Data Is Choking AI. Here's How To Break Free.
VentureBeat, Friday, May 5,2023
AI is a voracious, data-hungry beast. Unfortunately, problems with that data - quality, quantity, velocity, availability and integration with production systems - continue to persist as a major obstacle to successful enterprise implementation of the technology.
The requirements are easy to understand, notoriously hard to execute: Deliver usable, high-quality inputs for AI applications and capabilities to the right place in a dependable, secure and timely (often real-time) way. Nearly a decade after the challenge became apparent, many enterprises continue to struggle with AI data: Too much, too little, too dirty, too slow and siloed from production systems. The result is a landscape of widespread bottlenecks in training, inference and wider deployment, and most seriously, poor ROI.