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Atricle Dump - A Gentle Introduction to Artificial Intelligence
Do you have a website? If so, you need an ROR XMLNS code button which leads to a full ROR/RDF code page for your website. This code tells search engines all about the special details you input into the code about your website. For example, it tells them special details about each particular product (or certain special ones) that you sell on your site or sites, it tells the search engine bots your contact information such as your business address and phone number (without informing the entire universe, as the code is invisible to all but you and the search engine bots examining y
3.Natural language processing (NLP)
Languages like English, French or Malayalam, which are used by men, are called natural languages. The language we speak is often context sensitive. "Did you shoot the tiger?” has different meanings when asked to a hunter and a photographer. Also our language is incomplete. Natural language processing deals with understanding this language using knowledge about the grammar rules and context. This has a wide variety of
If a link exists, somewhere on the Internet, directing visitors to your site, or to one of your pages - this is a "backlink". It is the opposite of an outgoing link, or a "forward" link, that takes visitors away from your site. We all know about having a link page on our site. These are "forwarding" links. If a site other than your own, had a links page, and there existed a link on it, to your page, that would be a "forward" link for the site owner, and a "backlink" for you. Why are these links, then, so important? Specifically, if these li
AI uses ideas from diverse branches of knowledge like computer science, economics, biology, social sciences, mathematics and even grammar. It has also diverse applications in many areas of life. That is, it is an interdisciplinary subject, which takes ideas from almost all fields of knowledge and has applications in many diverse areas of life. Some of the branches of AI are discussed below. This in no way is a complete list.
1. Game playing:
Playing a game like checkers, chess, or go, requires a lot of intelligence for a human being and so these tasks were one of the earliest attractions of AI. Samuel wrote a program playing checkers in the 60's and many people contributed to the theory of game playing. Finally when a computer could beat the then world champion in a chess game, that was considered a victory of machine over man even though it was not so. Currently there are well-known algorithms for game playing and game playing is considered falling into the domain of algorithms than AI.
2. Automatic theorem proving:
Mathematicians are believed to be super intelligent creatures, and so in its early childhood AI tried to show intelligence by creating machines capable of proving theorems by themselves. By having some basic assumptions and rules, they tried to prove theorems by combining these rules, getting new assumptions and so on. Gelernters program for geometry theorem proving was a typical example. Later it was realized that the intelligence of human experts in this area is not easily imitable, and the use of common sense and knowledge about mathematics was needed to prove theorems. Currently not many developments are taking place in this area.
3.Natural language processing (NLP)
Languages like English, French or Malayalam, which are used by men, are called natural languages. The language we speak is often context sensitive. "Did you shoot the tiger?” has different meanings when asked to a hunter and a photographer. Also our language is incomplete. Natural language processing deals with understanding this language using knowledge about the grammar rules and context. This has a wide variety of a
Looking for a job online? Well, you are not alone. In fact, you are among the new breed of millions of job seekers who are hunting for their next job online. If someone were to argue that online job sites are little more than hot air, you only need to compare the success rate of offline job hunting efforts with that of online job hunting.Why Search For A Job Online?Here is a statistic to give you an idea of how big the online job industry is. Certainly it is very hard to quantify the overall number of resumes on the Internet. Monster.com has about 54 million resume
AI uses ideas from diverse branches of knowledge like computer science, economics, biology, social sciences, mathematics and even grammar. It has also diverse applications in many areas of life. That is, it is an interdisciplinary subject, which takes ideas from almost all fields of knowledge and has applications in many diverse areas of life. Some of the branches of AI are discussed below. This in no way is a complete list.
1. Game playing:
Playing a game like checkers, chess, or go, requires a lot of intelligence for a human being and so these tasks were one of the earliest attractions of AI. Samuel wrote a program playing checkers in the 60's and many people contributed to the theory of game playing. Finally when a computer could beat the then world champion in a chess game, that was considered a victory of machine over man even though it was not so. Currently there are well-known algorithms for game playing and game playing is considered falling into the domain of algorithms than AI.
2. Automatic theorem proving:
Mathematicians are believed to be super intelligent creatures, and so in its early childhood AI tried to show intelligence by creating machines capable of proving theorems by themselves. By having some basic assumptions and rules, they tried to prove theorems by combining these rules, getting new assumptions and so on. Gelernters program for geometry theorem proving was a typical example. Later it was realized that the intelligence of human experts in this area is not easily imitable, and the use of common sense and knowledge about mathematics was needed to prove theorems. Currently not many developments are taking place in this area.
