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Artificial Intelligence

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14 Apr 2017CPOL4 min read 25K   15  
Exploring the concepts of Artificial Intelligence

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Introduction

Industry is heavily spelling a term called AI (Artificial Intelligence). Let us spend couple of minutes to explore this emerging technology, quickly.

Definition

In simple terms, AI is part of a computing principle to simulate the human behavior intelligently.

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

Journey

During early 1990s, I studied AI paper in my graduation. It was forced to leave in elective category due to its science fiction characteristics. Now, AI is part of today's consumer world like driverless car, online shopping prediction/recommendation, etc.

On analyzing the industry history, Karel initiated this computing with the concept named "Robot" on 1923. Hmm.. almost a century ago. Issac continued with the introduction of Robotics on 1945. John McCarthy is called as Father of AI due to his enormous contribution during late 1950s. He not only coined AI but also invented LISP programming.

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Rest of the history with key milestone is explained in the above Timeline image.

Ecosystem of AI

AI ecosystem is built using not only Science but also Art. In general, Art and Science differs with key principle that Art is subjective; Science is objective. AI is combination of Science - Maths, Biology and Computers and of Art - Psychology, Philosophy, Sociology. It has been represented in the below ecosystem diagram:

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Artificial Intelligence is the foundation of Machine Learning, Statistics and Data Mining, chronologically. The below diagram depicts the connecting dots of the above said four platforms.

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In simple term, AI (Artificial Intelligence) is the superset of all paradigm.

Core Intelligence

As AI is highly associated with human intelligence such as reasoning, learning and problem solving, it should be appropriate to learn the concepts of Core Intelligence.

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Intangible intelligence comprises of Linguistic Intelligence, Problem Solving, Perception, Reasoning and Learning.

  • Linguistic Intelligence: Ability to use, comprehend, speak, and write the verbal and written language. Problem
  • Solving: Decision making process to select the best suitable alternative.
  • Perception: Process of acquiring, interpreting, selecting, and organizing sensory information.
  • Reasoning: Set of processes to provide the conclusion basis for judgment, making decisions, and prediction.
  • Learning: Activity of gaining knowledge or skill by studying, practicing, being taught, or experiencing something.

Industry Application

Fundamentally, technology needs to enable the business. In this perspective, AI has been dominant in various fields of the end customers, as below:

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  • Prescriptive Analytic: Best example is online shopping auto recommendations. Based on the customer behavior, App suggests the suitable products intelligently to achieve Win-Win situation for Business and Customer.
  • Gaming: AI helps to simulate Chess Expert for the competition with human champion. This design is based on heuristic knowledge.
  • NLP (Natural Language Process): Capability to interact with the computer that understands natural language spoken by humans.
  • Voice Recognition: Capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. Intelligent interactive Chat Bot is the best use case in the current world.
  • Robots: Robots are aimed to perform the manual efforts of human being. By doing so, it reduces/supports the human work. Robots are constructed using the relevant sensors, processors, memory to exhibit intelligence. Nowadays, manufacturing (car) industry is leveraging Robot culture for better productivity and error prone output.

Industry Adaptation

Intelligence is the ability to adapt to change. As Intelligence is part of AI term, it is interesting to observe the industry movement towards AI. Few scorecard speaks about it. Interestingly, there are around 46% of AI companies acquired, since 2012 have had VC backing.

On tracking last 5 years of major merger & acquiring activities, the industry trend is pretty clear.

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The above chart depicts about AI Merger and Acquisition based on every quarter at IT industry, since Q1 2012. In the similar line, top acquirers of AI startups are tabulated in the below timeline chart.

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It clearly indicates that every major player (you name) like Google, Apple, Facebook, Intel, Microsoft, Amazon, Yahoo, IBM, Oracle, Ford, Twitter, GE, etc. are actively participating in AI aggressive adoption at their space.

Points of Interest

As the closing note, human beings are always superior than computers. By design, humans perceive by patterns whereas the machines perceive by set of rules and data.

History

  • 15th April, 2017: Initial version

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


Written By
Architect
India India
Ganesan Senthilvel is a passionate IT leader with demonstrated 2 decades’ experience in architecture, design and implementing cutting edge solutions to address business opportunities of Enterprise applications. He earned Masters in Computer Science and Master in Business Administration. Now, he is pursing Doctorate program in Big Data. He is consistent technical contributor via COE, Blog, Whitepaper, Summit, Certification, etc. and also highly skilled at providing coaching and mentoring to internal teams and external institutes. Earned Microsoft Certifications like MCP, MCAD and financial domain certification.
He maintains his weekly blog at http://ganesansenthilvel.blogspot.in

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