Testing for AI Networking

Spirent AI Data Center Test Solution Scoops Grand Prize at Interop Tokyo 2024

The AI data center journey is just starting and expected to evolve dramatically with the technology. There is an urgent need to evaluate new data center architectures to ensure they are future-proof and optimized for maximum efficiency, to ensure a return on AI network investments. A new Spirent infographic compiles the latest AI data center market trends, architecture details, dynamic AI fabric requirements and new testing strategies and solutions required for ensuring AI Ethernet fabric performance and resiliency.

Artificial intelligence (AI) systems are expected to transform digital industries in ways still being discovered. Gartner estimates spending on AI software will grow to $297.9B with a CAGR of 19.1% by 2027. While Generative AI (GenAI) software spend will rise from 8% of AI software in 2023 to 35% by 2027. Generative AI has moved from the fringes to the forefront, igniting imaginations about its vast potential. Behind this wave of excitement, industries are diligently working to prove use cases, scale solutions to meet demand, and innovate to unlock AI’s full potential.

Innovative testing approaches in preparation for the AI revolution

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.

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.

AI/ML applications are driving new levels of high-speed Ethernet complexity for hyperscale data centers. Why emulation and validation tests are essential for ensuring new technologies perform as expected.

Spirent Moves Testing into the AI Fast Lane with Industry’s First AI Traffic Emulation Platform for Ethernet

In today’s rapidly evolving technological landscape, Enterprise and datacenter networking has undergone significant advancements. With the widespread adoption of AI/ML, edge computing, and high-performance computing (HPC) systems, modern datacenters demand a network that delivers exceptional performance and minimal latency. This network must also seamlessly adapt to accommodate the tremendous surge in data transfer demands driven by data-intensive and compute-intensive applications.