{"id":5439,"date":"2025-02-05T15:15:13","date_gmt":"2025-02-05T15:15:13","guid":{"rendered":"https:\/\/www.idearespa.eu\/?p=5439"},"modified":"2025-02-05T15:15:13","modified_gmt":"2025-02-05T15:15:13","slug":"il-futuro-gia-presente-della-tecnologia-conversazionale-la-rivoluzione-dei-chatbot","status":"publish","type":"post","link":"https:\/\/www.idearespa.eu\/en\/il-futuro-gia-presente-della-tecnologia-conversazionale-la-rivoluzione-dei-chatbot\/","title":{"rendered":"The (Already Present) Future of Conversational Technology: The Chatbot Revolution\u00a0\u00a0"},"content":{"rendered":"

In recent years, the technological landscape has been dominated by the evolution of artificial intelligence (AI)-based tools, including the CHATBOT<\/strong>capable of answering questions and solving problems in real time. A concrete example of this transformation is the project undertaken by IDEARE<\/strong>.<\/p>\n\n\n\n

The idea of developing a CHATBOT<\/strong> stems from a practical need: to reduce the load of help reports related to the management application REF<\/strong>TREE<\/strong>. In fact, support requests often result not from technical errors, but from users' difficulty in understanding the software's wide range of functionalities.  <\/p>\n\n\n\n

The objective was clear: to provide intuitive support that would allow users to solve common problems themselves, while improving operational efficiency and reducing business costs. The research focused on a tool that was already known, but had to be adapted to the specific needs of the system REF<\/strong>TREE<\/strong>characterised by inherent complexity.  <\/p>\n\n\n\n

The choice of solution and the role of artificial intelligence. <\/strong> <\/p>\n\n\n\n

After a thorough analysis, IDEARE<\/strong> decided to develop a CHATBOT<\/strong> based on artificial intelligence, able to interrogate software operating manuals and provide precise and targeted answers.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/p>\n\n\n\n

The system had to be user-friendly and easily accessible, ensuring a clear and understandable language for all users. This innovative approach led to the realisation of a text-based interface integrating AI services.<\/p>\n\n\n\n

The CHATBOT<\/strong> is designed to operate directly within the web portal used for REFTREE<\/strong>. Thanks to the integration with services provided by ChatGPT<\/strong>the CHATBOT<\/strong> can process input and generate relevant answers by exploiting machine learning and deep learning technologies.<\/p>\n\n\n\n

In particular, ChatGPT<\/strong> uses Natural Language Processing (NLP) algorithms to understand the meaning of users' questions and come up with coherent answers.\u00a0\u00a0<\/p>\n\n\n\n

A simple and intuitive graphic interface<\/strong>.  <\/p>\n\n\n\n

Ease of use was a priority when designing the graphical user interface of the CHATBOT<\/strong>.<\/p>\n\n\n\n

The interface was placed next to the platform's generic help message, making support easily accessible. With a minimalist and intuitive design, users can quickly select the area and process of interest and receive relevant and immediate answers.\u00a0\u00a0<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Integration with the web portal required the development of a dedicated web service, which allows the CHATBOT<\/strong> to interact with the user in a smooth and seamless manner. This approach was key to ensuring an optimal user experience, minimising technical difficulties and improving the effectiveness of the support provided.<\/p>\n\n\n\n

Technology behind the CHATBOT<\/strong> <\/strong> <\/p>\n\n\n\n

The technological heart of the CHATBOT<\/strong> is represented by ChatGPT<\/strong>an advanced artificial intelligence model developed by OpenAI.<\/strong><\/p>\n\n\n\n

ChatGPT<\/strong>which stands for Chat Generative Pretrained Transformer, is a system based on machine learning and deep learning, enabling it to learn autonomously from the input received from users. Thanks to NLP algorithms, the CHATBOT<\/strong> can analyse and understand natural language, responding in an accurate and relevant manner.\u00a0\u00a0<\/p>\n\n\n\n

Main technical specifications<\/strong> :                                                                                                                           <\/strong> <\/p>\n\n\n\n

    \n
  • Language model<\/strong>: ChatGPT-4\u00a0\u00a0<\/li>\n<\/ul>\n\n\n\n
      \n
    • Architecture<\/strong>: Transformers pre-trained on billions of parameters\u00a0\u00a0<\/li>\n<\/ul>\n\n\n\n
        \n
      • Basic technologies<\/strong>Machine Learning, Deep Learning, and Natural Language Processing (NLP)\u00a0<\/li>\n<\/ul>\n\n\n\n
          \n
        • Training Dataset<\/strong>: Extensive up-to-date multilingual corpus, including technical manuals, user documentation and dynamic content\u00a0\u00a0<\/li>\n<\/ul>\n\n\n\n
            \n
          • API Integration<\/strong>: Web service designed by QBT for direct calls to the model\u00a0\u00a0<\/li>\n<\/ul>\n\n\n\n
              \n
            • Speed of response<\/strong>Less than 2 seconds for the 90% of standard requests\u00a0\u00a0<\/li>\n<\/ul>\n\n\n\n

