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Artificial Intelligence
Introduction: *`*`*`*`*`*`*`*`*`*`*
This is an ironic twist in terminology. The term "intelligence" refers to processing capability; therefore, every computer is intelligent. However, artificial intelligence implies human-like intelligence.
Possibly we can say that it means “non-natural understanding”.
Artificial intelligence in some sense is engineering inspired by biology. It is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion.
In AI, an "intelligent system" is one that exhibits behaviors normally associated with human intelligence.
Definition: *`*`*`*`*`*`*`*`* Defining "intelligence" in a computer system can be problematic since intelligence can be defined as something that humans possess and computers do not. In AI, however, an "intelligent system" is one that exhibits behaviors normally associated with human intelligence. Systems that perform complex diagnostic procedures and pattern matching are considered intelligent.
Artificial intelligence (AI) is a branch of computer science and engineering that deals with intelligent behavior, learning, and adaptation in machines.
The ability of a computer or other machine to perform those activities that are normally thought to require intelligence and which brings common sense, expert knowledge, and superhuman reasoning to computers.
Schools of thought: *`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`* AI divides roughly into two schools of thought: Conventional AI and Computational Intelligence (CI), also sometimes referred to as Synthetic Intelligence to highlight the differences.
Conventional AI: *`*`*`*`*`*`*`*`*`*`*`*`*`*`* This mostly involves methods which are now classified as machine learning, characterized by formalism and statistical analysis. This is also known symbolic AI, logical AI, neat AI and Good Old Fashioned Artificial Intelligence (GOFAI).
Methods include:
Expert systems: apply reasoning capabilities to reach a conclusion. An expert system can process large amounts of known information and provide conclusions based on them. Case based reasoning Bayesian networks Behavior based AI: a modular method of building AI systems by hand
Computational Intelligence: *`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`* This involves iterative development or learning (e.g. parameter tuning e.g. in connectionist systems). Learning is based on empirical data and is associated with non-symbolic AI, scruffy AI and soft computing.
Methods mainly include:
Neural networks: systems with very strong pattern recognizing capabilities. Fuzzy systems: techniques for reasoning under uncertainity, have been widely used in modern industrial and consumer product control system. Evolutionary computation: applies biologically inspired concepts such as populations, mutation and survival of the fittest to generate increasingly better solutions to the problem. These methods most notably divide into evolutionary algorithms (e.g. genetic algorithms) and swarm intelligence (e.g. ant algorithms)
History of Artificial intelligence: *`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`* Humans have always speculated about the nature of mind, thought, and language, and searched for discrete representations of their knowledge.
1960s-1970s: *`*`*`*`*`*`*`*`*`*`*`*`* During the 1960s and 1970s, Joel Moses demonstrated the power of symbolic reasoning for integration problems in the Macsyma program which is the first successful knowledge-based program in mathematics. Leonard Uhr and Charles Vossler published "A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators" in 1963, which described one of the first machine learning programs that could adaptively acquire and modify features and thereby overcome the limitations of simple perceptrons of Rosenblatt. Marvin Minsky and Seymour Papert published Perceptrons , which demonstrated the limits of simple neural nets. Alain Colmerauer developed the Prolog computer language. Ted Shortliffe demonstrated the power of rule-based systems for knowledge representation and inference in medical diagnosis and therapy in what is sometimes called the first expert system. Hans Moravec developed the first computer-controlled vehicle to autonomously negotiate cluttered obstacle courses.
1980s: *`*`*`*`*`*`* 1980s: Lisp machines developed and marketed. First expert system shells and commercial applications. In the 1980s, neural networks became widely used due to the backpropagation algorithm. The team of Ernst Dickmanns built the first robot cars, driving up to 55 mph on empty streets. Rodney Brooks introduced the subsumption architecture and behavior-based robotics as a more minimalist modular model of natural intelligence in 1987.
1990s and Turn of Century: *`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`* During the 1990s and 2000s AI has become very influenced by probability theory and statistics. Bayesian networks are the focus of this movement, providing links to more rigorous topics in statistics and engineering such as Markov models and Kalman filters, and bridging the divide between neat' andscruffy' approaches.
The last few years have also seen a big interest in game theory applied to AI decision making. This new school of AI is sometimes called `machine learning'. After the September 11, 2001 attacks there has been much renewed interest and funding for threat-detection AI systems, including machine vision research and data-mining.
Tasks Domains of AI: *`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`* Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior.
The tasks in which carefully acquired expertise is necessary. These targets of work in AI include:
Mundane Tasks: *`*`*`*`*`*`*`*`*`*`*`*`*`* Perception Vision Speech Natural language Understanding Generation Translation Commonsense reasoning Robot control Formal Tasks: *`*`*`*`*`*`*`*`*`*`*`*`* Games Chess Checkers Go Mathematics Geometry Logic Integral calculus Proving properties of programs
eventually treating them as equal team members in the chase to clarify ethics.
But some authorities in the relevant fields have raised concerns that machines will take over the world in the next 10-30 years. It will then discuss what we can do to ensure that machines will behave in a constructional way.
"I am afraid that the long term future we are building will have no space left for human beings,” says Daniela Cerqui, a social and cultural anthropologist at the Institute of Sociology and Anthropology of the University of Lausanne.” I definitely do not like the idea of robots replacing human beings."
The Expectations: *`*`*`*`*`*`*`*`*`*`*`*`*`*`*`* These are some of the expectations and opinions which some of the people concerned with artificial intelligence hold:
Joanne Pransky, who has been involved in robotics for twenty years and calls herself the Worlds First Robotic Psychiatrist says that:
"Most of us would rather be attended to in a hospital by a robot than be ignored and given the choice to stay in our own homes with a nursebot or go to a nursing home, a robot would allow us to continue to live independently as well as offer a more cost-effective alternative."
Ray Kurzweil envisions a future where there are no sharp distinctions between human and machine.
"You're not going to be able to walk into a room in 2035 and say humans on the left side of the room, machines on the right. You'll have a hard time finding a human who doesn't have extensive amounts of technology inside them in the form of nanobots and other systems that are keeping them healthy and also extending their range of experiences and their intelligence."
Bob Christopher, the CEO of UGOBE, a robotic technology company says that:
"The advances in robotics make it clear that many household chores will be easily handled by a robot in the near future"
The Future of Artificial intelligence: *`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*`*
Even the most advanced neuroscientist would admit that the brain is unbelievably complicated and we are scratching the surface and really understanding what’s going on inside the brain.
Many scientists remain doubtful that true AI can ever be developed. The operation of human mind is still little understood, and computer design may remain incapable of copying the complex processes.
But still new ways and ideas are emerging to achieve true artificial intelligence.
Says Donoghue, a neuroscientist, that:
“Recreating the connections between the brain and the body may sound like science fiction, but its just the beginning. We are working on recreating an artificial nervous system, We are working on ways that will transform the electrical impulses of the brain into light, and that, that light will then be used as an artificial nervous system using fiber optics to transmit that information to the muscles. Then converted back into electrical stimulation where it can stimulate the arm and we'll re-animate the limb."
These machines are being developed. What will be the ultimate effect of this? Should they be allowed to make decisions regarding the application of lethal force? What form and how intimate should human-robot relationships become? Is it a good or bad thing if robots become our natural successors and we fade into extinction?
Time will answer all these questions!
