| |
|
| |
Token costs have overtaken hallucinations as the top reason enterprise AI projects die before reaching production; it's cited by 29% of technical leaders as the primary production killer, ahead of every reliability failure combined. The teams seeing success don't treat inference cost as an after-the-fact line item. They architect for token costs from the beginning.
This event examines what that shift actually looks like in practice: GPU memory & data architecture decisions that determine cost per token served & the orchestration choices that separate a project that survives its second budget review from one that doesn't.
We'll open with new VentureBeat Pulse Research on how enterprises are - & aren't - measuring the economics of the AI they're already running.
This isn't a panel. It's a small group of peers, over drinks, working through the hardest question in enterprise AI right now.
Featured Speakers:
An evening conversation & drinks with a small number of enterprise AI leaders, kept intentionally close to keep the conversation substantive.
|
|
|
|
|
|
|
|
