Artificial Intelligence can be classified into the following three types.
●Artificial Narrow Intelligence (ANI) [Dedicated for One task]
●Artificial General Intelligence (AGI) [Behaves like Human]
●Artificial Super Intelligence (ASI) [Intelligent than human]
Artificial Narrow Intelligence (ANI)
Artificial Narrow Intelligence (ANI) is the most common form of Artificial Intelligence. It is designed to solve one single problem. This type of Artificial Intelligence works in o very controlled environment with a limited set of parameters. It is the only type of Artificial Intelligence that presently exists. For example, recommending a product for an e-commerce user and predicting the weather are some of the applications of ANI.
Artificial General Intelligence (AGI)
Artificial General Intelligence (AGI) is still a theoretical concept having a human-level of cognitive functions across a wide variety of domains such as language processing, Image processing, computational functioning and reasoning. An AGI system would consist of many ANI systems working together and communicating with each other to imitate human reasoning.
Artificial Super Intelligence (ASI)
Artificial Super Intelligence (ASI) is seen as the logical progression from AGI, An ASI system would surpass all human capabilities including decision making, taking rational decisions and even building emotional relationships as seen in imaginary movies. While the gap between AGI and ASI would be relatively narrow, the long journey ahead of us towards AGI Itself makes this a concept that would be practical very far away in future.
Approaches of Artificial Intelligence
It is important to know that most of the present day computers that you use are fourth- generation computers and hence are not smart machines. The fifth generation computers are the latest development in the field of Computer Science which is still in research and development, though this field is emerging at a very fast speed in all areas of our life whether it is business, science, medicine, space, defence, education, transport, airlines or railways. Before discussing various applications of Artificial Intelligence, particularly in daily use, let’s briefly discuss following four historical approaches of Artificial Intelligence that have been followed by different people..
Thinking Humanly
Thinking Humanly is the cognitive modelling approach followed in Artificial Intelligence, where a computer program thinks like a human. This approach relies on three techniques – Introspection psychological experiments and brain imaging. Introspection means trying to catch our own thoughts as they go by. Psychological experiments refer to observing a person’s behaviour and adding it to a database of similar behaviours obtained from other persons during similar conditions. Brain imaging refers to observing the brain in action through techniques like Magnetic Resonance Imaging (MRI) and Magneto Encephalography (MEG).
Al Fact
Thinking Humanly technique was proposed by Allen Newell and Herbert Simon, who developed the General Problem Solver (GPS) system in 1961.
Acting Humanly
Acting Humanly is the Turing Test approach developed by Alan Turing in 1950. This approach was designed to provide a satisfactory operational definition of Artificial Intelligence by providing the following capabilities to a computer.
•Natural Language Processing (NLP) that enables the computer to communicate in national language like English
• Knowledge Representation for storing the Knowledge gained
•Automated Reasoning for drawing conclusions from the stored information or knowledge
• Machine Learning for adopting the computer to new circumstances
Thinking Rationally
Thinking Rationally is the “Lows of Thought” approach based on the logical thinking process attempted by the Greek Philosopher Aristotle. The goal of thinking rationally approach is to solve problems logically, when possible. The main drawback of this approach is that it is not- easy to convert informal knowledge into formal terms required by logical notation.
Acting Rationally
Acting Rationally is the rational agent approach that uses rational agents for solving problems intelligently. A rational agent is a program that operates autonomously by perceiving its environment in order to achieve the best outcome of the problem being solved. The rational agent approach has two advantages over the other three approaches. First, It is more general as correct inference is the only one of several possible methods for achieving rationally. Second, It is more amendable than human behaviour or thought-based approaches for scientific Development.