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Topic 2 - Applications of AI

Topic 2 - Applications of AI. St Kentigern’s Academy Unit 2 – Artificial Intelligence. Artificial Neural Network/System. A neural network is an electronic model of the brain consisting of many interconnected simple processors. Artificial Neural Network/System.

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Topic 2 - Applications of AI

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  1. Topic 2 - Applications of AI St Kentigern’s Academy Unit 2 – Artificial Intelligence

  2. Artificial Neural Network/System • A neural network is an electronic model of the brain consisting of many interconnected simple processors.

  3. Artificial Neural Network/System • Neural networks take a different approach from conventional programming. Neural networks are designed to try and do things that we don’t exactly know how to do.

  4. Artificial Neural Network/System • The brain consists of millions of interconnected records. • An ANS consists of hundreds of interconnected artificial neurons, so it is based on the same model as the brain.

  5. Artificial Neural Network/System • Applications of ANS • Debt risk assessment • Loan granting is one area in which neural networks can aid humans, as it is not based on predetermined criteria, but instead the answers are vague. • The process works by analysing past failures and making decisions based upon past experience.

  6. Artificial Neural Network/System • Applications of ANS • Stock Market Prediction • Neural systems have been touted as all powerful tools in stock market prediction. • The program tries to anticipate the market by interpreting external parameters such as economic indicators and public opinion.

  7. Artificial Neural Network/System • Applications of ANS • Postal Services • Character recognition is applied to handwritten documents and is used to help post offices automate the sorting of mail.

  8. Artificial Neural Network/System • Advantages • They learn and adjust to changes in circumstances. • Disadvantages • The neural system need to be trained which is very time consuming.

  9. Vision Systems • This is the machines ability to make sense of visual input. • A camera sends its image to a computer • The computer compares the images of items with a ‘learned’ image of an ideal item of the same type. • Some vision systems use an ANS to help with image interpretation.

  10. Vision Systems • Applications of Vision Systems • Industrial • Vision systems are used to check items on production lines • Military • Target recognition is a military application which uses image data to determine if an enemy target is present. • Satellite Photo Interpretation • Satellites collect an enormous amount of data which would normally take researchers ages to analyse and interpret. Using a vision system with a neural network speeds up the task.

  11. Speech recognition • These systems allow the user to communicate with the computer by talking to it.

  12. Speech recognition • The characteristics of speech recognition are: • Training for each voice pattern; • Control instructions; • Background noise; • Factors affecting accuracy.

  13. Speech recognition • Training • However, before using the system you must first go through the process of training it. • This consists of reading pre-defined text into the computer. • The computer samples you voice and matches it to sounds which are common in all words.

  14. Speech recognition • Training • When training a speech recognition package you should take the following into account: • Speak in a consistent, level tone; • Use a consistent rate, without speeding up; • Speak without pausing between words; • Work in a quiet environment; • Pronounce words clearly.

  15. Speech recognition • Control Instructions • As well as allowing a user to speak into a system and it converting the sound to text, systems also allow a user to speak commands. • This is seen as a different form of HCI as it is possible to control the computer without using a keyboard or a mouse. The user can switch from dictation mode to command mode easily when working on a document.

  16. Speech recognition • Background Noise • A change in the background noise will affect the accuracy of the system. • A system that is trained in an empty quiet room will make mistakes if taken and used in a room with background noise, e.g. a room full of computers will make a buzzing noise that a system will pick up on.

  17. Speech recognition • Factors Affecting Accuracy • These include: • Background noise; • The user having a cold/sore throat; • The user’s accent/dialect;

  18. Speech recognition • Applications of Speech recognition • Word processing • The user speaks the words and they are converted into text and put in a WP document; • Punctuation Commands • As another form of HCI to input commands to the computer; • Disabled Users • For users who are unable to use their hands;

  19. Speech recognition • Applications of Speech recognition • Cars • Some cars let you control mobile phones/music via speech recognition. • Military • Used in training simulators where a speech interface can simulate multiple remote operators; • Mobile Phones • Rather than trying to type using the small keyboard you can tell the phone who to call.

  20. handwriting recognition • The user writes on the touch-screen using a stylus pen and the writing is turned into text and displayed on the screen. • Early systems (and still some today) required the user to enter letters and numbers so that they can be stored and matched against any future input. • Current systems train the user to write in a specific way, this means that more users can use the system as it is not programmed to one persons handwriting.

  21. handwriting recognition • Applications • Palmtops and Tablet PC’s • Both of these are small devices and by having handwriting recognition available via the touch-screen, there is no need to use up space with a keyboard.

