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Types of Artificial Intelligence

There’s a reason why “artificial intelligence” (AI) is one of the trendiest terms in the IT industry. Numerous technological breakthroughs that were once the stuff of science fiction have begun to permeate everyday life in recent years. Artificial intelligence is now widely recognized as a production element with the potential to revolutionize businesses and whole economies.

AI in Different Types of Sectors:

In this advanced tech-era, AI is almost used in every possible industrial sector, such as:

  • Healthcare
  • Banking
  • Retail
  • E-Commerce
  • Entertainment
  • Transportation

Types of Artificial Intelligence:

Since AI is rapidly progressing and becoming smarter, some are scared that it could soon take over the world. Since AI has such dramatic impacts in many fields, many in business and the public believe we are on the cusp of achieving the apex of AI research. Understanding the present level of AI and the long road ahead for AI research requires an appreciation for the breadth and diversity of AI.

AI is categorized in different types depending on two major factors:

  1. Capabilities: According to the capabilities of AI machines, these are classified. Capabilities are divided into three types:

a. Narrow AI
b. General AI and
c. Super AI

2. Functionalities: This is categorized depending up on the functionalities present in the AI. Functionalities are divided into four types:

a. Reactive Machines
b. Limited Memory
c. Theory of Mind
d. Self-Awareness

Let’s learn how capabilities and functionalities play their roles in global market.

There are three types of capabilities:

a. Narrow AI:

Narrow AI, also known as Weak AI. It is limited to a single task and cannot function beyond its boundaries. It targets a particular group of cognitive talents and improves in that range. As machine learning and deep learning methodologies continue to advance, narrow AI applications are becoming more prevalent in our daily lives.

Examples of Narrow AI:

  • Apple Siri: It has a predetermined set of restricted functions. Siri has trouble handling things that are too complex for it to handle.
  • IBM Watson supercomputer: It is another Narrow AI example. It uses cognitive computing, machine learning, and natural language processing to process information and answers your questions. On the popular game show Jeopardy!, IBM Watson once beat human contestant Ken Jennings and won.
  • Other Examples: Google Translate, picture recognition software, recommendation systems, spam filters, and Google’s page ranking algorithm are further examples of Narrow AI.

b. General AI:

General AI also called as Strong AI. It is smart enough to learn and understand everything a human can. Basically, it is a computer’s ability to use skills and information it has already learned in new situations. But researchers haven’t been able to make a strong AI yet, which is what they want to do. To make robots act like sentient humans, people would have to figure out how to give them all of humans’ cognitive abilities. Microsoft has put $1 billion into research on AI through its OpenAI project.

Examples of General AI:

  • K Computer by Fujitsu: It is a supercomputer with a top ranking in terms of speed. It’s an important step toward developing powerful AI. Almost 40 minutes were spent simulating only one second of brain activity. As a result, predicting when we will have powerful AI is challenging.
  • Tianhe-2: It is a powerful machine created by scientists at China’s National University of Defense Technology. It’s the fastest computer ever created, with 33.86 petaflops (quadrillions of cps). Despite that, the human brain can operate at one exaflop, or a billion cycles per second.

c. Super AI:

Super AI has exceeded human intellect and can accomplish anything a human can. Artificial superintelligence is the theory that AI will become so clever that it can grasp human thoughts and experiences and be affected by them to feel and behave in accordance with their own values and aims. Nobody knows whether it exists. Super AI can think, reason, solve problems, make choices, and act on its own.

Examples of Super AI:

With the help of advanced AI, we can set up machines to run 24×7. Institutions of higher learning, for instance, often staff call centres to answer the many questions students have every day. Super AI can manage this with ease, responding with highly tailored answers to questions at all hours.

There are four types of AI functionalities:

a. Reactive Machines:

Reactive Machine is the basic kind of artificial intelligence that does not store memories or utilise previous experiences to guide future behaviours. It only operates with current data. They observe and respond to the surroundings. Reactive machines are assigned specified duties and do not possess any further skills.

b. Limited Memory:

Limited Memory AI learns to make judgments using historical data. Such systems have temporary memory. They are permitted to utilise this historical information for a limited time but are not permitted to add it to a library of their experiences.

c. Theory of Mind:

Theory of Mind AI is a cutting-edge type of technology that only exists in concept. A deep grasp of how the people and objects in an environment may change emotions and behaviour is necessary for this form of AI. It needs to be able to comprehend the feelings, opinions, and ideas of others. Even though this sector has seen significant advancements, this particular AI still needs work.

d. Self-awareness:

Self-awareness AI is purely theoretical at this point. These programs can recognise human emotions and understand their causes and effects. All of these gadgets will have greater intelligence than the average human being. As well as being able to recognise and elicit emotions from the people with whom it interacts, this kind of AI will have its own set of feelings, goals, and beliefs.

Conclusion:

Perhaps we are still a long way off from building self-aware, problem-solving machines using AI. However, we need to put in the time and effort required to comprehend how a machine may self-train and learn, eventually developing the capacity to make judgments based on its own prior experiences.

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