We have all seen demonstrations of the capabilities of Artificial Intelligence (AI)-based imaging applications, from facial recognition to computer vision assisted application platforms. However, scaling these imaging implementations to Petabyte-scale for real-time datasets is problematic because:
Utilizing brute-force methods on modern imaging databases, which can be in the petabyte-size range, is often both incredibly difficult and enormously expensive. This has forced organizations with extremely large image databases to look for new approaches to image similarity search and more generally to the problem of data storage and analysis.
To read the whole pager, please fill in below details.