There was once a time when people dreamed of living in an automated world where daily mundane tasks would be in control of robots. However, with time this mere dream has transformed into a reality with the rapid rise of Artificial Intelligence (AI) which has introduced the world to an array of possibilities and opened up a whole new dimension. Today, Artificial Intelligence is a word used in many fields from voice assistants to self-driving cars. The types and applications are in discussion and all these services are available to serve individual needs. Hence reaffirming the dream of having an automated world where designed intelligent beings take care of your all affairs.

 
But companies like to use the term AI to explain even the simple analytics or functionalities. Today, we will like to talk about AI in a way that will help you understand what it is and how is it evolving. We will explore where is it available, and who are the companies making use of AI.
Let’s start with the most generic question “What Is Artificial Intelligence?”

Artificial Intelligence Definition

The definition of Artificial Intelligence says: “Description In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans.” Artificial Intelligence (AI) refers to the induction of human intelligence in computers which are experts to think like humans and imitate their behavior. Additionally, the word may also refer to any computer that displays human mind-like characteristics such as learning and problem-solving based on that learning.

Above all, AI is the technology that makes machines “think”. Also, it enables them to do tasks like humans do. It is not remembering data and process it as common programs do. It is enabling machines to think on their own and make logical decisions about things like humans do. The common technologies or algorithms that make AI possible are listed below. Anything that doesn’t use these high-level algorithms can’t be regarded as AI.
  • Machine Learning
  • Deep Learning
  • Neural Networks
  • Bayesian networks
  • Evolutionary algorithms

Artificial Intelligence Background

Before we move on to discover the various types and applications of artificial intelligence, we need to visit the world of Alan Turing and more specifically the Turing Test; a method of inquiry.
 
Long before AI was a commonly used term in the world. Alan Turing had made a proposition that highlighted that the criteria for a computer to qualify as having artificial intelligence would simply be whether or not it could mimic human responses under specific conditions.
 
The test places a human observer or judge at the center of it all and asks it to decide the “human” out of the two candidates (one of which is a computer). If the judge points to the computer as the human candidate, it means that the computer did indeed have artificial intelligence. Since it was able to present itself convincingly as a human to a blind judge.
 
While this test has its own set of problems with validity and even with the method of performance. It does not do away with the fact that with the right training and programming, computers can gain accurate knowledge and data. This can be useful to assist humans across a variety of forms/arenas.

Types of Artificial Intelligence

The following can also be thought of as stages of AI through which AI is evolving and finally reach the stage like human intelligence. We discuss the three most common types of AI below.

1. Artificial Narrow Intelligence (ANI)

Artificial Narrow Intelligence (ANI), also known as Narrow AI or Weak AI, is a form of Artificial Intelligence that performs one narrow -range or a single task. It has a limited spectrum of capabilities. For now, this is the AI that exists largely today. A machine that possesses ANI doesn’t mean it is dumb. Instead, it means it can work with a small amount of data than humans do.

2. Artificial General Intelligence (AGI)

When the term AI comes to mind, it generally refers to AGI. If an Artificial Intelligence system is designed to completely emulate human intelligence and behavior, we call it Artificial General Intelligence. Moreover, some scientists also like to call it Strong AI and Full AI. Simply put, it is the Artificial Intelligence System that can function and make similar decisions like humans.

3. Artificial Super Intelligence (ASI)

Artificial Super Intelligence (ASI) is the conceptual AI, often termed as Super AI, that not only imitates human intelligence and behavior. It is the stage where computers are self-conscious and exceed human intelligence and ability. Also, replicating human beings’ multifaceted intellect, ASI would be far stronger at everything we do like maths, science, art, sports, medicine, entertainment, interpersonal relationships, everything. Ultimately, super-intelligent beings’ decision-making and problem-solving capacities would be far superior to human beings.

Applications of Artificial Intelligence

The following are some of the major applications of AI that are currently in use.

1. Knowledge reasoning

Knowledge representation and reasoning in the field of artificial intelligence dedicated to representing information about the world in a form that a computer system can use to solve complex tasks. Accordingly, the application allows a computer to collect raw data in different companies, institutions, and centers. Likewise, it then represents it in graphical forms to extract relations and patterns in the data. A machine then finally uses this data form to take further actions just like humans would do. The most common examples of knowledge reasoning are medical diagnose, human-like speech, or theorem provers.

