AI Proving Ground Podcast · 2025-12-16 · 42 min
AI at scale isn’t about more GPUs - it’s about building a system that can keep evolving. In this episode of the AI Proving Ground Podcast , John Gentry of NVIDIA and Derek Elbert of World Wide Technology explain why AI factories are becoming the backbone of enterprise AI - and why isolated GPU clusters can’t keep up. They break down the factory model for production-grade artificial intelligence: data and power in, intelligence out. But making it work now requires more than compute - enterprises must unify networking, storage, orchestration, security, and multi-tenant management into a single, flexible system that serves the entire business. At the center is data. What was once an asset is now the bottleneck. As platforms and GPUs evolve every year, enterprises need industrial-grade data pipelines and architectures built for portability - not lock-in. The episode looks ahead to distributed inference and agentic AI, where models run at the edge while core factories continuously generate new intelligence. The mandate is clear: design for scale, flexibility, and constant change - or fall behind. Good AI starts with good data. Now it has to be put to work.
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