He was desperate to find her when he was abandoned by the mother despite her love towards the boy due to social phenomena. Think for a minute. Am I describing a real scenario that happened between a human son and a mother or can you recall some story which had the same resemblance? Yeah, you are right. I was just giving a short description of Steven Spielberg’s film “Artificial Intelligence”. So, David was actually a humanoid robot boy with emotions such as love as well as a certain level of intelligence fed in to his systems to be able to appear quite similar to a human boy. So what is Artificial Intelligence (AI)? It has been a question which was answered in many different ways based on the emphasis of the era that was being considered. First it was termed to describe machines which act as humans. There were other definitions such as machines ‘acting rationally’ (doing the right thing to suit the situation and problem in hand), ‘thinking rationally’ and ‘thinking humanly’.
The first research which can be considered as to be in-line with AI was done by Warren McCullouch and Walter Pitts in 1943 They proposed a model of neurons (as the ones which are in a human brain) in an artificial manner to represent neural properties. They also suggested that with the use of many such neurons combined as in a network could be used to model logical connectives such as AND, OR, NOT. Another important point that they suggested was that given the necessary data such neural networks could learn which is one of the early births of learning techniques to be suggested which later improved to neural network based learning in greater scale. In 1949 Donald Hebb was successful in introducing a simple updating rule so that the neural network connections which were used to connect each of the neurons to their neighboring neurons could be updated. It was known as “Hebbian Rule” which is even used in neural network learning at the simplest level nowadays. Princeton university graduate students, Marvin Minsky and Dean Edmonds started working on the neural network computer in 1951 which was called as SNARC. It is said that although the above mentioned research had resemblances of Artificial Intelligence, Alan Turing was the first to introduce the whole concept of AI with the an article named “Computing Machinery and Intelligence” in which he introduced the famous Turing test and other AI concepts such as Machine Learning, genetic algorithms and reinforcement learning to the world.
The coining of the name “Artificial Intelligence” was done at the Dartmouth conference held in 1956 which consisted of many US researchers of the era such as Allen Newell, Herbert Simon, John McCarthy and Marvin Minsky. It was proposed my John McCarthy to name the field of machines being able to simulate or act with intelligence as “Artificial Intelligence” which was since then called by that name irrespective of whether that term precisely depicts the area in concern.
The time period after the Dartmouth conference, many researches came up with computer programs to address AI aspects, within the limited computational power and tools available at that time. In 1957 Newell and Simon created a computer program called “General Problem Solver” which was intended to act as a universal problem solver for problems which can be formulated in to symbolic representations. But this was not able to handle real world problems other than defined problems such as chess games, theorem proving, towers of Hanoi, etc. Many such problem solving programs such as ‘Geometry Theorem Prover’ by Herbert Gelertner(1959), Program for playing checkers by Samuel(1952-1956) followed. LISP, a high level programming language specifically to cater to the AI domain was introduced by McCarthy in 1958 making a great breakthrough to the future of Artificial Intelligence. The next major aspect which was introduced was the concept of Knowledge-based systems. In the mean time, researches started thinking in the line of how humans gain intelligence through learning from the knowledge they gather. This gave rise to the development of Knowledge based systems, one of the first main such systems being the DENDRAL program by Buchanan and fellow researchers in 1969 in order to solve the problem of inferring molecular structures. Another system that was developed for diagnosing blood infections was called MYCIN and was quite successful in its task even sometimes better than human experts showing that the area of research is promising. AI based expert systems and knowledge based systems was used for industrial purposes as well for some time but it the systems lacked long term prospects. AI was developed and continued as a Science where new areas of research coming in to the scene. Neural networks were given more importance and research was carried out further since 1986. Speech recognition, Linguistics, Data mining, Machine learning, Pattern classification, clustering, and many more areas were interlinked to AI and was starting to boom.
AI is a vast subject where many other disciplines are intermingled. Mathematics, Logic, Medicine, Genetics, Philosophy, Economics, Psychology, Cognitive Sciences, Computer Science, Computer Engineering, Robotics and Linguistics are some of the other subject areas which foster the research in AI and also whom which get improved from AI’s contributions. For example, most of the AI programs are based on foundations in Mathematics and logic. Further areas such as medical diagnosis, robots for surgeries have been developed to assist the human medical practitioners to provide a better service to the patients. Projects such as identifying human genomes, DNA classifications have benefited from the AI related experiments such as pattern classifications, clustering, etc. This shows that AI has a strong bond between lots of other disciplines which make the subject having lots of research to be carried out in a vast number of lines. This makes the evolving of AI to be wider but slower compared to other scientific subjects. Nevertheless, as the various contributions in all these domains help make the life of mankind better and more easier, so that the bond among these interlinked subjects remain while researches find means of strengthening it further in the future with many other findings.
For a general person what would AI mean? He would not care whether it is an advanced interrelated subject or not. You and I should have some benefit for us to believe and identify the importance of AI. Therefore, let’s look at how AI has approached our lives in practice. Have you encountered when you are browsing the internet to buy something, some sites recommend you products to buy based on your past buying trends and likings? Do you know that you can even delegate the task of ordering your weekly grocery goods online to a computer agent? Yes, you can. All these are enabled due to the existence of intelligent software agent systems which can act rationally and perform the task given, which is a part of AI. Further, have you heard of robot pets that are used to behave like actual pets in giving total love and caring to the elderly people in Japan? There are medical testing devices, which enables the lab technicians as well as the medical practitioners to easily diagnose an illness of a patient and also prescribe required drugs or treatments accurately with the help of AI. Nowadays there are even programs which can automatically generate and compose music and programs and which can select music to play based on the rhythm of walking (enabled using wireless communication between your music player and a device placed in your shoe as you are walking).
For sure, you must have heard about the world renowned chess master Gary Kasparov being defeated against a chess game from his opponent “Deep Blue” an intelligent chess playing machine developed by IBM in 1997. Gaming is another area where AI related concepts could be applied to build computers to play different games that can play against human or other computer players effectively. The above are only a very few of the applications of AI which a general user would be able to witness as at resent.
There is yet more to tell, yet more to find, yet more to explore in this vast and exciting field of Artificial Intelligence. The specific details and technical aspects of the various areas in AI would be covered in the articles to follow in the months to come, giving you a better feeling of Artificial Intelligence and to create wonder, interest and enthusiasm in this field.