Cognitive agents: technologies that combine machine learning and natural-language generation to build a completely virtual workforce (or “agent”) that is capable of executing tasks, communicating, learning from data sets, and even making decisions based on “emotion detection.”
— Srinivasan Venkatarajan (@srini_venkat) June 19, 2019
Natural-Language Generation (NLG)
— Srinivasan Venkatarajan (@srini_venkat) June 19, 2019
1) Broadcasters have been using NLG to draft stories about games in real time.
2) Structured performance data can be piped into a natural-language engine to write internal and external mgmt reports automatically.
Natural-language generation (NLG): s/w engines that create seamless interactions between humans and technology by following rules to translate observations from data into prose.
— Srinivasan Venkatarajan (@srini_venkat) June 19, 2019
#RPA - s/w automation tool that automates routine tasks such as data extraction, cleaning through existing UI. The robot has a user ID just like a person and can perform rules-based tasks like accessing email & systems, perform calculations, creating docs/rpts, & checking files
— Srinivasan Venkatarajan (@srini_venkat) June 19, 2019
IPA in its full extent encompasses 5 core technologies:
— Srinivasan Venkatarajan (@srini_venkat) June 19, 2019
1) Robotic process automation (RPA)
2) Smart workflow
3) Machinne learning/advanced analytics
4) Natural-language generation (NLG)
5) Cognitive agents#IPA #IntelligentProcessAutomation
IPA mimics activities carried out by humans and, over time, learns to do them even better #IPA #IntelligentProcessAutomation
— Srinivasan Venkatarajan (@srini_venkat) June 19, 2019
IPA vs RPA:
— Srinivasan Venkatarajan (@srini_venkat) June 19, 2019
IPA combines fundamental process redesign with robotic process automation and machine learning.#IntelligentProcessAutomation #IPA #RPA
