The ETHFAIbot uses a language model that is capable of answering a wide range of questions and performing various natural language processing tasks. It has been trained on a large corpus of text data, which enables it to provide informative responses and generate human-like text.
It uses deep learning techniques, such as neural networks, and has been fine-tuned for specific tasks like Web3-orientated questions and answers in our case. During the fine-tuning process, we adapted the pre-trained network to the specific task by adjusting the weights in its layers to minimize the prediction error. The fine-tuned model can then be used to generate text or answer questions in a way that is easy to comprehend and relate to.
The chatbot is solely created for one purpose and that is to serve our users to the best extent of their queries and by doing so, guide and help them progress in the Web3 space. The performance of AI is evaluated based on its ability to generate text that is coherent, contextually appropriate, and consistent with the input prompt. The model's accuracy and consistency improve with larger amounts of training data and more advanced deep-learning techniques.
We are continuously working on improving the Web3 and crypto-related functionalities of the chatbot by feeding it massive amounts of text data, using a proven prompt engineering model.