AI Networks: A Troubling Shift 🤖🤯
Tech
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Telecom networks are undergoing a shift, as operators pilot systems leveraging artificial intelligence. This week, Nokia and AWS demonstrated a new network slicing system. The setup is being tested by telecom operators du in the United Arab Emirates and Orange in Europe and Africa. These experiments utilize AI agents to monitor network conditions and dynamically adjust resources. Network slicing allows operators to create multiple virtual networks, each tailored for specific needs like emergency services or high-bandwidth applications. The tests highlight the increasing involvement of cloud platforms in managing telecom operations, suggesting AI is beginning to function as an operational controller, adjusting physical and virtual resources in response to live events.
AI-DRIVEN NETWORK SLICING: A NEW ERA OF CONNECTIVITY
Network slicing, a key element of the 5G standard, is undergoing a significant transformation with the integration of AI agents. This approach enables operators to create multiple virtual networks tailored to specific needs, such as emergency services or high-bandwidth consumer traffic. Traditionally, network slicing required manual planning and fixed configurations, limiting responsiveness to dynamic demand. The new system, being piloted by operators like du and Orange, leverages AI to monitor network performance and automatically adjust resources, promising a more agile and efficient network management approach.
THE NOKIA-AWS COLLABORATION: A SYMPHONY OF AI AND NETWORKING
The innovative network slicing system is the result of a strategic partnership between Nokia and AWS. Nokia’s slicing and automation tools are combined with AI models delivered through Amazon Bedrock, AWS’s managed AI service platform. This “agentic AI” approach empowers AI agents to track network performance indicators like latency and congestion, considering factors like event schedules and weather conditions. The collaboration represents a crucial step in automating network management, shifting towards a more dynamic and responsive infrastructure.
OPERATOR CHALLENGES AND THE CASE FOR NETWORK SLICING
Telecom operators have faced a long-standing challenge: despite the technical advancements of 5G – including higher speeds and lower latency – translating these gains into new revenue streams has proven difficult. Network slicing is viewed as a potential solution, offering opportunities to generate enterprise income by providing tailored connectivity services. However, the operational complexity and uncertainty surrounding demand have hindered widespread adoption. Operators are striving to align their networks with the expectations of enterprise customers, who increasingly desire connectivity that behaves like cloud computing – offering on-demand scaling and predictable performance.
CLOUD INTEGRATION AND THE EVOLUTION OF TELCO INFRASTRUCTURE
The testing phase of the Nokia-AWS system highlights the growing involvement of cloud providers in telecom operations. Operators are increasingly migrating parts of their core networks onto public cloud platforms and building cloud-based control systems. This trend is fueled by the need to modernize networks and adopt software-driven infrastructure. The integration of AI-driven control loops on top of cloud platforms represents the next logical step, enabling rapid adjustments and optimizing network performance in real-time.
REGULATORY CONSIDERATIONS AND THE FUTURE OF AI-CONTROLLED NETWORKS
The deployment of AI-controlled networks raises important questions for regulators and operators alike. Concerns surrounding reliability, accountability, and potential operational risks necessitate careful oversight. Operators are adopting a gradual approach to automation, maintaining human oversight while rigorously validating system behavior under real-world conditions. Ultimately, the successful integration of AI into network management will depend on establishing clear regulatory frameworks and ensuring that operators prioritize safety and performance.
This article is AI-synthesized from public sources and may not reflect original reporting.