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Sunday, February 28, 2021

RPA Examined

See also aspects of business process modeling for extensions to the idea.  And likely combination with broader methods of ML and AI

Some thoughts on RPA: By Maria Macaraig  October 8, 2019    in Datafloq

Robotic process automation or RPA is the technology that makes it possible to program software and empower machines to mimic human actions, replicate human motion, and perform human functions automatically, and repetitively. 

RPA is powering waves of transformative change in manufacturing industries, defense, aerospace, business, and healthcare. The intelligent software and its visible application, the robot, don’t rest, is error-free, and is more productive and profitable than a human.   

Robotic process automation is not only changing the way we work; the technology is quietly revolutionizing the future. It should be useful to review the developments that set the stage for RPAs dominance so that we gain a better appreciation of the role and significance of RPA.

Kansas software experts at Tricension explain the history and role of RPA in enabling companies to enhance quality and improve productivity by streamlining business processes. 

The 1950s and 60s: Emergence of Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP)

Foundational research conducted by eminent American computer scientists led by John McCarthy and Arthur Samuel paves the way for imbuing computers with the capability to think and respond like humans. 

AI, ML, computer engineering, and linguistic sciences were combining resources to deliver a single toolkit that could boost robotic process automation. 

Artificial Intelligence was focusing on creating smart machines that could mimic human intelligence (using logic, and reasoning) to solve complex issues that were beyond the range of the human brain. 

Machine Learning, developing as an offshoot of AI, was coding software algorithms that could gather and analyze big data. We designed algorithms that could “think” and “learn” on their own without being expressly programmed to do so.

Advancements in Natural Language Processing enabled us to bridge the gap between computers and natural human language. Artificial Intelligence technology-enabled computers to analyze large volumes of natural language and accurately comprehend the meaning and intent behind human-oriented spoken and written commands.   ... " 

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