Robotics Process Automation(RPA) allows organizations to automate task just like a human being was doing them across application and systems. Robotic automation interacts with the existing IT architecture with no complex system integration required.
RPA can be used to automate workflow, infrastructure, back office process which are labor intensive. These software bots can interact with an in-house application, website, user portal, etc. The RPA is a software program which runs on an end user’s pc, laptop or mobile device. It is a sequence of commands which are executed by Bots under some defined set of business rules.
The main goal of Robotics process automation process to replace repetitive and boring clerical task performed by humans, with a virtual workforce. RPA does not require the development of code, nor does it require direct access to the code or database of the applications.
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.
AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as Apple’s Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention.
Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services.
Cloud infrastructure refers to the hardware and software components — such as servers, storage, a network, and virtualization software — that are needed to support the computing requirements of a cloud computing model.
In cloud computing, these virtualized resources are hosted by a service provider or IT department and are delivered to users over a network or the internet. These resources include virtual machines and components, such as servers, memory, network switches, firewalls, load balancers, and storage.
In a cloud computing architecture, cloud infrastructure refers to the back-end components — the hardware elements found within most enterprise data centers. These include multisocket, multicore servers, persistent storage and local area network equipment, such as switches and routers — but on much greater scale.
Major public cloud providers, such as Amazon Web Services (AWS) or Google Cloud Platform, offer services based on shared, multi-tenant servers. This model requires massive compute capacity to handle both unpredictable changes in user demand and to optimally balance demand across fewer servers. As a result, cloud infrastructure typically consists of high-density systems with shared power.