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Artificial Intelligence

18 September 2023

NLP: the art of communication between humans and machines

The power of conversational Artificial Intelligence has grown exponentially in recent years. But what makes this technology so powerful?

Conversational AI is an area of artificial intelligence that focuses on creating software systems that can communicate with humans using natural language. It is one of the main applications of Natural Language Processing (NLP) and combines various techniques such as machine learning and deep learning to understand, interpret and generate human-like responses. It is used in applications such as virtual assistants and voice-enabled devices, revolutionising the concepts of user experience and human-computer interaction and bridging the gap between people and technology.

One of the main potentials of this technology is its ability to give users effortless access to a wide range of information. Instead of navigating complex interfaces or sifting through huge amounts of data, users can engage in simple natural language conversations with AI systems. This conversational interface allows them to retrieve information quickly and efficiently, and to make informed decisions while staying up-to-date in a fast-moving digital world.

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The benefits of conversational AI platforms

Rewriting the paragraph in bullet points: Conversational AI acts as a virtual assistant . It is able to:

  • support users in performing everyday tasks such as setting reminders, scheduling appointments or making reservations
  • optimise sales processes by fostering greater brand awareness
  • greatly improve interactions with citizens, customers and employees
  • reduce waiting times and provide accurate answers
  • retain users and customers who can count on 24/7 personalised assistance or services.

Another important advantage of this technology is that it has the potential to automate business processes, transforming the modus operandi of organisations. Indeed, when integrated into workflows, routine tasks can be delegated to virtual agents so that human resources can focus on higher-value activities. The result? Optimised business processes and increased productivity.

Coversational AI and Knowledge Technology: a combo for your strategy

The combination of Conversational AI and discovery technologies enables the transformation of the information retrieval process and the experiences of users who have the ability to express their queries through a simple search query and obtain personalised answers in line with their needs.

Conversational artificial intelligence is a powerful resource that can help organisations in multiple ways, but its potential is enhanced when combined with discovery technologies. This synergy has immense power in transforming information retrieval and user experiences. Conversational artificial intelligence enables natural language interactions, allowing users to express their queries and preferences in a conversational manner. Discovery technologies, on the other hand, leverage advanced algorithms and data analysis to deliver highly relevant and personalised results. When these two technologies come together, users can engage in meaningful conversations with AI systems while ensuring accurate and efficient responses.

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As conversational artificial intelligence acts as a catalyst for innovation

As it continues to advance, its impact will transform industries and unlock new possibilities in the evolution of the technological landscape.

The use of Large Language Models (LLM) and, more importantly, their public availability, has drastically changed the landscape of conversational artificial intelligence. With the new capabilities offered by generative artificial intelligence, users’ expectations are skyrocketing and their demands are becoming increasingly demanding. This scenario implies addressing at least the following aspects:

  • The conversation must be as fluid and natural as possible;
  • All requests must be understood and addressed;
  • The answers provided must be accurate and appropriate;
  • The system must have in-depth knowledge and be able to access huge amounts of data;
  • Responses must be provided quickly.

Regardless of the specific use case implemented, conversational technologies generate significant value from interactions in several ways. The simplistic but comprehensive paradigm is that the larger the available data base, the more conversational AI can be trained to perform the greatest number of tasks, offer continuous support, reduce errors and reduce customer service costs.