Artificial Intelligence Overview

AI (pronounced AYE-EYE) or artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. Particular applications of AI include expert systems, speech recognition, and machine vision.


Since the invention of computers or machines, their capability to perform various tasks went on growing exponentially. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time.

A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings.

What is Artificial Intelligence?

According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”.

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.

AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.

Philosophy of AI

While exploiting the power of the computer systems, the curiosity of human, lead him to wonder, “Can a machine think and behave like humans do?”

Thus, the development of AI started with the intention of creating similar intelligence in machines that we find and regard high in humans.

Goals of AI

  • To Create Expert Systems ? The systems which exhibit intelligent behavior, learn, demonstrate, explain, and advice its users.
  • To Implement Human Intelligence in Machines ? Creating systems that understand, think, learn, and behave like humans.

What Contributes to AI?

Artificial intelligence is a science and technology based on disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. A major thrust of AI is in the development of computer functions associated with human intelligence, such as reasoning, learning, and problem solving.

AI has been dominant in various fields such as ?

  • Gaming ? AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge.
  • Natural Language Processing ? It is possible to interact with the computer that understands natural language spoken by humans.
  • Expert Systems ? There are some applications which integrate machine, software, and special information to impart reasoning and advising. They provide explanation and advice to the users.
  • Vision Systems ? These systems understand, interpret, and comprehend visual input on the computer. For example,
  • A spying aeroplane takes photographs, which are used to figure out spatial information or map of the areas.
  • Doctors use clinical expert system to diagnose the patient.
  • Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist.
  • Speech Recognition ? Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human’s noise due to cold, etc.
  • Handwriting Recognition ? The handwriting recognition software reads the text written on paper by a pen or on screen by a stylus. It can recognize the shapes of the letters and convert it into editable text.
  • Intelligent Robots ? Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors and huge memory, to exhibit intelligence. In addition, they are capable of learning from their mistakes and they can adapt to the new environment.


History of AI

Here is the history of AI during 20th century ?

YearMilestone / Innovation
1923Karel ?apek play named “Rossum's Universal Robots” (RUR) opens in London, first use of the word "robot" in English.
1943Foundations for neural networks laid.
1945Isaac Asimov, a Columbia University alumni, coined the term Robotics.
1950Alan Turing introduced Turing Test for evaluation of intelligence and published Computing Machinery and Intelligence. Claude Shannon published Detailed Analysis of Chess Playing as a search.
1956John McCarthy coined the term Artificial Intelligence. Demonstration of the first running AI program at Carnegie Mellon University.
1958John McCarthy invents LISP programming language for AI.
1964Danny Bobrow's dissertation at MIT showed that computers can understand natural language well enough to solve algebra word problems correctly.
1965Joseph Weizenbaum at MIT built ELIZA, an interactive problem that carries on a dialogue in English.
1969Scientists at Stanford Research Institute Developed Shakey, a robot, equipped with locomotion, perception, and problem solving.
1973The Assembly Robotics group at Edinburgh University built Freddy, the Famous Scottish Robot, capable of using vision to locate and assemble models.
1979The first computer-controlled autonomous vehicle, Stanford Cart, was built.
1985Harold Cohen created and demonstrated the drawing program, Aaron.
1990Major advances in all areas of AI ?

  • Significant demonstrations in machine learning
  • Case-based reasoning
  • Multi-agent planning
  • Scheduling
  • Data mining, Web Crawler
  • natural language understanding and translation
  • Vision, Virtual Reality
  • Games
1997The Deep Blue Chess Program beats the then world chess champion, Garry Kasparov.
2000Interactive robot pets become commercially available. MIT displays Kismet, a robot with a face that expresses emotions. The robot Nomad explores remote regions of Antarctica and locates meteorites.


While studying artificially intelligence, you need to know what intelligence is. This chapter covers Idea of intelligence, types, and components of intelligence.


What is Intelligence?

The ability of a system to calculate, reason, perceive relationships and analogies, learn from experience, store and retrieve information from memory, solve problems, comprehend complex ideas, use natural language fluently, classify, generalize, and adapt new situations.

Types of Intelligence

As described by Howard Gardner, an American developmental psychologist, the Intelligence comes in multifold ?

