IT Press Tour 70: DDN
StorageNewsletter, Wednesday, October 14th, 2026
DDN pitches the economics of AI storage, listing eight ways data platforms waste GPU time in training and inference.
At the 70th IT Press Tour, DDN focused on AI economics rather than raw performance, under the tagline 'We don't make GPUs faster. We make them work, profitably.'
Citing Gartner, it noted AI-optimized IaaS spending of $42 billion in 2026, with inference overtaking training at 55%.
DDN lists eight ways storage erodes GPU economics: GPUs waiting on data, checkpoint stalls, noisy neighbors and costly expansion in training, and prefill delays, agentic loops recomputing context, scaling slowdowns and weak tenant isolation in inference.
Its answer is two data engines, EXAScaler and Infinia, under one namespace and closely tied to NVIDIA platforms.