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.”
Chatbots: 10 years of development
Chatbots have been in development for over 10 years, 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:
- Data shortage: There usually aren’t enough “clean” questions and answers to train a language model well. This limits the model’s capabilities.
- Limited knowledge: 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.
- Time-consuming retraining: If info changes, the model must be retrained, which is a time- and resource-intensive process.
GPT technology: a new paradigm
GPT technology represents a new approach. Unlike traditional chatbots, no separate model training is needed for a company-customized GPT. 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.
This means a company gets an AI as intelligent as ChatGPT, but with the added ability to answer company-specific questions. It’s also important to note that, unlike traditional chatbots, there is no need to retrain the model – answers update immediately as the documents change.
Therefore, a company-specific GPT assistant represents a completely new approach to chatbots, offering greater flexibility, better response quality, and lower resource costs, making it an ideal tool for increasing efficiency.