Linguistic intelligenceThe ability to speak, recognize, and use mechanisms of phonology (speech sounds), syntax (grammar), and semantics (meaning).Narrators, Orators
Musical intelligenceThe ability to create, communicate with, and understand meanings made of sound, understanding of pitch, rhythm.Musicians, Singers, Composers
Logical-mathematical intelligenceThe ability of use and understand relationships in the absence of action or objects. Understanding complex and abstract ideas.Mathematicians, Scientists
Spatial intelligenceThe ability to perceive visual or spatial information, change it, and re-create visual images without reference to the objects, construct 3D images, and to move and rotate them.Map readers, Astronauts, Physicists
Bodily-Kinesthetic intelligenceThe ability to use complete or part of the body to solve problems or fashion products, control over fine and coarse motor skills, and manipulate the objects.Players, Dancers
Intra-personal intelligenceThe ability to distinguish among one’s own feelings, intentions, and motivations.Gautam Buddhha
Interpersonal intelligenceThe ability to recognize and make distinctions among other people’s feelings, beliefs, and intentions.Mass Communicators, Interviewers


You can say a machine or a system is artificially intelligent when it is equipped with at least one and at most all intelligences in it.


What is Intelligence Composed of?

The intelligence is intangible. It is composed of ?

  • Reasoning
  • Learning
  • Problem Solving
  • Perception
  • Linguistic Intelligence

Let us go through all the components briefly ?

  • Reasoning ? It is the set of processes that enables us to provide basis for judgement, making decisions, and prediction. There are broadly two types ?
Inductive ReasoningDeductive Reasoning
It conducts specific observations to makes broad general statements.It starts with a general statement and examines the possibilities to reach a specific, logical conclusion.
Even if all of the premises are true in a statement, inductive reasoning allows for the conclusion to be false.If something is true of a class of things in general, it is also true for all members of that class.
Example ? "Nita is a teacher. All teachers are studious. Therefore, Nita is studious."Example ? "All women of age above 60 years are grandmothers. Shalini is 65 years. Therefore, Shalini is a grandmother."
  • Learning ? It is the activity of gaining knowledge or skill by studying, practising, being taught, or experiencing something. Learning enhances the awareness of the subjects of the study.

The ability of learning is possessed by humans, some animals, and AI-enabled systems. Learning is categorized as ?

  • Auditory Learning ? It is learning by listening and hearing. For example, students listening to recorded audio lectures.
  • Episodic Learning ? To learn by remembering sequences of events that one has witnessed or experienced. This is linear and orderly.
  • Motor Learning ? It is learning by precise movement of muscles. For example, picking objects, Writing, etc.
  • Observational Learning ? To learn by watching and imitating others. For example, child tries to learn by mimicking her parent.
  • Perceptual Learning ? It is learning to recognize stimuli that one has seen before. For example, identifying and classifying objects and situations.
  • Relational Learning ? It involves learning to differentiate among various stimuli on the basis of relational properties, rather than absolute properties. For Example, Adding ‘little less’ salt at the time of cooking potatoes that came up salty last time, when cooked with adding say a tablespoon of salt.
  • Spatial Learning ? It is learning through visual stimuli such as images, colors, maps, etc. For Example, A person can create roadmap in mind before actually following the road.
  • Stimulus-Response Learning ? It is learning to perform a particular behavior when a certain stimulus is present. For example, a dog raises its ear on hearing doorbell.
  • Problem Solving ? It is the process in which one perceives and tries to arrive at a desired solution from a present situation by taking some path, which is blocked by known or unknown hurdles.

Problem solving also includes decision making, which is the process of selecting the best suitable alternative out of multiple alternatives to reach the desired goal are available.

  • Perception ? It is the process of acquiring, interpreting, selecting, and organizing sensory information.

Perception presumes sensing. In humans, perception is aided by sensory organs. In the domain of AI, perception mechanism puts the data acquired by the sensors together in a meaningful manner.

  • Linguistic Intelligence ? It is one’s ability to use, comprehend, speak, and write the verbal and written language. It is important in interpersonal communication.


Difference between Human and Machine Intelligence

  • Humans perceive by patterns whereas the machines perceive by set of rules and data.
  • Humans store and recall information by patterns, machines do it by searching algorithms. For example, the number 40404040 is easy to remember, store, and recall as its pattern is simple.
  • Humans can figure out the complete object even if some part of it is missing or distorted; whereas the machines cannot do it correctly.


