AIネットワークのテスト

AI is no longer a distant promise for telecom—it’s reshaping the network from the ground up. In this insightful on-demand webinar, Spirent and leading industry experts explore how telecom operators are evolving from AI-enhanced networks to infrastructure that’s purpose is built for AI. The discussion focuses on real-world challenges and strategies for supporting AI at scale, highlighting why traditional networks aren’t enough to meet the demands of tomorrow’s intelligent services. One of the key takeaways is the recognition that AI traffic isn’t business as usual. With unpredictable throughput patterns, bursty inference spikes, high concurrency levels, and strict latency requirements, AI workloads are forcing a fundamental shift in network design. Telecom operators must rethink their role—not just as connectivity providers but as enablers of AI ecosystems. That means becoming providers of AI-ready infrastructure and delivering services like AI networking-as-a-service and infrastructure-as-a-service.

AI is transforming telecom infrastructure in ways that are both exciting and demanding. With artificial intelligence now embedded in everything from core networks to radio equipment, and AI workloads driving massive new traffic patterns, the telecom industry must rapidly adapt. But how do you assure performance, trust, and security in networks that are evolving this fast? This RCR Wireless webinar takes a high-level look at how telcos are rethinking testing and assurance for the age of AI. From validating AI-driven network functions to preparing infrastructure for AI-generated traffic, the landscape is shifting—and the tools and strategies must shift with it.

This session is dedicated to exploring the transformative impact of cutting-edge technologies on service assurance strategies within the telecommunications sector. As we delve into this topic, we will uncover how advancements in 5G infrastructure, cloud computing at the network edge, and artificial intelligence (AI) are reshaping the landscape of network operations and service delivery. The massive investments in 5G infrastructure, particularly on the RAN (Radio Access Network) side, have set the stage for an unprecedented increase in network capabilities. This expansion isn't just about speed and connectivity; it's about fundamentally changing how networks operate and how services are delivered. With carriers expanding mid-band spectrum rollouts and enhancing performance, the implications for service assurance are profound.

人工知能と機械学習は、ネットワーク・テストの多くの側面、すなわちフィールドからサービス保証まで、自動化と効率性の向上に役立っています。では、現在、ネットワーク・テストと保証の分野でAI/MLは具体的にどのように適用されているのでしょうか。また、その価値はどのように証明されているのでしょうか。そして、これはフィールド・ワーカーや通信事業者の運用にどのような意味を持つのでしょうか。 この*RCR Wireless News*のウェビナーでは、Spirentと業界の専門家が、将来的にAI主導のインテリジェントで自動化されたネットワークの実現に向けた進捗状況について最新情報を共有し、AIがネットワークのテストと保証の状況をどのように変えつつあるかについて視聴者に洞察を提供します。

Artificial intelligence (AI) is revolutionizing the telecommunications industry. This engaging webinar explores AI's transformative potential and its future impact on telecom operations. We’ll share our predictions on how AI will drive new efficiencies in capital spending and in delighting customers with new experiences and services and creating new revenue streams. AI and machine learning are transitioning from tactical solutions to strategic tools in telecom, promising to unlock immense value, particularly in networking. This shift is essential for driving efficiencies in capital spending, optimizing network designs, and enhancing customer experiences with new services and revenue streams.

This panel discussion delves into the critical role of testing and verification in the telecom industry, particularly as it incorporates AI and machine learning. Key areas of focus include the challenges and opportunities that come with implementing AI technologies, such as data handling, cost management, people and culture, and security. Telecom operators are increasingly integrating AI to enhance various operational aspects. However, this journey involves significant hurdles. Panelists will explore the specific challenges, including handling vast amounts of data generated by networks, the costs associated with AI implementations, and the cultural shift required to embrace new technologies.