RIPEVA's official blog. Visit us at: www.ripeva.com
"A Different Kind of Company. A Different Kind Of IT."
Tuesday, January 19, 2021
How AI is finding patterns and anomalies in your data
From autonomous vehicles, predictive analytics applications, and facial recognition, to chatbots, virtual assistants, cognitive automation, and fraud detection, the use cases for AI span dozens of industries. Regardless of the AI application, though, these use cases all have a common aspect. After implementing thousands of AI projects, experts have come to realize that despite all of the diversity in applications, AI use cases fall into one or more of seven common patterns. One of them—the pattern-matching pattern—has allowed machines to digest large amounts of data to identify patterns, anomalies, and outliers in the data, so organizations can unearth previously undiscovered insights in their datasets.
In this article, you'll learn how pattern-matching is being put to use in today's organizations to prevent fraud, find the best job candidates, manage inventories in times of crisis, and empower data scientists with new perspectives on how to improve critical processes.
Subscribe to:
Post Comments (Atom)
The Total Economic Impact™ Of Microsoft Dynamics 365 ERP
Leaders need clear, data-backed evidence before investing in change. The Forrester "Total Economic Impact of Microsoft Dynamics 365 ERP...
-
Streamline collaboration and simplify your business's processes with connected tools. This blog discusses how Microsoft Dynamics 365 Bus...
-
Explore how cloud AI services could be the catalyst for your enterprise's AI implementation journey. This compelling Forrester report fr...
-
Sellers often struggle with manual tasks that reduce time spent with customers. This solution brief outlines how Copilot in Microsoft Dynami...
No comments:
Post a Comment