{"id":9218,"date":"2023-03-23T15:25:39","date_gmt":"2023-03-23T12:25:39","guid":{"rendered":"https:\/\/tehisintellekt.ee\/kuidas-erineb-ettevottele-kohandatud-chatgpt-traditsioonilistest-vestlusrobotitest\/"},"modified":"2026-02-01T14:03:54","modified_gmt":"2026-02-01T11:03:54","slug":"how-custom-chatgpt-for-business-differs-from-traditional-chatbots","status":"publish","type":"post","link":"https:\/\/tehisintellekt.ee\/en\/how-custom-chatgpt-for-business-differs-from-traditional-chatbots\/","title":{"rendered":"How custom ChatGPT for business differs from traditional chatbots"},"content":{"rendered":"\t\t
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Chatbots have been used in companies for years to support employees and customers. However, ChatGPT, released at the end of 2022, brought a major shift, being the first to cross the threshold of perceived “usefulness.” <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Chatbots: 10 years of development<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Chatbots have been in development for over 10 years<\/strong>, mostly using a so-called “imitation strategy” – questions and answers in databases are used to train machine learning models to mimic them. This strategy comes with several problems: <\/p>

  1. Data shortage:<\/strong> There usually aren’t enough “clean” questions and answers to train a language model well. This limits the model’s capabilities. <\/li>
  2. Limited knowledge:<\/strong> Since the model is based on existing data, it cannot answer questions it hasn’t seen before. This means the model’s usefulness is limited. <\/li>
  3. Time-consuming retraining:<\/strong> If info changes, the model must be retrained, which is a time- and resource-intensive process.<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    GPT technology: a new paradigm<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    GPT technology represents a new approach. Unlike traditional chatbots, no separate model training is needed for a company-customized GPT<\/strong>. Instead, a pre-trained “smart” model is given access to the company’s existing documents. Data science techniques are then used to select the documents most likely to contain the correct answer. <\/p>

    This means a company gets an AI as intelligent as ChatGPT, but with the added ability to answer company-specific questions<\/strong>. It\u2019s also important to note that, unlike traditional chatbots, there is no need to retrain the model – answers update immediately as the documents change. <\/p>

    Therefore, a company-specific GPT assistant represents a completely new approach to chatbots, offering greater flexibility, better response quality, and lower resource costs<\/strong><\/strong>, making it an ideal tool for increasing efficiency.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    Latest articles<\/b><\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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