By Laura Cleland at December 09 2018 04:23:57
In medicine, programs have been developed that analyze the disease symptoms, medical history, and laboratory test results of a patient, and then suggest a diagnosis to the physician. The diagnostic program is an example of so-called expert systems-programs designed to perform tasks in specialized areas as a human would. Expert systems take computers a step beyond straightforward programming, being based on a technique called rule-based inference, in which preestablished rule systems are used to process the data. Despite their sophistication, systems still do not approach the complexity of true intelligent thought.
It is a good idea to choose a champion for each tool who will master its use. Assign owners to processes Choose a person with leadership skills and the appropriate level of responsibility and influence and make him/her accountable for continuous improvement of the process. Give him/her a clear objective to achieve and an incentive to reach the goal. Encourage feedback for process improvement To ensure that the flow of information between executors and the process owner is fluid, encourage people to contribute to process enhancement through incentives. Use your imagination to reward contributors (consider not only monetary incentives).
Many scientists remain doubtful that true AI can ever be developed. The operation of the human mind is still little understood, and computer design may remain essentially incapable of analogously duplicating those unknown, complex processes. Various routes are being used in the effort to reach the goal of true AI. One approach is to apply the concept of parallel processing-interlinked and concurrent computer operations. Another is to create networks of experimental computer chips, called silicon neurons, that mimic data-processing functions of brain cells. Using analog technology, the transistors in these chips emulate nerve-cell membranes in order to operate at the speed of neurons.
Process definitions are high level descriptions instead of rigid workflows : Processes can only be defined up to a certain level of detail, and it is difficult to provide low level work instructions or to automate decisions. Because they cannot be formalised in detail, process simulation is rarely possible. Decisions are highly subjective and too complex to be expressed in a formal language, as they are taken based on intuition and not on rigid business rules.
In all cases, however, the task that the algorithm is to accomplish must be definable. That is, the definition may involve mathematical or logic terms or a compilation of data or written instructions, but the task itself must be one that can be stated in some way. In terms of ordinary computer usage, this means that algorithms must be programmable, even if the tasks themselves turn out to have no solution. In computational devices with a built-in microcomputer logic, this logic is a form of algorithm. As computers increase in complexity, more and more software-program algorithms are taking the form of what is called hard software.
In mathematics, method of solving a problem by repeatedly using a simpler computational method. A basic example is the process of long division in arithmetic. The term algorithm is now applied to many kinds of problem solving that employ a mechanical sequence of steps, as in setting up a computer program. The sequence may be displayed in the form of a flowchart in order to make it easier to follow. As with algorithms used in arithmetic, algorithms for computers can range from simple to highly complex.