2. AI Planning

Automated planning, commonly referred to as AI planning, is the application of AI that deals with producing concrete steps or courses of action for a specified task that optimize performance measures. AI planning describes steps for a described system. These algorithms make use of the way humans perform a task. So, they write code for machines to do the same. Common examples include robots and autonomous systems, cognitive assistants, and service composition.

3. Machine learning (ML)

Instead of using explicit instructions, relying on patterns and inference, ML is the subset of AI that uses training data to make predictions about a specific field. it is also referred to as predictive analytics as it trains on historical data available about a domain and learns the factors that contribute to the output. ML algorithms are available in a wide range of applications, such as email filtering, weather prediction, and computer vision, where the creation of a traditional algorithm to perform the task is difficult or unfeasible.

4. Natural language processing (NLP)

NLP is like a subfield of linguistics, computer science, information engineering, and artificial intelligence. It deals with the interaction between machines and humans. As humans use natural languages to communicate. This field enables machines to understand these languages and respond in the same manner. You can see the most common example in digital personal assistants(DPA).

Applications Of Natural Language Processing (NLP)

5. Computer vision (CV)

Unlike NLP which uses text to extract information, CV uses digital images or videos to help computers gain a high-level understanding of the world. A CV is described as a field of study aimed at developing techniques to help computers “see” and comprehend digital media, such as photographs or videos. However, this remains an unresolved problem based on both the limited knowledge of biological vision and the nature of visual perception in a physical world that is dynamic and almost variable. It is commonly used in image processing/editing applications.

What is Computer Vision and How is it Transforming Our World?

6. Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. Computer science, in particular, uses this as a form of identity access management and control whereby it can create personalized identity checks to prevent any mismatch or sharing of identities. Furthermore, It is available over a wide array of industries with many of them choosing it as their method of keeping track of employees and their workings within the organization.

7. Virtual Agent

Probably one of the most sought after AI applications, a virtual agent is a computer-generated, animated, artificially intelligent character that is posed as the online customer service representative for the business. It has the ability to not only conduct a conversation with humans but also direct it towards particular topics on individual concerns.
 
Moreover, outside the world of commerce, these agents are also able to perform non-verbal behavior and listen to humans to hold conversations with them regarding everyday topics if need be.

8. Deep learning Platforms

Used in pattern recognition and classification (for large sets), this is a special type f machine learning that consists of artificial neural networks with many abstraction layers.
 

What this helps to do is break down the data sets and arrange them in particular manners to aid the understanding and to help figure out any patterns/classifications/groupings that might be possible within that one set. All this also helps to gain insight on data repetition, data formation, and the crossover of data on many ends.

Deep Learning Frameworks: Choose The Best Fit For You

Major AI Companies in the World

Below is a brief introduction of major companies (hand-picked from Forbes AI 50 list around the world that are using AI to solve real-world problems.

Nuro

An AI company that builds autonomous vehicles to transfer goods. The range is from retail centers and shops to homes or storage to shopping centers.

Uptake

A five-year-old company that leverages artificial intelligence to analyze how its customers’ machines can run better and avoid common failures.

Lemonade

They sell renters and homeowners insurance through the use of a chatbot to collect customer information and work through claims.

Dataminr

The company ingests public internet data. Like social media posts and uses deep learning, natural language processing, and advanced statistical modeling to send users tailored alerts.

Icertis

Earlier this year, the company celebrated its tenth anniversary. The uses a cloud-based platform to help companies analyze past contract negotiations and automate administrative tasks.

Conclusion

In the future, predictive analysis and artificial intelligence can quite literally spearhead the development of content and software. This means that you would just need a computing system to recognize needs and create solutions that could counter those very specific needs only.
 
Therefore, the only way to go from all of this is upwards. Since the latest advancements stand as proof of the massive potential that AI holds. Accordingly, it helps companies and individuals understand why they need to slowly transition their practices and adapt methodologies to suit the future needs for growth.