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AI Artificial Intelligence. Definition What is your definition of Artificial Intelligence? Artificial intelligence (AI) is the intelligence of machines.

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Presentation on theme: "AI Artificial Intelligence. Definition What is your definition of Artificial Intelligence? Artificial intelligence (AI) is the intelligence of machines."— Presentation transcript:

1 AI Artificial Intelligence

2 Definition What is your definition of Artificial Intelligence? Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. (

3 AI Reasons Is AI possible at all? Why would scientists try to create Intelligent Agents? What might we use AI for? What systems should have AI? What does a machine need to gain AI? Why have scientists been unsuccessful at this point?

4 Applications Artificial intelligence has been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore. ( Example: Apple iTunes Genius Mixes The Genius Mixes feature searches your iTunes library to find songs that go great together, then organizes them into mixes youll love. iTunes creates multiple Genius Mixes automatically. (

5 Problems Intelligence is the ability to think, to imagine, to create, memorize, understand, recognize patterns, make choices, adapt to change and learn from experience. Artificial intelligence is a human endeavor to create a non-organic machine-based entity, that has all the above abilities of natural organic intelligence. Initial hopes of computer scientists of creating an artificial intelligence, were dashed hopelessly as they realized how much they had underrated the human mind's capabilities! How do you teach a machine to imagine?

6 Problems Initially, researchers thought that creating an AI would be simply writing programs for each and every function an intelligence performs! As they went on with this task, they realized that this approach was too shallow. Even simple functions like face recognition, spacial sense, pattern recognition and language comprehension were beyond their programming skills! They understood that to create an AI, they must delve deeper into natural intelligence first. They had to understand what understanding really means!

7 Approaches Neural Networks: This is the bottom up approach. It basically aims at mimicking the structure and functioning of the human brain, to create intelligent behavior. Researchers are attempting to build a silicon-based electronic network that is modeled on the working and form of the human brain! Our brain is a network of billions of neurons, each connected with the other. At an individual level, a neuron has very little intelligence, in the sense that it operates by a simple set of rules, conducting electric signals through its network. However, the combined network of all these neurons creates intelligent behavior This approach has not been able to achieve the ultimate goal but there is a very positive progress in the field.

8 Approaches Expert Systems: This is the top down approach. Instead of starting at the base level of neurons, by taking advantage of the phenomenal computational power of the modern computers, followers of the expert systems approach are designing intelligent machines that solve problems by deductive logic. As the name expert systems suggest, these are machines devoted to solving problems in very specific areas. They have total expertise in a specific domain of human thought. They are programmed to use statistical analysis and data mining to solve problems. They arrive at a decision through a logical flow developed by answering yes-no questions. Chess computers like Fritz and its successors that beat chess grandmaster Kasparov are examples of expert systems.

9 Approaches Swarm Intelligence: This is an approach to, as well as application of artificial intelligence similar to a neural network. Here, programmers study how intelligence emerges in natural systems like swarms of bees even though on an individual level, a bee just follows simple rules. They study relationships in nature like the prey-predator relationships that give an insight into how intelligence emerges in a swarm or collection from simple rules at an individual level. They develop intelligent systems by creating agent programs that mimic the behavior of these natural systems! (

10 The BIG Questions… Even if such an intelligence is created, will it share our sense of morals and justice, will it share our dreams? OR Will we create a world closer to that of the science fiction movies iRobot, Terminator, or the Matrix where machines battle with humans for dominance of the world?

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