What Is AI? and What is not AI?

In this article. we’ll discuss AI in detail, and talk about Components of AI and Use Cases, applications of AI in real-world.

Al refers to the ability of machines to perceive, learn, interact with the environment, analyze, and solve problems independently.

Let us take a closer look at how Al-driven systems interact with our environment. Like us humans, Al-driven systems can see, listen, talk, remember information, and analyze/act.

We refer to these capabilities of Al-driven systems as five Al senses, and the technologies associated with these senses are known as core Al components.

The core components are the central building blocks of Al-driven systems, based on which user applications are developed.

Core AI Components

The following table describes the core components of AI and sample application areas.

How to identify an AI-Driven System?

If the answer is “yes” to any of these questions, the system uses AI for decision making and taking actions,

What Is Not Al?

A system does not use Al, if it uses:

  • A set of pre-defined rules to automate human tasks.
  • ML algorithms to predict something (generated in the form of a report), but there is no action taken based on such predictions.
  • ML algorithms to find correlations and patterns in the data.
  • Cognitive technologies to extract information from human speech, text, or videos but there is no action associated with the intelligence derived.

One thumb rule to remember: “If a system is not capable of making independent decisions, it’s not an Al-driven system.”

AI Use Cases

Let us look at a few examples of how AI-driven systems are taking actions based on predictions provided by ML algorithms.

Future of AI

More and more organizations are realizing the true value that Al can bring to their organizations. Let us
look at some areas where Al can make a big difference.

Al will augment and enhance, rather than automate The ‘Intelligence’ in Al should perceive and behave in human
and replace, our human experiences. and familiar ways.

Note of Caution:

“As Al-driven systems make decisions based on ML algorithms, which in turn, rely on data collected from various sources, the systems can sometimes make incorrect, even biased decisions. Therefore it is essential to use diverse data sets and apply ethical standards while developing ML algorithms”.

Applications of AI in real world

  • Pharma companies can analyze the sales data of the past years to understand the sales pattern of each of its products. Which of the analytics applications can be used? Descriptive analytics! provides an insight into the past and answers the question of what has happened. So, organizations can use descriptive analytics to create a summary of the historical sales data.
  • Smart email categorization and automatic spam filters used in Gmail is one of the prominent applications of machine learning.
  • Core Al component can be related to the sensory function- The computer/smart vision component of Al enables systems to extract meaningful and actionable information by analyzing digital images and videos.
  • A well known real-world application is Chatbots. Using chatbots as virtual personal assistants, the bank can enhance their customer service operations.
  • Another renowned application is the Al-driven system, the system makes human-like intelligent decisions based on facts/data.

Summary

  • Al-driven systems can see, talk, listen, analyze or act, and remember information.
  • The core Al components associated with decision making are:
  • 1. Natural language processing technology.
  • 2. Computer vision technology.
  • 3. Augmented or prescriptive analytics technology.
  • 4. Smart data discovery technology