By Gabrielle Button at November 10 2018 14:59:15
Multiple inputs to the process exist : Some of them would be competition, lifecycle stage of the market, brand image, budget, etc... ; Complex decisions are made : There are many possible ways to achieve the process objectives (reach planned sales, leverage brand image, etc...) ; Each decision implies different levels of risk and potential benefits : It is the responsibility of the worker to choose the best one (low price strategy, aggressive advertising campaign, etc...) ; There are three main characteristics that make knowledge processes different from highly structured processes: Focus is on communication instead of automation.
Current research in information processing deals with programs that enable a computer to understand written or spoken information and to produce summaries, answer specific questions, or redistribute information to users interested in specific areas of this information. Essential to such programs is the ability of the system to generate grammatically correct sentences and to establish linkages between words, ideas, and associations with other ideas. Research has shown that whereas the logic of language structure-its syntax-submits to programming, the problem of meaning, or semantics, lies far deeper, in the direction of true AI.
Here are the types of evidence you can use: Images ; A photo is often a great way to show a point. You can use a photo in three ways: * Literally: If you're talking about a piece of equipment, show a photo of it rather than describe its specifications in bulleted text. You can use callouts that point to the various features and label them. * Metaphorically: Sometimes a point you're making is a concept, rather than a fact. For example, you may be talking about tough times ahead, so you could show a photo of a rocky road or a steep staircase. * Schematically: If you're talking about a process, you can show it with a diagram or add arrows to point out parts of a photo.
The possibility of developing some such artifact has intrigued human beings since ancient times. With the growth of modern science, the search for AI has taken two major directions: psychological and physiological research into the nature of human thought, and the technological development of increasingly sophisticated computing systems. In the latter sense, the term AI has been applied to computer systems and programs capable of performing tasks more complex than straightforward programming, although still far from the realm of actual thought. The most important fields of research in this area are information processing, pattern recognition, game-playing computers, and applied fields such as medical diagnosis.