              The machine learning process allows the CHATBOT<\/strong> to constantly improve its performance. Every interaction with users represents a learning opportunity, allowing the system to refine its responses and adapt to the specific needs of the context in which it is used.  <\/p>\n\n\n\n

              <\/p>\n\n\n\n

              Use<\/strong><\/h2>\n\n\n\n

              The Bot<\/strong> answers following the user's selection of the area and process of interest and the specific question on the topic requested. If an incorrect question is formulated, the Bot, which has been instructed with specific manuals, will not give the answer but will ask you to rephrase it.\u00a0\u00a0<\/p>\n\n\n\n

              \"\"<\/figure>\n\n\n\n
              \"\"<\/figure>\n\n\n\n

              Method of instruction and supervision <\/strong> <\/p>\n\n\n\n

              The machine learning process allows the CHATBOT<\/strong> to constantly improve its performance. Every interaction with users represents a learning opportunity, allowing the system to refine its responses and adapt to the specific needs of the context in which it is used.  <\/p>\n\n\n\n

              The success of a CHATBOT<\/strong> depends to a large extent on the quality of the information on which it is based.<\/p>\n\n\n\n

              In the case of REFTREE<\/strong>the CHATBOT<\/strong> was trained using the manuals produced by IDEARE<\/strong>which includes a wide range of detailed information on how the software works. A dedicated working group regularly analyses the answers provided by the CHATBOT<\/strong>monitoring interactions through a log that records all queries made.\u00a0\u00a0<\/p>\n\n\n\n

              <\/p>\n\n\n\n

              Users also have the option of evaluating the responses received via a feedback system based on thumbs-up or thumbs-down buttons. This function is essential to identify any areas for improvement and to ensure that the CHATBOT<\/strong> continue to provide high quality answers.\u00a0\u00a0<\/p>\n\n\n\n

              In the future, IDEA<\/strong>RE<\/strong> <\/strong>plans to set up a dedicated supervision department, which will correct and supplement the manuals and update the instructions given to the CHATBOT<\/strong>. Thanks to the 'Administrator' interface developed by QBT<\/strong>it will be possible to efficiently manage the update process and ensure that the CHATBOT<\/strong> remains aligned to the needs of users.  <\/p>\n\n\n\n

              An evolving success. <\/strong> <\/p>\n\n\n\n

              Currently, the CHATBOT<\/strong> is operational on the sites of customers using REF<\/strong>TREE<\/strong> and is a concrete example of how artificial intelligence can be used to improve business efficiency. Although the CHATBOT<\/strong> is not yet complete for all areas of the system, the results obtained so far are promising and point to a future in which automated support will become increasingly sophisticated and customised.  <\/p>\n\n\n\n

              The possibility of extending the use of the CHATBOT<\/strong> to other applications developed by the Riina Prime Group<\/strong>further extending the positive impact of this technology. The experience gained with REF<\/strong>TREE<\/strong> may serve as a model for the development of similar solutions in other contexts, demonstrating the potential of artificial intelligence to revolutionise the way companies interact with their customers.  <\/p>\n\n\n\n

              The future of CHATBOTS<\/strong>  <\/p>\n\n\n\n

              I CHATBOT<\/strong> represent one of the most promising technologies of our time, with the potential to radically transform the way we interact with digital systems. The project developed by IDEA<\/strong>RE<\/strong> for REF<\/strong>TREE<\/strong> is a prime example of how a targeted use of artificial intelligence can lead to concrete and measurable results.  <\/p>","protected":false},"excerpt":{"rendered":"

              Negli ultimi anni, il panorama tecnologico \u00e8 stato dominato dall\u2019evoluzione di strumenti basati sull\u2019intelligenza artificiale (AI), tra cui i CHATBOT, capaci di rispondere a domande e risolvere problemi in tempo reale. Un esempio concreto di questa trasformazione \u00e8 il progetto intrapreso da IDEARE. L’idea di sviluppare un CHATBOT nasce da una necessit\u00e0 pratica: ridurre il […]<\/p>\n","protected":false},"author":1,"featured_media":5437,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[24,23],"tags":[],"class_list":["post-5439","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-innovazione-tecnologica","category-refidea"],"_links":{"self":[{"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/posts\/5439","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/comments?post=5439"}],"version-history":[{"count":1,"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/posts\/5439\/revisions"}],"predecessor-version":[{"id":5446,"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/posts\/5439\/revisions\/5446"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/media\/5437"}],"wp:attachment":[{"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/media?parent=5439"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/categories?post=5439"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.idearespa.eu\/en\/wp-json\/wp\/v2\/tags?post=5439"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}