Research briefly on the assigned tasks as it links to Artificial intelligence and post your description in this blog. Always give practical examples from research in your postings or presentations.
Gary : Turing Test
Tasin: Parallel Processing
Salima: Machine Learning
Immaculate: Natural Language
Sajni:Common - sense knowledge
Rishad:Inference Engine
Atiya:Fuzzy logic
Nafisa:Knowledge base
Terry: Expert system
Class Activity (To be done in Pairs)
1. Explain what Turing Test is? Is the Turing Test a valid test of intelligence? Why or why not?
2. What/Who is ELIZA?
3. Discuss the impact ELIZA had on the area of entertainment?
4. Go to this site and talk with ELIZA.
http://www-ai.ijs.si/eliza/eliza.html
5. What/Who is A.L.I.C.E?
6. Have a chat with ALICE. Click on the link below.
http://www.pandorabots.com/pandora/talk?botid=f5d922d97e345aa1
7. Research AARON, the expert system artist in your text or on line. Who is the artist, AARON or Harold Cohen? Is AARON a work of art, an artist, or both? Explain your answer.
http://www.pbs.org/safarchive/4_class/45_pguides/pguide_804/4484_aaron.html
http://www.scinetphotos.com/aaron.html
10 comments:
A computer application that performs a task that would otherwise be performed by a human expert. For example, there are expert systems that can diagnose human illnesses, make financial forecasts, and schedule routes for delivery vehicles. Some expert systems are designed to take the place of human experts, while others are designed to aid them.
Expert systems are part of a general category of computer applications known as artificial intelligence . To design an expert system, one needs a knowledge engineer, an individual who studies how human experts make decisions and translates the rules into terms that a computer can understand.
http://www.webopedia.com/TERM/E/expert_system.html
Parallel processing is the simultaneous processing of the same task on two or more microprocessors in order to obtain faster results. The computer resources can include a single computer with multiple processors, or a number of computers connected by a network, or a combination of both. The processors access data through shared memory. Some supercomputer parallel processing systems have hundreds of thousands of microprocessors.
With the help of parallel processing, a number of computations can be performed at once, bringing down the time required to complete a project. Parallel processing is particularly useful in projects that require complex computations, such as weather modeling and digital special effects. Let's take a real-life example to understand the efficacy of parallel processing.
5: Alice is:
Short for Artificial Linguistic Computer Entity, an open source, natural language chatbot that relies on artificial intelligence for human interaction.
7:AARON cannot learn new styles or imagery on its own, each new capability must be hand-coded by Harold Cohen, but it is capable of producing a practically infinite supply of distinct images in its own style. It does seem however that AARON's output follows a noticeable formula (figures standing next to a potted plant, framed within a colored square is a common theme).
I think that AARoN is not the artist as it has been programmed to do what it does. What do u think
Explain what Turing Test is? Is the Turing Test a valid test of intelligence? Why or why not?
The Turing test is a test of a machine's ability to demonstrate intelligence. It proceeds as follows: a human judge engages in a natural language conversation with one human and one machine, each of which tries to appear human. All participants are placed in isolated locations. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test.
Impracticality and irrelevance: the Turing test and AI research. Mainstream AI researchers argue that trying to pass the Turing Test is merely a distraction from more fruitful research. This is because there are easier ways to test their programs such as automated scheduling, object recognition, or logistics, In order to test the intelligence of the programs that solve these problems, AI researchers simply give them the task directly, rather than going through the roundabout method of posing the question in a chat room populated with computers and people.
ELIZA was one of the first programs that attempted to communicate in natural language, based on a "script" consisting of patterns and corresponding response, and “almost no intelligence whatsoever ” to “provided a startlingly human-like interaction”
Joseph Weizenbaum in Communications of the ACM in January 1966
ELIZA remains a milestone simply because it was the first time a programmer had attempted such a human-machine interaction with the goal of creating the illusion (however brief) of human-human interaction.
Influence on games
ELIZA had an impact on a number of early computer games by demonstrating additional kinds of interface designs,
Common sense knowledge:
In artificial intelligence research, commonsense knowledge is the collection of facts and information that an ordinary person is expected to know. a commonsense knowledge base is a database containing all the general knowledge that most people possess, represented in a way that it is available to artificial intelligence programs that use natural language or make inferences about the ordinary world.
Natural Language:
Natural language is the language that is used by humans for general purpose communications.
It also allows the user to present their search as a question or a statement instead of restricting it to just keywords.
For example, ask jeeves allows the user to present their searches in a form of wuestion to be able to obtain efficient results.
Inference engine
In computer science, and specifically the branches of knowledge engineering and artificial intelligence, an inference engine is a computer program that tries to derive answers from a knowledge base. It is the "brain" that expert systems use to reason about the information in the knowledge base for the ultimate purpose of formulating new conclusions. Inference engines are considered to be a special case of reasoning engines, which can use more general methods of reasoning.
http://en.wikipedia.org/wiki/Inference_engine
In simple rule-based systems, there are two kinds of inference, forward chaining and backward chaining.
Forward chaining: data gets put into working memory. This triggers rules whose conditions match the new data. These rules then perform their actions. The actions may add new data to memory, thus triggering more rules. And so on. This is also called data-directed inference, because inference is triggered by the arrival of new data in working memory.
Backward chaining: the system needs to know the value of a piece of data. It searches for rules whose conclusions mention this data. Before it can use the rules, it must test their conditions. This may entail discovering the value of more pieces of data, and so on. This is also called goal-directed inference, or hypothesis driven, because inferences are not performed until the system is made to prove a particular goal (i.e. a question).
http://www.j-paine.org/students/lectures/lect3/node10.html
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