Multi-Terabyte GPUs the Only Answer for AI Scaling

Are multi-terabyte GPUs and massive frontier models really the answer to enterprise AI, or are we hitting a hard wall of soaring memory costs and power constraints? In this episode of the Tech Field Day Podcast, host Alastair Cooke sits down with technical experts Ron Pagani Jr., Andy Banta, and Brian Martin to examine whether brute-force hardware scaling remains sustainable. The panel debates scale-up vs. scale-out architectures, emphasizing how smart software optimizations—such as persistent KV caching (MinIO MemKV, Solidigm) and intelligent data layers (CTERA)—can eliminate redundant GPU computation and lower costs. They also explore agentic microservices, power and cooling bottlenecks, and why right-sizing AI models for production is critical for achieving real-world enterprise ROI.