Eye On A.I. #314 Nick Pandher: How Inference-First Infrastructure Is Powering the Next Wave of AI
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Jan 17, 2026 In this engaging discussion, Nick Pandher, VP of Product at Cirrascale and former leader at NVIDIA and AMD, delves into the shift from AI model training to inference. He highlights the pivotal role of inference-first infrastructure and the rise of neoclouds as tailored solutions for businesses. Nick contrasts hyperscalers with neoclouds regarding performance and cost-efficiency. He also shares insights on the importance of security, private deployments, and the critical metrics for successful AI implementations, making this a must-listen for anyone interested in AI deployment.
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Inference Surpassed Training As The Priority
- Inference has become the dominant enterprise AI problem as organizations deploy existing foundational models into workflows.
- Firms prefer fine-tuning or RAG over costly retraining to adapt models to specific use cases.
Neoclouds Solve Predictable Inference Needs
- Enterprises move inference off hyperscalers when cost, performance predictability, and data control matter.
- Neoclouds can deliver consistent low time-to-first-token and better 24/7 performance for steady workloads.
Match Accelerators To Workloads
- Cirrascale stays accelerator-agnostic and pilots models across GPUs and new inference-first chips to find the best fit.
- Different accelerators suit different models, workloads, and power profiles.