Artificial intelligence is the branch of computer science. Artificial intelligence is the art of creating computer softwares or machines as intelligent as the humans.
What's the meaning of AI :
John McCarthy who is the father of Artificial intelligence says that, " Artificial intelligence Science & engineering of making intelligent machines especially intelligent computer programmes".
- Artificial intelligence is accomplished by studying how human brain thinks and how human brain learn,decide and work while trying to solve problems,then using outcomes of this study as basis of developing intelligent softwares and systems.
- AI is the development of computer systems that are able to perform tasks that would require human intelligence.
- Real life examples of AI are self driving cars, Boston dynamics, navigation systems, ASIMO, chatbots, human Vs computer games. etc,
Can machines think & behave like humans?
Artificial intelligence is,
" Thinking humanly
Thinking rationally
Acting humanly
Acting rationally "
Goals of AI :
- AI started with intension of creating similar intelligence in machines that we find and regard high in humans.
- AI is started to create the expert systems. These Intelligent systems an advice the users.
- To implement the human intelligence in the machines. This is technology any how humans how can work, how can think, how can behave, how can solve problems is applied to the machines and designing the machines to solve problems like humans, mostly difficult problems which are unsolvable to humans.
Contribution to AI :
AI is the science and technology based on disciplines such as computer science, Biology, psychology, linguistic, maths and engineering. The major thrust of it is development of the computer functions associated with human intelligence such as reasoning, learning and problem solving.
How AI technique works?
It is manner to organize and use the knowledge efficiently. About the knowledge it is -
- It should perceivable by people who provide it.
- It is modifiable to correct answers.
- Is useful in many situations though it is incomplete or inaccurate.
- It elevate speed of execution of complex programmes it is equipped with.
History of AI :
To know about AI, let's start with the history of the AI, as yearly.
While Hollywood movies and science fiction novels depict AI as human-like robots that take over the world, the current evolution of AI Technologies isn’t that scary – or quite that smart. Instead, AI has evolved to provide many specific benefits in every industry. Keep reading for modern examples of artificial intelligence in health care, retail and more.
Intelligent robots and artificial beings first appeared in the ancient Greek myths of Antiquity. Aristotle's development of the syllogism and it's use of deductive reasoning was a key moment in mankind's quest to understand its own intelligence. While the roots are long and deep, the history of artificial intelligenceas we think of it today spans less than a century. The following is a quick look at some of the most important events in AI.
1950s–1970s
Neural Networks
Early work with neural networks stirs ex,
for “thinking machines.”
1980s–2010s
Machine Learning
Machine learning becomes popular.
Present Day
Deep Learning
Deep learning breakthroughs drive AI boom.
1943
Warren McCullough and Walter Pitts publish "A Logical Calculus of Ideas Immanent in Nervous Activity." The paper proposed the first mathematic model for building a neural network.
1949
In his book The Organization of Behavior: A Neuropsychological Theory, Donald Hebb proposes the theory that neural pathways are created from experiences and that connections between neurons become stronger the more frequently they're used. Hebbian learning continues to be an important model in AI.
1950
Alan Turing publishes "Computing Machinery and Intelligence, proposing what is now known as the Turing test, a method for determining if a machine is intelligent. Harvard undergraduates Marvin Minsky and Dean Edmonds build SNARC, the first neural network computer.Claude Shannon publishes the paper "Programming a Computer for Playing Chess."Isaac Asimov publishes the "Three Laws of Robotics."
1952
Arthur Samuel develops a self-learning program to play checkers.
1954
The Georgetown-IBM machine translation experiment automatically translates 60 carefully selected Russian sentences into English.
1956
The phrase artificial intelligence is coined at the "Dartmouth Summer Research Project on Artificial Intelligence." Led by John McCarthy, the conference, which defined the scope and goals of AI, is widely considered to be the birth of artificial intelligence as we know it today. Allen Newell and Herbert Simon demonstrate Logic Theorist (LT), the first reasoning program.
