A Brief Overview of Artificial Intelligence


Artificial intelligence has been defined as a branch of science whose goal is to achieve intelligent performance by artificially intelligent computers. Artificial intelligence is the ability to reason, interact and learn in any known environment. Artificial intelligence is different from the natural intelligence exhibited by humans and other animals, which include emotion and consciousness. The difference between the later and the earlier categories can be seen by the popular acronym used. This acronym is called AI (artificial intelligence), since it projects the goal of building intelligent machines to meet human needs in various domains.

A typical artificial intelligence system uses a large amount of computing power, in order to gather, process and analyze large quantities of data in order to provide an overall understanding of the world around it. This sort of general purpose hardware and software is usually referred to as a deep neural network (DNN), short for neurons and nets. The DNN may use different types of algorithms or software to function. DNNs are increasingly used for a wide variety of tasks, including face recognition, speech analysis, object recognition and more recently, computer vision. The typical applications of DNN technology include tasks where the machine needs to recognize and act upon patterns of data without any human intervention.

Face recognition refers to a task that requires an algorithmically trained system to search through large databases to locate a person’s face. Computer vision refers to tasks where the algorithmute user’s vision and detect images, text or any other form of information in the environment without any human interpretation. Another popular use of artificial intelligence in the field of medicine is for medical imaging, where the output from a machine is used to provide a detailed analysis of a patient’s internal health.

Many areas of Machine Learning rely heavily on artificial intelligence. A Deep Learning algorithm is one such example. The output from deep learning algorithms is highly personalized, as it has been tailored to the requirements of each individual application. One of the biggest benefits of using deep learning algorithms is that they can also work independently even without human supervision. This is especially true when the required output is not only highly accurate but also when it is produced on a massive scale by a network of multiple computers all working in unison.

Image processing with artificial intelligence is another use of artificial intelligence. Traditional image processing methods have been slow and inefficient with traditional image processing hardware because it required a large number of computers to operate. With artificial intelligence software such as the Image Processing Software System (IPPS) developed by Cisco, businesses can process more data with less hardware. It is anticipated that Cisco will be among the leaders in adopting artificial intelligence technology for their clientele.

The potential applications of machine learning and artificial intelligence are vast and the applications currently being tested are increasing in capabilities. To date, researchers are testing the accuracy and efficiency of algorithms for search engine ranking, speech recognition, natural language processing, automated e-commerce systems, industrial strength decision making, and automated decision support. In the past, only large organizations with large budgets were able to afford such sophisticated machinery, but thanks to the progress of the technology, smaller companies and even individuals with an interest in the subject can now afford to build and operate their own artificial intelligent machine.

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