In this episode, we welcome Lead Principal Technologist Hari Kannan to cut through the noise and tackle some of the biggest myths surrounding AI data management and the revolutionary FlashBlade//EXA platform. With GPU shipments now outstripping CPUs, the foundation of modern AI is shifting, and legacy storage architectures are struggling to keep up. Hari dives into the implications of this massive GPU consumption, setting the stage for why a new approach is desperately needed for companies driving serious AI initiatives.

Hari dismantles three critical myths that hold IT leaders back. First, he discusses how traditional storage is ill-equipped for modern AI's millions of small, concurrent files, where metadata performance is the true bottleneck—a problem FlashBlade//EXA solves with its metadata-data separation and single namespace. Second, he addresses the outdated notion that high-performance AI is file-only, highlighting FlashBlade//EXA's unified, uncompromising delivery of both file and object storage at exabyte scale and peak efficiency. Finally, Hari explains that GPUs are only as good as the data they consume, countering the belief that only raw horsepower matters. FlashBlade//EXA addresses this by delivering reliable, scalable throughput, efficient DirectFlash Modules up to 300 TB, and the metadata performance required to keep expensive GPUs fully utilized and models training faster.

Join us as we explore the blind spots in current AI data strategies during our "Hot Takes" segment and recount a favorite FlashBlade success story. Hari closes with a compelling summary of how Pure Storage's complete portfolio is perfectly suited to provide the complementary data management essential for scaling AI. Tune in to discover why FlashBlade//EXA is the non-compromise, exabyte-scale solution built to keep your AI infrastructure running at its full potential.

For more information, visit: https://www.pure.ai/flashblade-exa.html

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00:00 Intro and Welcome

04:30 Primer on FlashBlade

11:32 Stat of the Episode on GPU Shipments

13:25 What is FlashBlade//EXA

18:58 Myth #1: Traditional Storage Challenges for AI Data

22:01 Myth #2: AI Workloads are not just File-based

26:42: Myth #3: AI Needs more than just GPUs

31:35 Hot Takes Segment