3.Natural language processing (NLP)
Languages like English, French or Malayalam, which are used by men, are called natural languages. The language we speak is often context sensitive. "Did you shoot the tiger?” has different meanings when asked to a hunter and a photographer. Also our language is incomplete. Natural language processing deals with understanding this language using knowledge about the grammar rules and context. This has a wide variety of
Catastrophic illnesses are claimed to have triggered approximately half of all personal bankruptcies in the United States. According to recent findings from a Harvard University study, most people who go bankrupt because of medical problems also have health insurance. Researchers found that many private insurance plans that offer limited catastrophic coverage were inadequate and offer little financial security for less severe illnesses.Questionnaires were distributed to 1,771 bankruptcy filers in 2001 in California, Illinois, Pennsylvania, Tennessee and Texas. According t
1. Game playing:
Playing a game like checkers, chess, or go, requires a lot of intelligence for a human being and so these tasks were one of the earliest attractions of AI. Samuel wrote a program playing checkers in the 60's and many people contributed to the theory of game playing. Finally when a computer could beat the then world champion in a chess game, that was considered a victory of machine over man even though it was not so. Currently there are well-known algorithms for game playing and game playing is considered falling into the domain of algorithms than AI.
2. Automatic theorem proving:
Mathematicians are believed to be super intelligent creatures, and so in its early childhood AI tried to show intelligence by creating machines capable of proving theorems by themselves. By having some basic assumptions and rules, they tried to prove theorems by combining these rules, getting new assumptions and so on. Gelernters program for geometry theorem proving was a typical example. Later it was realized that the intelligence of human experts in this area is not easily imitable, and the use of common sense and knowledge about mathematics was needed to prove theorems. Currently not many developments are taking place in this area.
3.Natural language processing (NLP)
Languages like English, French or Malayalam, which are used by men, are called natural languages. The language we speak is often context sensitive. "Did you shoot the tiger?” has different meanings when asked to a hunter and a photographer. Also our language is incomplete. Natural language processing deals with understanding this language using knowledge about the grammar rules and context. This has a wide variety of
There are many software applications available for managing customer interactions, or customer relationship management (CRM). It is a mistake to assume that once you've seen one, you've seen them all, because they are not all the same.One of the easiest ways a prospective client can reduce the risk of failure in CRM implementations is to fully engage and co-operate during the discovery phase.Some prospects are reluctant to provide information about their businesses and keep insisting "I know what I want". Unless a person has actually implemented CRM applications be
2. Automatic theorem proving:
Mathematicians are believed to be super intelligent creatures, and so in its early childhood AI tried to show intelligence by creating machines capable of proving theorems by themselves. By having some basic assumptions and rules, they tried to prove theorems by combining these rules, getting new assumptions and so on. Gelernters program for geometry theorem proving was a typical example. Later it was realized that the intelligence of human experts in this area is not easily imitable, and the use of common sense and knowledge about mathematics was needed to prove theorems. Currently not many developments are taking place in this area.
3.Natural language processing (NLP)
Languages like English, French or Malayalam, which are used by men, are called natural languages. The language we speak is often context sensitive. "Did you shoot the tiger?” has different meanings when asked to a hunter and a photographer. Also our language is incomplete. Natural language processing deals with understanding this language using knowledge about the grammar rules and context. This has a wide variety of
The Utah housing market is an excellent place to invest your money. Utah homes consistently increase in value, and in most areas of the state, homes are still affordable. If you are in the market for a Utah home mortgage loan, you may want to bypass the traditional bank or offline broker and consider using an online broker.Why Use an Online Broker?Online brokers are extremely easy to locate and work with. They also tend to charge lower fees than offline brokers. However, the main benefit of working with an online broker is the sheer mass of loan programs tha
3.Natural language processing (NLP)
Languages like English, French or Malayalam, which are used by men, are called natural languages. The language we speak is often context sensitive. "Did you shoot the tiger?” has different meanings when asked to a hunter and a photographer. Also our language is incomplete. Natural language processing deals with understanding this language using knowledge about the grammar rules and context. This has a wide variety of applications and is a field of active research. Also translation between these languages is studied in AI.
4. Vision, Speech recognition and similar areas.
Seeing an animal and recognizing it as a cat is child's play, but a difficult task for computers. Modern AI programs focuses on recognizing objects and persons and behavior based on vision. This has many applications in robot navigation, crime detection, military operations and so on.
5. Expert Systems
Human experts are rare, costly and perishing. If we spend a large sum and train a person as a neurologist, the maximum we can expect is 30-40 years of service. And we cannot take a copy of the neurologist! So if we can train a computer to have the same expertise or to be precise expert behaviour, at least in a narrow field, the utility is high. Expert systems deal with extracting expertise and porting it to computers. That is creating software that can exhibit expert behavior. This field has undergone explosive growth in the last few years.
6.Neural networks
Animal brain is composed of neurons and performs computations (thinking) by passing signals between these networks of neurons. Why not imitate this and evolve intelligence? Neural networks began from this foundation. They are capable of learning, adapting and predicting. Putting in simple language, a neural network is a collection of computation units (real or virtually created), which are interconnected and cooperates for computation. Neural networks have applications in control systems, speech and natural language processing, vision and many other fields.
There are various other areas in AI. It is a vast and emerging field. I will tell more about it in my next article.
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