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Pathway Diagrams Specifications Reactome Database Chemistry Flow Chart P1 S1 Flowchart

Pathway Diagrams Specifications Reactome Database Chemistry Flow Chart P1 S1 Flowchart

By Elizabeth Spain at November 10 2018 08:07:23

Flowcharts can be very useful for a technical writer. If you're working on a complex process, a flowchart can show you the various steps involved in that process. For example, you could be working on a manual on how to troubleshoot the Autopilot Flight Director system for the Boeing 747 aircraft. There are various steps involved in troubleshooting this system. Each step has multiple sub-steps. By creating a flowchart, you can quickly see which step takes place at what stage in the process.

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.

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Knowledge workers carry out these processes by taking into account multiple inputs (generally a wide set of unstructured data and information) to perform difficult tasks and make complex decisions among multiple possible ways of doing the work, each one implying different levels of risk and possible benefits. They are dependent on individuals and it is not possible to automate them. One example of a knowledge process is "Marketing a new product". The same steps are followed each time a new product is launched (benchmarking competitors, deciding pricing strategy, planning promotion, etc...), but it is the experience, knowledge and intuition of the people that drive the process to success.

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.

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