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Put simply, RPA involves automating menial and repetitive tasks; cognitive automation adds an all-important extra layer of AI and machine learning. This is a branch of AI that addresses the interactions between humans and computers with natural language. NLP seeks to read and understand human language, but also to make sense of it in a way that is valuable. Basic language understanding makes it considerably easier to automate processes involving contracts and customer service.

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He is also an Alberta Machine Intelligence Institute (Amii) Fellow and a Canada CIFAR AI (CCAI) Chair. Lili received his BS and PhD degrees in 2012 and 2017, respectively, from School of EECS , Peking University.

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Inbenta is a conversational experience platform offering a chatbot among other features. It uses Robotic Process Automation (RPA) to handle transactions, bookings, meetings, and order modifications. Not only the chatbot answers FAQs but also handles policy changes without redirecting users to a different page. It is up to the enterprise now to incorporate it and use it the way it deems fit.

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Entities will be able to build metaverse experiences using Improbable’s Morpheus technology, which is designed to host mass-scale multiplayer online games, Improbable said. Legoland is also exploring post-park experiences that open up new Lego worlds on digital platforms like Minecraft, Roblox, and Rec Room. For instance, in the healthcare industry, cognitive automation helps providers better understand and predict the impact of their patients health.

From the input unit, the data goes through one or more hidden units with the aim of transforming the input into something the output unit can use. There are many neural network models suitable for different use cases and with various computational demands. Although ‘Rules Based’ AI is a powerful method of automating data management processes, it is also one of the simplest artificial intelligence techniques for a business to adopt.

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However, if a business needs to automate repetitive and relatively simple tasks, symbolic AI could get them done. For example, if an office worker wants to move all invoices from certain clients into a dedicated folder, symbolic AI’s rule-based structure suits that need.

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