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Robotic process automation or RPA is an application of technology that is governed by the logic of business and designed inputs to automate business processes. A company can deploy RPA tools to configure software or a robot to collect and interpret applications for processing any function, be it a transaction, data manipulation, triggering responses, or communicating with other digitized systems. The application can range from generating a simple automatic response to an email to deploying tons of bots where each bot is programmed to automate tasks in a business process management system.
The technology provides companies with the ability to reduce costs on staffing and human error. This can be done through the deployment of bots which are typically low-cost and easy to implement. Such bots do not require custom software or deep systems integration.
Natural Language Processing (NLP) being a subset of a combination of computer science, information engineering, and AI deals in interactions between computer and human languages specifically to process natural language data.
The text analytics solutions are capable enough to solve complex insights in the most cost-effective ways. With the advancement of AI technologies, more and more professionals tend to show interest in working with text/speech data today.
In fact, the current approaches of NLP are based on deep learning which evaluates and uses data patterns to enhance program understanding.
The blend of cognitive science and computer science with significant impacts on the private and professional lives of people is considered Cognitive Computing. The goal of this technology is to stimulate human intelligence with computerized thought processes. These include machine learning, computer vision, speech recognition, natural language processing, and robotics.
Additionally, most cognitive systems rely on deep learning algorithms and neural networks to churn out information.
Computer Vision deals with the theory and technology of building an artificial system that receives information and input from images and multi-dimensional data. The vision sensors act upon the object to provide high-level information regarding the environment and the machine.
The technology of Computer Vision is close knitted with AI in order to interpret what it sees and further carry out appropriate analysis and processes in accordance.
The AI application which provides the ability to a system to automatically learn and improve from experience without any exclusive programming is considered machine learning technology. It focuses on the development of such programs which can access data and use them to enhance their learning by observations or data, direct experience, or instruction, to seek patterns in data.
The technology enables the analysis of voluminous data while delivering fast and accurate outcomes. Combining machine learning with cognitive technologies can open more windows for the effective processing of massive information.
Deep Learning can be termed as a subset of machine learning technology that mimics the functionalities of the human brain for data processing and creation patterns which are further used for decision making. The technology has the ability to learn unsupervised from data that is unstructured or unlabelled. This process is also considered deep neural learning or deep neural network. It utilizes a hierarchical level of artificial neural networks to carry out the ML process. Such networks are built like the human brain, with neuron nodes that are connected together like a web.
