Promo AI projects fail at scale not because models don't work or GPUs lack performance. They fail because data can't keep pace.

Foundation models work. GPUs deliver. But somewhere between raw data and inference, enterprises hit a wall. GPUs sit underutilized because training pipelines can't move data fast enough. Real-time inference stalls waiting for distributed data to arrive. And when teams try to scale beyond a handful of use cases, data becomes the constraint that breaks everything.

The conversation that needs to happen

During GTC week, NVIDIA, Hammerspace, and The Register are hosting an off-the-record executive roundtable with senior infrastructure leaders actually operating AI at scale. This is peer-to-peer dialogue designed to surface what's actually breaking when scaling AI across hybrid and multi-cloud environments—and what an effective data platform looks like in practice.

[1]Monday, March 16, 2026 | 6:00pm - 8:30pm | San Jose

Attendees will discuss where AI initiatives break down, how enterprises are enabling real-time inference at scale, and what future-ready data platforms look like. Conducted under Chatham House Rules to encourage candid, unfiltered conversation.

Places are limited. If you're leading infrastructure, data, or AI initiatives at enterprise scale, [2]register your interest here and we'll confirm your place.

Get our [3]Tech Resources



[1] https://www.theregister.com/Page/events/2026-03-16/?source=theregister

[2] https://www.theregister.com/Page/events/2026-03-16/?source=theregister

[3] https://whitepapers.theregister.com/