Roadblocks to getting real-time AI right

“Analysts estimate that by 2025, 30% of generated data will be real-time data. That is 52 zettabytes (ZB) of real-time data per year – roughly the amount of total data produced in 2020.
Over the last decade, technologies have been developed by the likes of Materialize, Deephaven, Kafka and Redpanda to work with these streams of real-time data.
But to really make such enormous volumes of data useful, artificial intelligence (AI) must be employed.
To make real-time AI ubiquitous, supporting software must be developed. This software needs to provide:

An easy path to transition from static to dynamic data
An easy path for cleaning static and dynamic data
An easy path for going from model creation and validation to production
An easy path for managing the software as requirements – and the outside world – change”