Artificial intelligence is one of the many ultramodern technological concepts that promise to revolutionize the human and microprocessor mutual interaction. A.I. will mark the arrival of fifth generation computing. The children of tomorrow can have pets and toys with a semiconductor heart and brain that may prove to be the characters of their unrestrained imagination coming to life. In actual sense, Artificial Intelligence is incorporating human like intelligence into machines made up of semiconductor brains. With the development of a successful A.I. we would be able to fuse the mechanical power and astounding abilities of machines with the innumerable capabilities of mortals.A perfect creature would be manufactured with the ability of machines to work continuously without any physical or mental fatigue and with utmost accuracy in addition to the abilities of humans to make decisions according to the situation like an emergency. Also the great power of creativity vested with humans would be incorporated into an electrically powered living thing. Now just imagine the capabilities of such a product of technology. The possibility of a robot basically made up of non-living material achieving sentience, that is, intelligence with the capacity for emotional development, is a hot philosophical subject. Humans have an exceptional tendency to invest a variety of emotions in inanimate objects such as cars, houses and so on, but experts in artificial life believe the capabilities of "conscious" robots will be too limited for them to ever offer a substitute for human friendship. Robots with A.I. in central instructing unit will surely arrive to change many things of routine life.

Efforts in this direction of technology have commenced since the last decade and there have been certain cases of success, but the ultimate thing is still far to reach. The extensive research in the field of Artificial Intelligence applications in all the parts of the world gained importance with the Japanese announcement in 1981 that they were going to build a fifth generation computer that would be capable of logic deduction, etc.
Even though the Japanese 5th generation project failed due to some inherent problems that are always there with A.I., the research still continued around the globe to integrate more intelligent computer systems. Emphatic generals foresaw battle by hordes of entirely autonomous buggies and aerial vehicles, robots that would have multiple goals and whose mission may last for months, driving deep into enemy territory. The problems in developing such systems are obvious - the lack of functional machine vision systems has lead to problems with object avoidance, friend/foe recognition, target acquisition and much more. Problems also occur trying to get the robot to adapt to its surroundings, the terrain, and other environmental aspects.

In the present situation, developers seem to be more concentrated on trivial goals, such as voice recognition systems, expert systems, system safety softwares, script and language transition programs and text to audio conversion programs to help the physically challenged and other advisory systems. There are also developers in the field who are working with the intention to reduce the workload on a pilot and other important military officials and civil servants. Modern pilots work in incredibly complex electronic environments - receiving information not only from their own radar, but from many others. The aircraft of the third millennium have highly complex avionics, navigation, communications and weapon systems. All this must be organized in a highly accessible way. Through voice-recognition, systems could be checked, modified and altered without the pilot looking down into the cockpit. Expert and advisory systems could predict what the pilot would want in a given scenario and decrease the complexity of a given task automatically. The modern weaponry is powered by some brilliantly developed A.I.'s that can make a weapon more and more target specific. The Evolutionary Algorithm could be actually programmed into the weapon systems, so that the system could dynamically adapt to the terrain, and other mission-specific parameters. We will discuss the EA later in the article. Many of the computer games have an A.I. engine or software that is designed for the way the computer should act at a user generated event. Games like chess and other board games have a very hi-tech A.I. that act very intelligently at every user move, but the thinking capability of these A.I.'s is diminutive when compared to that required by the Robots so that they can make decisions as we humans as per the situation, emergency or in any other case. The CAIR, India's very own A.I. research facility at Bangalore have developed a few technologies and software's that can help design A.I. for some specific cases. The following is a brief description of them -

nipuNa is an expert system shell developed. It has some novel features, not present in the commercially available shells. It provides an inference strategy that discovers all the goals that are logical consequences of the rules and the observations. The tool has been designed to be used for developing embedded expert systems. It provides a user friendly development environment.
The knowledge representation scheme used in nipuNa is the "if … then … " format and is not restricted to Horn rules. A hypertext-based cross-referencing mechanism is provided for querying the knowledge base during the development phase. This helps in writing rules and integrating them into the knowledge base. On-line help is provided with the tool for all the features. nipuNa has been developed in a PC version (nipuNa-PC) as well as a workstation version (nipuNa-WS).

