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    A Reality Check for Chatbots or Humans?

    The chatbots also need different recommendation algorithms for different domains, and that is the essential part of the chatbot to be developed.  

    A Reality Check for Chatbots or Humans?

    By

    Apac CIOOutlook | Monday, July 29, 2019

    Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

    The noise surrounding the phenomenon that AI-powered chatbots will replace human beings is a scenario that is imaginary at present. But, there exists no technology to mimic the workings of the human brain. The process of decoding the hype around chatbots to understand the functioning.

    FREMONT, CA: The latest generation of Chatbots is acknowledged as smart dialogue systems driven by techniques like NLP and fixed conversation flows. The out of the box chatbot does not hail from a specific domain; it needs rigorous training. Even though it has been trained, the concept of understanding the different contexts of the same word is impossible for the NLP implemented to resolve.

    Some difference which exists between the chatbot and real human intelligence are:

    • Ingest And Know-It-All Chatbot:

    Chatbots in simplification are digital libraries of information about the particular domain it has been incorporated into function. These digital libraries packed with information converse or react to the users with the Natural Language Processing (NLP) implemented in the program.

    • Self-Learning Chatbots:

    The terminology often used can sometimes be misleading as the “Self-Learning Chatbot” do not learn on its own. Chatbots need to be trained, to capture the user behavior details through interaction, the user analytics information like the tastes/choices of the user through implicit or explicit means.

    See Also: Top Chatbot Solution Companies

    Once the user behavior is identified, and data is collected, the chatbot finds the nearest match from the trained knowledge and recommends it to the user. A recommendation algorithm built in the chatbot represents the quality of the suggestions imparted by the chatbot.

    The chatbots also need different recommendation algorithms for different domains, and that is the essential part of the chatbot to be developed. Along with recommendation algorithms, the hypotheses, data, and feedback, all of which has equal scope for design and development, and none of the above can be carried out by the chatbot on its own. 

    • General Purpose, Generative Chatbots:

    A chatbot which is capable of learning newer concepts from the basics and respond like a human is possible, but it would not comply with the conversational norms or social rules. A chatbot having access to the social media profiles, banking details, and personal information to enhance the learning quotient is a chatbot to be aware of. It has the power to expose private information and posts freely from social media without filtering the societal quotient. AI can learn infinitesimally but cannot think on its own. The chatbots are formulating the responses based on a probability of words, creating a grammatically correct sentence, which lacks an understanding of the solution and is completely based on mathematical algorithms.

    Check Out: Top Virtual Assistant Companies 

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