, highly reliable AI-driven control, stable remote monitoring, autonomous operations, and greater operational efficiency. In this way, the network becomes more than a connectivity service—it becomes a foundational platform for delivering AI-powered services in the AI era.
Example use case
Real-time processing and control of operational data
In smart factories, large numbers of robots, autonomous guided vehicles (AGVs), cameras, and sensors work together while AI applications for video analytics, quality inspection, and robotic control operate across devices, edge environments, and cloud infrastructure. At the same time, wireless network conditions constantly change due to the movement of people and equipment, physical obstructions, and fluctuations in traffic demand, making it challenging to maintain low-latency and highly reliable control. AI-RAN continuously monitors both AI service performance and network conditions in real time. By predicting communication and computing resource requirements, it dynamically optimizes radio resources, communication paths, network slices, and edge processing locations. As a result, autonomous operations can continue safely and efficiently even as conditions on the factory floor change.
“APN (All Photonics Network),” the next-generation network supporting high-capacity communications in the AI era
Technology introduction
APN (All Photonic Network) is a network technology that aims to provide high-speed, high-capacity, low-latency, and energy-efficient communications by connecting devices to the network using an all-optical architecture. As data volumes increase and AI processing becomes more sophisticated, networks are required to deliver higher performance than ever before, and APN is positioned as the foundation supporting this evolution. In applications that handle large volumes of data—such as video, audio, and sensor data—in real time, the quality of communication itself determines the value of the service.