Pilot Associate Kernel - In many engineering systems, information is processed in a concurrent and hierarchical manner. At the lowest level of the system, a large number of data processing tasks collect data from the physical system. After processing the data, any significant change in the parameters of interest is reported to the next level of the hierarchy of the event. After receiving events, some event-handler tasks are initiated. Such event-handlers take autonomous actions whenever possible, else they generate either events to be processed by the immediate higher level or requests (for more data) from the immediate lower level. This way, only those events requiring human intervention reach the top of the hierarchy. The Pilot Associate Kernel is a toolbox for developing such concurrent hierarchical applications with real-time constraints. It provides features for event based programming in a multitasking environment. It also provides methods for control, communication and synchronisation between tasks.

Intelligent Warning Manager - An Intelligent Warning Manager has been developed to manage and display warnings to the aircraft pilots. The warning manager reasons with the set of warnings and displays only those that are important to the pilot based on the warning knowledge provided to the warning manager.

They are working hard towards the goal of building a successful fifth generation computer. You can know more about their work and contribution towards the fifth generation technologies from there website.

The major reason of big developed countries like UK and US to invest a lot of money for the research of the 5th generation technologies is to strengthen their military powers. Even the research is carried out with military applications in focus. The applications of AI in the military are wide and varied, yet due to the robustness, reliability, and durability required for most military programs and hardware, AI is not yet an integral part of the battlefield. Various paradigms in A.I. have been successfully applied in the military field. For example, using an EA - Evolutionary Algorithm to evolve algorithms to detect targets given radar/FLIR(Forward-Looking Infra-red) data, or neural networks differentiating between mines and rocks given sonar data in a submarine. There is detailed description of the two examples of Evolutionary Algorithm in depth as follows. The source of following information regarding the examples of EA are abridged from an article of the website Generation5.

Genetic Programming is an excellent way of evolving algorithms that will map data to a given result when no set formula is known. Normally mathematicians and programmers could write or develop algorithms to deal with a problem containing 5 or so variables, but problem arises when this value of 5 goes up to 10, 20 or may be 50. Then the problem becomes nearly impossible to solve. Now comes the role of GP(Genetic Programming). A GP-powered program creates a series of randomly generated expression trees that represent various formulas thus simplifying the algorithm. Then a test is carried out amongst the expression trees and the data. Herein the poor trees are discarded and the best ones are kept and breed. Now these trees are mutated, crossed-over and all the elements in the genetic algorithms are used to breed the 'highest-fitness' tree for the given problem. The best output of these will be a perfectly match amidst the variable and answer. At other times it will generate an answer very close to the wanted answer.

A notable example of such a program is SDI's 'e' evolutionary algorithm designed by Steve Smith. 'e' has been used by SDI to research algorithms to use in radars in modern helicopters such as the AH-64D Longbow Apache and RAH-66 Comanche. 'e' is presented with a mass of numbers generated by a radar and perhaps a low-resolution television camera, or FLIR device. The program designed by him then attempts to find (through various evolutionary means) an algorithm to determine the type of vehicle, or to differentiate between an actual target and mere "noisy" data. Basically, the EA is fed with a list of 42 different variables collected from the two sensors, and then a truth-value specifying whether the test data was clutter or a target. The EA then generates a series of expression trees (much more complicated than those normally used in GP programs). When a new best program is discovered, the EA uses a hill-climbing technique to get the best possible result out of the new tree. Then, the tree is subjected to a heuristic search to optimize the tree. Once the best possible tree is found, he will output the program as either pseudocode, C, Fortran or Basic. Once the EA had evolved the training data, it was put to work on some test data. The results were quite impressive with the training data, but the performance was poignant when applied to test data. Nevertheless, the fused detection algorithm (using both radar and FLIR information) still provided a decent error percentage.

Another outstanding technique of evolving algorithms that will map data to the results is Neural Networks (NN). A NN is normally pre-trained with a set of input vectors and a 'teacher' to tell them what the output should be for the given input. A NN can then adapt to a series of patterns. Thus, when fed with information after being trained, the NN will output the result whose trained input most closely resembles the input being tested. This method actually reduces the capacity of producing results in various unprecedented situations. Some of the scientists adapted this method to identify sonar sounds. Their goal was to train a network to differentiate between rocks and mines - a notoriously difficult task for human sonar operators to accomplish.

