How is AI finding patterns and anomalies in your Data?

AI finding pattern and anomalies

The most adopted of the seven patterns of Artificial Intelligence is Patterns and Anomalies pattern. The mission of the Patterns and Anomalies pattern of Artificial Intelligence is to use ML and other approaches to understand patterns in the data and discover connections between the data.

Why is it Patterns and Anomalies in AI is important?

Data is at the living source of AI so it’s no surprise that computers shine at recognizing patterns in data. Whether it’s patterns of behavior, actions, input, or other patterns, AI systems are ready to quickly spot it. Using AI to identify patterns is right because humans, by nature, are unpredictable. AI is ready to detect patterns that humans might not have even thought to appear for. Also, AI is ready to listen to lots more information at only once as against the limited amount of information that humans can process and analyze.
Businesses now are beginning to understand the importance of interconnected operations to get a clear image of their business and they need to respond to fast-moving data quickly mainly in cybersecurity threats. Patterns and Anomalies pattern of Artificial Intelligence could be key in solving it.

Top 3 Application how Patterns and Anomalies in AI work

1. Automatically correcting errors

Patterns and anomalies matching in AI may also be wont to automatically detect and proper errors. Data is commonly incomplete. AI systems can spot errors and make adjustments as required.AI can learn what normal patterns and behavior seem like, spot and fix errors, automatically fix issues on its own and supply feedback if needed.

2. Fraud detection and Risk Analysis

The financial sector, especially in banking and MasterCard processing institutions, are early adopters in using machine learning and AI to enable real-time identification of probably fraudulent transactions. Artificial Intelligence-based systems are ready to handle many transactions using trained models to form decisions on a second whether a specific transaction is valid or not. These models can identify which purchases don’t fit usual patterns and take a look at interactions between money transaction parties to come to a conclusion. So patterns and anomalies of AI play a very important role here.

3. In Business

One example Walmart used AI to detect sales patterns. One of the connections Walmart a leading supermarket noticed was the relation between the hurricane and strawberry flavored pop-darts.In addition to regular shelter amenities, people backed up these strawberry flavored pop darts which was detected from the sales pattern and anomalies using the AI. And so they loaded the store with strawberry flavored darts. This prediction will be tough for humans while this AI has predicted so easily.

Conclusion

By thinking AI in terms of pattern, more projects could be planned and executed more efficiently.
Once you find a pattern and anomalies for any problem you can find a solution easily.

AI finding pattern and anomalies

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