5 Artificial Intelligence Applications You Can See in Action Today

In recent years, no emerging technology has captured as much attention as artificial intelligence (AI). But with great hype often comes great confusion; navigating your way through the various applications of AI development can quickly become an arduous endeavor.

Nonetheless, gaining a good grasp of AI’s uses is essential to understanding the field on a comprehensive scale. To help make sense of it all, let’s cover five of our favorite AI applications that you can see in action today.

Narrow AI

To start things off, let’s dive into the type of AI you’re probably most familiar with: Narrow AI. It’s likely that you’ve already used Narrow AI at some point today. You can find Narrow AI present in Netflix’s recommendations for what to watch next, Amazon’s shopping suggestions, Tesla’s self-driving car systems, and just about any place where AI is present.

Narrow AI is an AI system that focuses on solving one particular, pre-defined task. Whether it’s telling you the weather or beating you at chess, Narrow AI is superb at dealing with one specific problem — and only that problem. Because it is trained to deal with a distinct issue, Narrow AI is trained with specific data. After this training, it is well-equipped to handle this scenario, and nothing more.

Due to these constraints, Narrow AI is also commonly called Weak AI. It is not self-aware of sentient. It does not possess the capacity to match human intelligence. And it cannot learn and adapt to wildly different problems like a human can. For example, a machine learning application that’s trained to analyze x-rays usually cannot be utilized to predict stock market movements. To accomplish such a feat, you’d need to turn to a General AI system for help.

General AI

Also known as Adaptable AI or Strong AI, General AI can theoretically be used to tackle a variety of tasks. It even has the potential to handle brand new scenarios it hasn’t encountered before. The concept of General AI much more closely resembles a human’s ability to adapt than Narrow AI. General AI has the capacity to reason, learn, strategize, and communicate like a human being.

Because of these advanced abilities, General AI is much more complicated to create than Narrow AI. Consequently, this category of AI is still very much in its preliminary stages of development. This makes sense when you think about it. Synthesizing information, interpreting it, and creating new concepts based on these findings are all abilities that humans take for granted since it comes to us naturally. Replicating these skills in a machine shines a light on just how complex these processes really are.

As a result, the concept of General AI has become a divisive topic for those that work with AI every day. While some industry experts see it as the ‘holy grail’ of AI, others believe it will not be feasible for many decades to come, if at all. Still, the benefits it offers (even if not completely achieved) are too immense to resist pursuing.

The Transformation of Big Data into Smart Data

Big data is a field that revolves around the extraction and analysis of massive amounts of structured and unstructured information. This data is often too immense and complex for standard data-processing protocols and software to handle. The insights that can be elucidated from this mountain of information can be game-changing. For this reason, organizations from San Francisco to Tokyo are racing to tap into this field’s potential by combining it with AI.

Netflix’s product development is a prime example of big data and AI working together. With a user base exceeding 100 million people, the streaming company was able to build predictive recommendation models. By tracking numerous factors such as preferences, how a user discovers new content, search queries, ratings, and even when a user pauses or stops watching a program, Netflix is able to recommend viewers movies or shows that might interest them.

Data Mining

Used often in big data, data mining is a combination of computer science and statistics that extracts insights from information with AI’s help. By sifting through vast sets of data, miners can identify recurring patterns that can aid in solving longstanding problems.

E-commerce giant Amazon was one of the early proponents of data mining. By identifying buying patterns in their customer data, Amazon is able to infer other potential purchases that consumers may like. For example, if you purchase a phone from Amazon’s platform, it’s likely that it will recommend you check out phone cases, protective screens, and other auxiliary equipment for your new gadget.

Computer Vision

Computer vision is how a machine sees and makes sense of the world around it. By processing visual input from either static images or video feeds, AI systems are not only able to “see” this visual input but also understand what it is seeing. It’s akin to the part of a human’s brain which processes visual input from the eyes, not the eyes themselves.

After a user inputs an image into a computer vision system, it can output a variety of qualitative and quantitative features, like the image’s color, classification, shape, or size. Tesla’s self-driving systems are a great example of this in action. These systems have to be capable of recognizing and processing variables like shapes, type of object, and color extremely quickly so that the vehicle can act accordingly in real-time.

More AI Applications Are on the Way

We hope you’ve enjoyed this overview of AI applications you can see in action today! Hopefully, it has helped you understand how this incredible technology can be used to solve a plethora of problems.

Are you yearning for more examples of AI? Well, here’s some great news — this list barely scratches the surface of what AI is capable of! Stay tuned for a follow-up post. We’ll take a deep dive into even more AI applications.