Most AI solutions today are fielded by the big players in IT.  For example, Apple's Siri or the capabilities they embedded directly in iOS9, or Google's many savvy search solutions or Amazon's very smart recommendations.  Amazon's Echo is also, like Siri, connecting to a very smart cloud capability that takes advantage of AI. AI capabilities are also being programmed into robotic solutions including self driving cars. IBM is also investing heavily in AI, with Watson the most famous result.

Here is a short list of capabilities we recommend all enterprise technologists track. The list is by no means comprehensive, but is definitely representative of what is available now:

Artificial Intelligence On Your Phone:

  • Siri: Part of Apple's iOS, watchOS and tvOS. Intelligent personal assistant.
  • Cortana: Microsoft's intelligent personal assistant. Designed for Windows mobile but now on Android and a limited version runs on Apple iOS. Also works on desktops and Xbox One.
  • Google Now: Available within Google Search mobile app for Android and iOS as well as the Google Chrome web browser on other devices. Delegates requests to web services powered by Google.

Artificial Intelligence From The Cloud:

Really most all of the AI on your phone and desktops is communicating with cloud services, so keep in mind most solutions are a blend that highly leverage cloud capabilities. But we needed a place to talk about Echo and Watson and soon many others, so:

  • Watson: A technology platform that uses natural language processing and machine learning to reveal insights from large amounts of data.
  • Echo: The device you buy is mostly a speaker and microphone with some commodity IT to connect it to the cloud. The real smarts come from Amazon Web Services.

For Personal and Business Use:

  • Gluru: Organize your online documents, calendars, emails and other data and have AI present you with new insights and actionable information.
  • ai: Let AI coordinate schedules for you. Your own personal scheduler.
  • CrystalKnows: Using AI to help you know the best way to communicate with others.
  • RecordedFuture: Leverages natural language processing at massive scale in real time to collect and understand over 700,000 web sources to seek understanding.
  • Tamr: Unique approaches to Big Data leveraging machine learning.
  • LegalRobot: Automating legal document review in ways that can serve people and businesses.
  • Intraspexion: Uses Deep Learning as the core of an early warning system to investigate and prevent potential litigation.
  • EverLaw: The power of mobile, machine learning and cloud computing delivered as a SaaS.

Artificial Intelligence For Developers:

  • Vicarious: Building the next generation of AI algorithms.
  • Soar is a general cognitive architecture for developing systems that exhibit intelligent behavior.
  • io is a service with easy to use, open templates for a variety of advanced AI workloads.
  • Jade: Java Agent Development Framework. Simplifies multi-agent system development.
  • Protege: A free, open-source ontology editor and framework for building intelligent systems.
  • ai: Build smarter machine learning/AI applications that are fast and scalable.
  • Seldon: An open, enterprise-grade machine learning platform that adds intelligence to organizations.
  • SigOpt: Run experiments and make better products with less trial and error.
  • Scaled Inference: Cloud based models and an inference engine to help in model selection.
  • OpenCV: Open source computer vision, a library of programming functions aimed mainly at computer vision.

Artificial Intelligence For Healthcare:

  • Enlitic: Deep learning for healthcare and data driven medicine.
  • io: Automatic image recognition with many use cases, including medicine.
  • Zebra Medical Vision: Closing the gaps between research and result for patients with data and AI.
  • Deep Genomics: Machine learning and AI transforming precision medicine, genetic testing, diagnostics and therapies.
  • Atomwise: Using AI and analytics to predict medicines and discover drugs.
  • com: AI and Machine Learning delivering insights on treatments.

Artificial Intelligence For Robotics:

  • net: Building flying vehicles powered by intelligent software.
  • Skycatch: Software for fully autonomous aerial systems.
  • IdentifiedTech: Industrial mapping drone automation.

Artificial Intelligence For Space:

  • SpaceKnow: Using AI to track global economic trends from Space.
  • OrbitalInsight: Space trends for understanding global issues.

Artificial Intelligence For Marketing and Customer Interaction:

  • DigitalGenius: Computer driven conversation with customers in ways that scale and serve.
  • Conversica: AI to help you find your next customer, including automated email conversations to qualify leads.

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