AI and machine learning have been important tools in telecom networks for many years, especially in network testing, measurement, monitoring, and assurance. These tools are essential for characterizing and validating networks, detecting faults, and analyzing root causes. With the advancements in generative AI and increased computing power, there is a renewed interest in utilizing AI in the telecom network.
Keysight Technologies, a key player in the industry, has been integrating AI across its portfolio and supporting initiatives like the use of AI in open Radio Access Networks. In a recent interview with Joel Conover, senior director at Keysight, he shared insights on the impact of AI in network testing and assurance.
Conover highlighted that AI applications are driving new requirements in network equipment and architectures due to significant investments in AI data centers. Keysight has been working closely with customers to develop new emulators and measurement techniques for AI data center workloads to optimize system performance.
When asked about generative AI in network testing, Conover emphasized the importance of enabling customers to build, train, and operate AI models efficiently. Keysight is focused on developing new models to emulate AI workloads and deliver them at a scale never seen before, addressing challenges like bandwidth constraints and system complexity.
In terms of risks and challenges, Conover mentioned that integrating AI into communications technology shows promise in predicting channel conditions and improving network performance. However, developing tools to simulate and tune AI models early in the research and development cycle is crucial for advancing technologies like 5G and beyond.
Regarding the use of AI in test tools and validation, Keysight sees opportunities to incorporate AI in its solutions to enhance design, emulation, and testing processes. Machine learning algorithms are already being used in design suites to optimize circuitry, while AI-driven analytics help identify anomalies in network data for better troubleshooting.
In conclusion, Keysight recognizes the potential of AI in driving efficiency and insight across various applications. By leveraging AI in product development and customer support, Keysight aims to deliver faster, more relevant results and enhance user experience. As the industry continues to evolve, the integration of AI in network testing and assurance will play a crucial role in shaping the future of telecom networks.