  22. Intelligent Robots • Robots are automatic electro-mechanical machines. • Some are not fully automatic but are remotely controlled by humans using TV and other feedback. • The term intelligent robot has been coined to differentiate robots equipped with vision systems, ANS, the ability to learn or some other aspect of AI. • A dumb robot has no controlling processor and it merely repeats the same movements again and again.

  23. Intelligent Robots • Advantages of Intelligent Robots • Increased productivity • Robots do not require breaks • Improved accuracy • More accurate than humans • Consistency • They don’t get tired like humans • Reduced Wage Bill • Fewer staff employed with no wages

  24. Intelligent Robots • Advantages of Intelligent Robots • Increased productivity • Robots do not require breaks • Improved accuracy • More accurate than humans • Consistency • They don’t get tired like humans • Reduced Wage Bill • Fewer staff employed with no wages • Hostile Environment • Can go to dangerous places where humans can’t

  25. Intelligent Robots • Sensors • These allow the robot to be aware of their surroundings • Bumb Sensors • When the robot touches an item it knows; • Proximity Sensor • The robot knows when it is near something • Light Sensor • Can tell the differences in light • Temperature sensors • The robot can tell if the temperature has changed

  26. Intelligent Robots • Applications • Automated Delivery • Large companies employ a team of staff to deliver internal mail each day. Robots are now being used to automate the process. • Pipe Inspection • Robots are proving useful for routine pipe inspection in manufacturing and processing plants. Their ability to reach inaccessible areas makes them useful. • Bomb Disposal • Robots for this purpose are available in many communities and are used routinely by law enforcement. Their objective is to separate personnel from danger as they seek out and detonate explosives. • Exploration of unknown environments • A robot which is being sent to another planet must have independent decision making capabilities.

  27. Expert Systems • Expert systems collect the small fragments of human know-how into a knowledge base which is used to reason through a problem, using the knowledge which is appropriate. • Instead of attempting to create an intelligent program, research focused on creating a means of representing and accessing knowledge.

  28. Expert Systems • Expert systems are computer programs which could offer advice in a restricted subject where it was possible to create facts and rules representing knowledge. • An expert system is an attempt to replace the human expert and to make their knowledge available in a cost-effective form.

  29. Expert Systems • Advantages of Expert Systems • More available than a human expert • In a remote area an expert may not be available. The expert system could be available 24/7 and consulted at any time. • Don’t have to pay the system wages • Human experts can command large fees for their services, but once an expert system is set up the company wage bill can be reduced by employing fewer people.

  30. Expert Systems • Advantages of Expert Systems • They have the combined knowledge from more than 1 human expert • A single human has only his knowledge. An expert system can contain the combined knowledge of many experts in the field. • They are more reliable. • Humans are prone to error. Expert systems have a restricted domain and are only aware to the task for which they were designed and are not prone to interference from external factors. This makes them more reliable.

  31. Expert Systems • Applications • Medicine • MYCIN was the first expert system which gave advice to doctors on blood disease. • DHSS • An expert system advices on the benefits due depending on circumstances. • Legal • Solicitors can check that they are giving the right advice to a client • British Gas • Has an expert system which is used to calculate the most likely place where corrosion will occur in a gas pipe.

  32. Expert Systems • Social, Legal and Ethical Issues • Effects on employment • Many fear that using AI in industry will mean a decrease in jobs and with good reason. On-line shopping means fewer sales clerks. • However, we need expert systems because of the lack of experts. • And remember, an expert system should only be used as advice. Therefore a human needs to query the expert system to obtain the knowledge. This means that there are training implications.

  33. Expert Systems • Social, Legal and Ethical Issues • Training Issues • Staff will need to be trained to use the new system. • Some staff will be resistant to change and worried about job losses. Staff need to be reassured that an expert system will help them and that they will be give all the training they need in order to do their job.

  34. Expert Systems • Social, Legal and Ethical Issues • Public Reactions • An example: if you had to go to the doctor for a serious consultation, would you prefer to see a human or a robot? • Most people would not like to think that important decisions are being made for them by a computer program.

  35. Expert Systems • Social, Legal and Ethical Issues • Loss of Human Expertise • There is a fear from experts that if they give their knowledge to a program then they will be no longer needed. • This is not the case. Expert systems are required because there are not enough experts.

  36. Expert Systems • Social, Legal and Ethical Issues • Who is to blame? • If an expert system gets it wrong and a human follows that advice and uses it, who is to blame? • The program? • The programmer? • The Human Expert? • An expert system is to be used the same way that a book should be used as reference. If the human chooses to agree with the expert system that’s fine. But if the advice is wrong it is the human who is responsible.

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