Robot Process Automation (RPA) and Its Future

2022 ◽  
pp. 35-58
Author(s):  
Ozge Doguc

Many software automation techniques have been developed in the last decade to cut down cost, improve customer satisfaction, and reduce errors. Robotic process automation (RPA) has become increasingly popular recently. RPA offers software robots (bots) that can mimic human behavior. Attended robots work in tandem with humans and can operate while the human agent is active on the computer. On the other hand, unattended robots operate behind locked screens and are designed to execute automations that don't require any human intervention. RPA robots are equipped with artificial intelligence engines such as computer vision and machine learning, and both robot types can learn automations by recording human actions.

Author(s):  
Ozge Doguc

Many software automation techniques have been developed in the last decade to cut down cost, improve customer satisfaction, and reduce errors. Robotic process automation (RPA) has become increasingly popular recently. RPA offers software robots (bots) that can mimic human behavior. Attended robots work in tandem with humans and can operate while the human agent is active on the computer. On the other hand, unattended robots operate behind locked screens and are designed to execute automations that don't require any human intervention. RPA robots are equipped with artificial intelligence engines such as computer vision and machine learning, and both robot types can learn automations by recording human actions.


2020 ◽  
Vol 9 (1) ◽  
pp. 90-102
Author(s):  
Max Gotthardt ◽  
Dan Koivulaakso ◽  
Okyanus Paksoy ◽  
Cornelius Saramo ◽  
Minna Martikainen ◽  
...  

Technology development has grown rapidly in the last decades and gained importance for accounting and auditing through its identified potentials. Particularly the automation of judgment systems and systems that require human intervention, are deemed to be more relevant to confront a transformation through Robotic Process Automation (RPA). During the continuous development, the augmentation of such systems through Artificial Intelligence (AI) presents a greenfield project with high expectations. However theoretical frameworks have not yet been elaborative and sufficient to capture how such deployments can be conducted. Addressing this research gap, this study presents a summarized overview of the transforming RPA ecosystem and indicates what challenges are critical to being confronted for a successful implementation of such systems in accounting and auditing.


Author(s):  
Mr. Maheshwar M ◽  
Ms. Maitrayee Mahanta ◽  
Mr. P R Kuber Gupta

The model that is proposed in this article suggests ways to shorten the bridge between human and computer with less human intervention by using inclining concepts such as Machine Learning and Artificial Intelligence. The voice assistants that exists currently in market is capable to perform basic tasks whereas, ARYA on the other hand is a type of voice assistant such as google assistant, cortana etc. which has made it easier for the end users to perform and automate various tasks just using their voice. It has multiple advantages over other voice assistants such as face recognition, cross platform assistance and automate document modifications. These features enhance the Access Control System over the usage of voice assistant and also reduces time and complexity of doing many tasks manually. KEYWORDS-machine learning, artificial intelligence, cross platform, face recognition


Author(s):  
Shivangi Ruhela ◽  
Pragati Chaudhary ◽  
Rishija Shrivas ◽  
Deepti Chopra

Artificial Intelligence(AI) and Internet of Things(IoT) are popular domains in Computer Science. AIoT converges AI and IoT, thereby applying AI into IoT. When ‘things’ are programmed and connected to the Internet, IoT comes into place. But when these IoT systems, can analyze data and have decision-making potential without human intervention, AIoT is achieved. AI powers IoT through Decision-Making and Machine Learning, IoT powers AI through data exchange and connectivity. With the AI’s brain and IoT’s body, the systems can have shot-up efficiency, performance and learning from user interactions. Some studies show that, by 2022, AIoT devices such as drones to save rainforests or fully automated cars, would be ruling the computer industries. The paper discusses AIoT at a greater depth, focuses on few case studies of AIoT for better understanding on practical levels, and lastly, proposes an idea for a model which suggests food through emotion analysis.


Author(s):  
Daryna Prylypko

Key words: copyright, work, artificial intelligence, computer program In the article, the problemsof legislation of Ukraine regarding the issues of copyright on works created due to artificialintelligence were analyzed. Particularly, who is the owner of copyright ofworks created due to artificial intelligence. On the one hand, it could be a developer ofa computer program, from the other hand, it could be a client or an employer. Because,it could happen that there is a situation when robots created something newand original, e.g., how it happened with the project “New Rembrandt”. In this case,computers created a unique portrait of Rembrandt. And here is a question, where isin this portrait original and intellectual works of developers of these computers andprograms. In the contrast, this portrait could be created without people who developedspecial machines, programs, and computers. The article’s author proposes to addinto Ukrainian legislation with following norm: the owner of the copyright createddue to artificial intelligence should be a natural person who uses artificial intelligencefor these purposes within the official relationship or on the basis of a contract. In caseof automatic generation of such work by artificial intelligence, the owner of copyrightshould be the developer.Also, another question arises, particularly, who will be responsible for the damagecaused by the artificial intelligence. As an example, of the solution for this issue Resolution2015/2103 (INL) was given, where is mentioned that human agent could be responsiblefor the caused damage. Because, it is not always a developer is responsiblefor the damage.Also, the legislation and justice practice of foreign countries was explored. Theways of overcoming mentioned problems in legislation of Ukraine were proposed.Such as changing our legislation and giving the exact explanation in who is the ownerof copyright on works created due to artificial intelligence and in which cases this personcould become an owner of the copyright. However, probably, these issues shouldbe resolved at international level regarding globalization.


Author(s):  
Jianxin Lin ◽  
Yingce Xia ◽  
Yijun Wang ◽  
Tao Qin ◽  
Zhibo Chen

Image translation across different domains has attracted much attention in both machine learning and computer vision communities. Taking the translation from a source domain to a target domain as an example, existing algorithms mainly rely on two kinds of loss for training: One is the discrimination loss, which is used to differentiate images generated by the models and natural images; the other is the reconstruction loss, which measures the difference between an original image and the reconstructed version. In this work, we introduce a new kind of loss, multi-path consistency loss, which evaluates the differences between direct translation from source domain to target domain and indirect translation from source domain to an auxiliary domain to target domain, to regularize training. For multi-domain translation (at least, three) which focuses on building translation models between any two domains, at each training iteration, we randomly select three domains, set them respectively as the source, auxiliary and target domains, build the multi-path consistency loss and optimize the network. For two-domain translation, we need to introduce an additional auxiliary domain and construct the multi-path consistency loss. We conduct various experiments to demonstrate the effectiveness of our proposed methods, including face-to-face translation, paint-to-photo translation, and de-raining/de-noising translation.


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