The network architecture was quite simple; it had 60 inputs, one hidden layer with 1-24 inputs, and two output units. The output would be [0,1] for a rock and [1,0] for a mine. The large amount of input units was to incorporate 60 normalized energy levels of frequency bands in the sonar echo. What this means is that a sonar echo would be detected, and subsequently fed into a frequency analyzer, that would breakdown the echo into 60 frequency bands. The various energy levels of these bands was measured, and converted into a number between 0 and 1.A few simple training method was used (gradient-descent), as the network was fed examples of mine echoes and rock echoes. After the network had made its classifications, it was then told whether it was correct or not. Soon, the network could differentiate as good or better than its equivalent human operator. The network had also beaten standard data classification techniques. Data classification programs could successfully detect mines 50% of the time by using parameters such as the frequency bandwidth, onset time, and rate of decay of the signals. Unfortunately, the remaining 50% of sonar echoes do not always follow the rather strict heuristics that the data classification used. The networks power came in its ability to focus on the more subtle traits of the signal, and use them to differentiate. To conclude the military applications of A.I., I would quote a sentence from an article at Generation5 - "As techniques are refined and improved, more and more AI applications will filter into the war scene - after all, silicon is cheaper than a human life."

A.I. finds a major relevance in building the robots that can do anything and everything perfectly. There are great expectations from these metal friends whenever they come to action. All of us are pretty obsessed with the things shown in Hollywood movies and want all of the fantasies of Holly flick writers to come to life. But, science has something dissimilar to say. According to Kevin Warwick's research, robots with brain processing capabilities are no more intelligent than snails or bees, with basic behavior patterns and the ability to map out simple environments. "Humans have human emotions and robots have robot emotions. As soon as you allow robots to learn, you are opening up the possibility that they could develop their own emotions." Sony's AIBO robot pooch, developed in 1999, proved that robots can learn how to interact with humans using limited intelligence and play a part in their daily lives, albeit at a rudimentary level. The AIBO has learning ability and the capacity to mature. It is not designed for a servile role, but rather to fulfill a "useful" purpose, primarily that of companionship. AIBO had been designed to be a friend for the older people of our fast paced and timeless society and for those who are in a psychological state of loneliness. Ironically, Sony's extensive research into developing the world's first intelligent companion may have overestimated man's need for a chum endowed with brains. The emergence of seemingly "useless" artificial pets like Tamagotchis or Furbies confirmed that a relationship between people and robotic creatures is possible, even if the robot is little more than a key ring or stuffed toy with a dozen predefined functions.

Nigel Shadbolt, professor of artificial intelligence at the University of Southampton is unconvinced about the role robots will play in our lives. "I can imagine robots becoming companions, but we are a long way from producing robots with the same behavior and intelligence as pets". Shadbolt is skeptical about robots ever fulfilling more than a proxy role in social situations. The hypothetical nature of sentience debates leads experts such as Dr Murray Shanahan, senior lecturer in electrical engineering at Imperial College, to completely reject the possibility of artificial pets ever possessing human emotions or responses. According to him, sentience is a rather high-vaulting word to describe the kind of robots that we could have in the near future. It is not appropriate to think of robots as being tied up with human biological heritage, as we're not aiming to put things that matter in robots. Cybernetics experts seem unwilling to talk about the prospect of building "conscious" robots capable of experiencing pleasure or pain, as they would then be responsible for the way in which they are treated. Shanahan is adamant that robots, particularly those with sophisticated 'thought' functions, must perform a completely servile role. "I would not want to build such things where there was a moral issue involved...We're designing these things and we need to engineer them in a way that [ensures] robots never move beyond what they are programmed to do."

All these systems are quite impressive, and perfected models could provide incredible assets to the human race. Artificial Intelligence may only get developed to a certain level due to the threat humans feel, as computers get more and more intelligent. The concepts behind movies such as Terminator where our robotic military technology backfires on us and destroys us are rampant. Hollywood fantasies of destruction of human race by A.I. enabled metal demons can become the dark reality of the future. None of us, not even the scientists who are working hard towards the development of A.I. are sure of what would be the reaction of an A.I. enabled machine. How would a machine react when humans empower it with the capability of thinking and deciding as humans? Would it be the Ram or the Ravana - would it be the Krishna or the Kansa - would it be the Good or the Evil. As I conclude these are the moral issues that we must confront as artificial intelligence develops.