AI Proving Ground Podcast: Exploring Artificial Intelligence & Enterprise AI with World Wide Technology

The Network Is Becoming the Real Unit of AI Performance

Feb 12, 2026

Guest

Taylor Allison

Taylor Allison, NVIDIA Ethernet switch product marketer who bridges hardware and AI networking; David Jansen, Cisco strategist for cloud, SDN and large-scale AI infrastructure; Justin van Shaik, WWT technical architect for high-performance AI fabrics. They discuss why networking is the AI force multiplier. They contrast training vs inference network needs. They map common bottlenecks and security shifts for AI workloads.

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INSIGHT

Network Is The Strategic Constraint

The network has shifted from utility to strategic constraint in AI systems.
Thousands of GPUs only become transformative when they can communicate and synchronize without friction.

INSIGHT

Network As The Force Multiplier

The network acts as a force multiplier enabling thousands of GPUs to behave like a single system.
Performance, time-to-value, and system unity depend more on connectivity than on individual GPUs alone.

INSIGHT

Tail Latency Dictates AI Progress

Both training and inference are highly network dependent and sensitive to worst-case latency.
Training waits on the slowest GPU to share results, so tail latency can stall the entire pipeline.

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As AI systems grow larger and more distributed, enterprises are discovering that performance, security and time-to-value depend less on individual components and more on how well the system moves, synchronizes and protects data at scale. In this episode of the AI Proving Ground Podcast, WWT's Justin van Schaik, Cisco's Dave Jansen and NVIDIA's Taylor Allison talk about how a well-designed network fabric extends time to value, increases risk and quietly erodes the economics of AI initiatives.

More about this week's guests:

Justin van Shaik is a Technical Solutions Architect at World Wide Technology, specializing in High Performance Networking, AI and Open Networking. A seasoned technologist, he helps organizations design and deploy advanced infrastructure to support next-gen workloads at scale.

David Jansen is focused on technology strategy for Cisco's Global Solutions Engineering team across all segments, verticals, and technologies via an ongoing series of innovation initiatives. David spends a lot of time with strategic customers + partners engagements globally. With over 30 years of experience in the IT industry, David is an industry expert in Cloud, Software Defined Networking (SDN), virtualization, orchestration, large scale WAN backbone, and AI Infrastructure.

Taylor Allison is responsible for product marketing related to the NVIDIA Ethernet switch portfolio, including the hardware platforms as well as network operating systems and telemetry tools. Taylor has a passion for product marketing and management in the data center infrastructure space, with expertise in networking, storage, HPC, and AI/ML. Prior to joining NVIDIA in 2021, Taylor was Lenovo's HPC/AI storage leader, responsible for high performance storage platforms, software, and solutions. Taylor earned his MS in Mathematics from the University of North Carolina.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.