1958
John McCarthy develops the AI programming language Lisp and publishes the paper "Programs with Common Sense." The paper proposed the hypothetical Advice Taker, a complete AI systems with the ability to learn from experience as effectively as humans do.
1959
Allen Newell, Herbert Simon and J.C. Shaw develop the General Problem Solver (GPS), a program designed to imitate human problem-solving. Herbert Gelernter develops the Geometry Theorem Prover program.Arthur Samuel coins the term machine learning while at IBM.John McCarthy and Marvin Minsky found the MIT Artificial Intelligence Project.
1963
John McCarthy starts the AI Lab at Stanford.
1966
The Automatic Language Processing Advisory Committee (ALPAC) report by the U.S. government details the lack of progress in machine translations research, a major Cold War initiative with the promise of automatic and instantaneous translation of Russian. The ALPAC report leads to the cancellation of all government-funded MT projects.
1969
The first successful expert systems are developed in DENDRAL, a XX program, and MYCIN, designed to diagnose blood infections, are created at Stanford.
1972
The logic programming language PROLOG is created.
1973
The "Lighthill Report," detailing the disappointments in AI Research, is released by the British government and leads to severe cuts in funding for artificial intelligence projects.
1974-1980
Frustration with the progress of AI development leads to major DARPA cutbacks in academic grants. Combined with the earlier ALPAC report and the previous year's "Lighthill Report," artificial intelligence funding dries up and research stalls. This period is known as the "First AI Winter."
1980
Digital Equipment Corporations develops R1 (also known as XCON), the first successful commercial expert system. Designed to configure orders for new computer systems, R1 kicks off an investment boom in expert systems that will last for much of the decade, effectively ending the first "AI Winter."
1982
Japan's Ministry of International Trade and Industry launches the ambitious Fifth Generation Computer Systems project. The goal of FGCS is to develop super computers-like performance and a platform for AI development.
1983
In response to Japan's FGCS, the U.S. government launches the Strategic Computing Initiative to provide DARPA funded research in advanced computing and artificial intelligence.
1985
Companies are spending more than a billion dollars a year on expert systems and an entire industry known as the Lisp machine market springs up to support them. Companies like Symbolics and Lisp Machines Inc. build specialized computers to run on the AI programming language Lisp.
1987-1993
As computing technology improved, cheaper alternatives emerged and the Lisp machine market collapsed in 1987, ushering in the "Second AI Winter." During this period, expert systems proved too expensive to maintain and update, eventually falling out of favor.Japan terminates the FGCS project in 1992, citing failure in meeting the ambitious goals outlined a decade earlier.DARPA ends the Strategic Computing Initiative in 1993 after spending nearly $1 billion and falling far short of expectations.
1991
U.S. forces deploy DART, an automated logistics planning and scheduling tool, during the Gulf War.
1997
IBM's Deep Blue beats world chess champion Gary Kasparov
2005
STANLEY, a self-driving car, wins the DARPA Grand Challenge.The U.S. military begins investing in autonomous robots like Boston Dynamic's "Big Dog" and iRobot's "PackBot."
2008
Google makes breakthroughs in speech recognition and introduces the feature in its iPhone app.
2011
IBM's Watson trounces the competition on Jeopardy!.
2012
Andrew Ng, founder of the Google Brain Deep Learning project, feeds a neural network using deep learning algorithms 10 million YouTube videos as a training set. The neural network learned to recognize a cat without being told what a cat is, ushering in breakthrough era for neural networks and deep learning funding.
2014
Google makes first self-driving car to pass a state driving test.
2016
Google DeepMind's AlphaGo defeats world champion Go player Lee Sedol. The complexity of the ancient Chinese game was seen as a major hurdle to clear in AI.
Working of AI with or without programming :
AI without programming AI with programming It can answer the specific question it is meant to solve programm with AI can answer the generic question it is meant to solve Modification in program leads to change in its structure it can absorb new modification by putting highly independent pieces of information together Modification is not quick & easy. It may leads to affecting programe adversely without affecting its structure quick and easy program modify
Now, we had gone through the Artificial intelligence. But what's the intelligence then? In the next article, you will get information about what is intelligence then!
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