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The latest evolution of AI chatbots, often referred
to as “intelligent virtual assistants” or “virtual agents,”
can not only understand free-flowing conversation through use of
sophisticated language models, but even automate relevant tasks.
Such chatbots often use deep learning and natural language processing, but simpler chatbots have existed for decades.

By initiating conversations at the right moment,
such as when a visitor appears interested in a particular service
or product, chatbots can turn casual browsing into meaningful interactions.
Furthermore, chatbots can be deployed on landing pages to boost
conversion rates by guiding users through the buying process or answering any questions they might have.
These AI-powered chatbots can be integrated into
websites, apps, or messaging platforms to provide reliable
customer support. Generative models enable the chatbot to generate relevant responses in real-time, rather than relying on pre-set scripts.

AI chatbots differ from standard chatbots in that they leverage large language models (LLMs) versus traditional conversation flows and pre-programmed responses to generate responses to text
and voice inputs. Before the advent of chatbots, any customer questions, concerns or complaints, big or
small, required a human response. Deep learning capabilities enable AI chatbots to become more
accurate over time, which in turn enables humans
to interact with AI chatbots in a more natural, free-flowing way without being misunderstood.
Modern AI chatbots now use natural language
understanding (NLU) to discern the meaning of open-ended user input, overcoming anything from typos to translation issues.

References:
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