Jeff Clarke and Rob Bruckner join Patrick Moorhead and Daniel Newman to discuss Dell’s commercial PC strategy, the role of engineering excellence in the Dell Pro lineup, and how AI-enabled devices are reshaping enterprise computing.

Roman Chernin joins Patrick Moorhead and Daniel Newman to discuss how AI infrastructure is shifting from training to inference, why Nebius built Token Factory to optimize system-level performance, and how agent-driven ROI will define AI success in 2026 and beyond.

Tom Cosenza joins Daniel Newman and Greg Lotko to discuss how quantum computing is reshaping enterprise security strategy, the risks of delaying post-quantum preparation, and why building a cryptographic inventory is the first critical step toward resilience.

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AI is accelerating breakthroughs in fusion energy and materials science, but infrastructure remains the limiting factor. Lenovo and Quantum Formatics explore how private AI environments and purpose-built systems are enabling the next wave of discovery.

AI is becoming a scale and control business. On Episode 297 of The Six Five Pod, Patrick Moorhead and Daniel Newman examine the companies building the infrastructure, forming the alliances, and making the moves that will define who wins and who gets squeezed out. Control is shifting across compute, models, infrastructure, and enterprise distribution as NVIDIA, Microsoft, OpenAI, Meta, and others push to control the next phase of the AI market.

AI is moving fast, but most organizations are not ready for what it takes to deploy it at scale. HPE’s Trish Damkroger explains why infrastructure, not models, is now the limiting factor and how the “AI factory” is redefining enterprise execution.

As AI moves from design to deployment, infrastructure constraints are becoming the primary bottleneck. Lenovo and IREN explore how gigafactory-scale systems, vertical integration, and time-to-first-token metrics are redefining AI at scale.

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As AI moves into production, enterprises must solve for distributed execution across core and edge environments. This conversation explores how infrastructure is evolving to support scalable, real-time AI inferencing.

As AI workloads scale, memory is emerging as the defining constraint on performance. This conversation explores how innovations in HBM and system integration are reshaping the future of AI infrastructure.