AI doesn't just chew up compute—it eats your network for breakfast. In this episode of Pop Goes the Stack, #F5's Lori MacVittie, Joel Moses, and Ken Arora dig into the pressing issues surrounding #AI workloads and networking. Everyone's worried about GPUs and cooling, but nobody’s talking about the lateral east-west traffic explosion, the rise of inter-agent comms, or the operational strain on DCN fabric and interconnects. Our experts discuss the importance of upgrading data center networks to accommodate AI demands, examining the differences between training and inferencing workloads. The conversation also covers the necessity of high-performance networking, the relevance of latency, data gravity, and the potential expansion of data centers. Tune in to get valuable insights into the challenges and solutions shaping the future of AI-driven applications. Chapters: 00:00 Welcome to Pop Goes the Stack 00:17 AI's GPU scramble and network stress-test 00:43 Debate: Is it really the network? 01:19 AI networking: Training vs. inferencing 02:50 Latency and bandwidth in AI workloads 05:21 Data gravity and edge AI 11:30 Security and reliability in AI networking 15:04 East-west networking 19:59 Key takeaways Learn how you can stay ahead of the curve and keep your stack whole with additional insights on #AppSecurity, multicloud, AI, and emerging tech: https://go.f5.net/tawxbjad More about F5: https://go.f5.net/c0627jg6 Read our blog: https://go.f5.net/ph4rfmgx Follow us on LinkedIn: https://go.f5.net/eetd3jep

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