Impacts Of Artificial Intelligence

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Artificial Intelligence Recently, the media has spent an increasing amount of broadcast time on new technology. The focus of high-tech media has been aimed at the flurry of advances concerning artificial intelligence (AI). What is artificial intelligence and what is the media talking about? Are these technologies beneficial to our society or potential threats? Medical facilities, police departments, and manufacturing plants have all been changed by AI. Will machine language and artificial neural network replace humans in the future? Artificial intelligence is defined as developing computer programs to solve complex problems by applications of processes that are analogous to human reasoning processes. Roughly speaking, a computer is intelligent …show more content…

For example, the self-driving car fleet from Uber is already under active development and testing in Pittsburg. Competitiveness with Google Translate and Apple Siri show promise with language learning. With improvements in computer vision and legged locomotion, robots for unstructured environments become practical; these might include agricultural and service settings and helping humans (especially the elderly and infirm) with domestic chores. Finally, as machines improve their grasp of language, search engines and "personal assistants" on mobile phones will change from indexing web pages to understanding web pages, leading to qualitative improvements in their ability to answer questions, synthesize new information, offer advice, and connect the dots. AI may also have a substantial impact on areas of science, such as systems biology, where the complexity and volume of information challenges human abilities. (Russell, …show more content…

Some machine learning works in a way similar to the way people do it. Google Translate, for example, uses a large database of text in a given language to translate to another language, a statistical process that doesn 't involve looking for the "meaning" of words. Humans, do something similar, in that we learn languages by seeing lots of examples. Google Translate doesn 't always get it right, precisely because it doesn 't seek meaning and can sometimes be fooled by synonyms or differing connotations. (Schapire, 2008) Current and future examples of machine learning include; optical character recognition, face detection, spam filtering, fraud detection, weather prediction and medical

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