7 Secret Patterns AI Can Help You Identify and What You Can Do with Them

AI is everywhere. Whether it is the automobile industry, financial institutions, manufacturing, health care, smart homes, or cybersecurity, you will see AI at work in some capacity. These are only some of the applications of AI and many new ones are emerging with each passing day.

  Despite the diversity in AI applications, there are certain characteristics that all AI applications share. Based on that, you can categorize them into seven different patterns. Yes, it might be impossible to limit an ever-evolving field like AI into seven patterns but doing so will help you cover most of the use cases of artificial intelligence and help you develop a better understanding of it.

In this article, you will learn about how AI can help you find hidden patterns and how you can use them to your advantage.

1. Hyper-Personalization Pattern

With users demanding personalized user experiences, brands will harness the power of AI and start to treat each customer as a separate entity. That is where the hyper-personalization pattern comes into play. It allows brands to create a profile for each customer and then tweak that profile to fulfill different purposes such as

• Delivering relevant content
• Recommending the right products
• Show relevant ads

This is achieved by analyzing user behavior, browsing patterns, and searches. Netflix is already using this hyper-personalization pattern to recommend movies and TV shows and Starbucks is taking advantage of personalization to connect with its customer base. We are also seeing its applications in the financial and fitness industries too. Hyper-personalization helps mobile app development company Dubai to optimize user experiences and deliver what they want.

2. Automation Pattern

In today’s competitive business environments, profit margins are slim. Businesses are looking at cost-cutting measures and switching to an autonomous system is one of them. It will not minimize business reliance on manual labor but also reduce the burden off the shoulders of your employees. With machine learning behind its back, autonomous patterns can perceive the external environments and predict the future behavior of different elements. Additionally, it also allows you to develop a plan which can help you cope up with future changes. This type of pattern is frequently used in the automobile and aviation industries.

3. Conversational Pattern

Human-computer interaction has been around for quite some time now and scientists have always dreamed about designing machines that can communicate as humans do. We have come very close to achieving that goal with chatbots, smart voice assistants, and sentiment and mood analysis technologies.

The biggest advantage of these technologies is that they can also facilitate human-to-human interactions by implementing advanced natural language processing and language translation capabilities. What’s even more interesting is that smart assistants and devices now accept multiple forms of input such as voice, text, or images, which means that you can communicate with them using any of these methods.

4. Predictive Analytics With AI

Predictive analytics allows brands to analyze past and present user behaviors and predict future outcomes based on these patterns. The goal of using machine learning is to make smarter decisions but brands must follow machine learning ethics while using predictive analytics.

When you combine predictive analytics with artificial intelligence, you can easily predict the future values of data based on past and current data points. That’s not all, it can also be used for:

• Predicting failure
• Identifying and choosing the best solution
• Identifying matches in data
• Offer useful advice
• Smart navigation
• Solving problems
• Perform optimization activities

In short, it equips you with augmented intelligence capabilities, which would help you make the right decisions. When you make the right decisions at the right time, you will achieve better business results.

5. Recognition

Researchers are striving to create machines that can recognize the world and have succeeded to a certain degree. Deep learning, which is a subset of machine learning, can help you recognize images, videos, audio, and objects with precision. Recognition patterns capitalize on machine learning along with other cognitive approaches to recognize objects from unstructured data sets. Many tech giants, businesses, and even governments are investing heavily in recognizing patterns and using them for object identification purposes.

Some of the examples of recognition patterns can be found in:

• Facial recognition
• Voice recognition
• Gesture detection
• Handwriting recognition

6. Goal-Driven Systems

As organizations become more goal-oriented, they are also switching towards goal-driven systems. Thanks to advancements in machine learning, machines can now learn and adapt. Not only can machines learn the rules of a game, but they can also beat humans at it too. We have seen machines beat humans at chess, checkers, and Go. That’s not all, machines are also establishing their supremacy in video games too. They have defeated gamers at multiplayer games and complex games such as DotA.

This means that organizations can deploy machine learning and other cognitive approaches to help their goal-driven system to learn through trial and error. This can come in handy when you want your system to help in choosing the best solution for a problem. This type of AI pattern relies on reinforcement learning and is gaining a lot of popularity.

Here are some of its applications:

• Resource optimization
• Iterative problem solving
• Real-time actions
• Online bidding
• Games

7. Anomaly Identification

One of the hallmarks of machine learning is its capability to identify patterns. What makes machine learning special is its ability to create higher-order connections between different data points. It can check whether the data points belong to an existing pattern or is an anomaly. This makes it an ideal choice for fraud detection and risk management. That is why it is widely used in cybersecurity. It can also be used to identify and fix human errors. Moreover, it can suggest words while you are typing by analyzing patterns and pointing out spelling and grammatical mistakes.

How do you use AI in your organization? How will AI help with pattern identification?  What patterns do you identify? Let us know in the comments section below.