Understanding Artificial Intelligence: What is artificial intelligence with examples? (Paperback)
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Language: English. Brand new Book. Understanding Artificial IntelligenceWhat is artificial intelligence with examples?What exactly is artificial intelligence?It's about having a machine that can reach conclusions in a similar way to a human. That is, it can take examples and learn from them to improve the accuracy of its future conclusions. A good example of that is learning what a dog looks like from photographs of Labradors, poodles, and pit bulls and then later, when shown a picture of a Chihuahua, being able to identify that as being another breed of dog. The machine can reach a new, accurate, conclusion based on what it has learned in the past.Today, we are still a long way from creating machines that are as capable as humans. But the current machines are getting very good at specific applications. The important thing to understand about artificial intelligence is that the machine is not programmed with all the possible answers but uses what it has learned to create new answers.What makes a machine "intelligent""It's a combination of things. The machine is weighing up a collection of possibilities for an answer based on the data it was trained on and previous answers it has given. The machine is also learning so that over time the accuracy of its results puter scientists have been working on developing this type of program for probably five decades. The reason we hear so much about artificial intelligence now is that powerful computers have become very cheap and small, and computer scientists have been able to develop better programs that can make use of that power.How do you "teach" AI to a machine?Say we have an AI machine for selecting fruit with bad bits. We would start by showing the machine a large amount of fruit and telling it which ones were good and bad. The machine doesn't store all those images and then look at a new piece of fruit and compare it to all those images. Instead the software starts to characterize what kind of things make the image of a piece of fruit good or bad. It could be that it has some discolored regions or some cuts. The software then looks at a new piece of fruit and if it identifies discolored regions anywhere on the fruit it can assign a probability to the fruit being bad. Books.

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