Abstract
Chat-GPT has become increasingly popular and has provided tremendous help to people in their daily life. The fundamental working principle of Chat-GPT involves the incorporation of various methods such as Natural Language Processing (NLP), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Transformer and Reinforcement Learning from Human Feedback model (RLHF). These methods assist Chat-GPT in understanding, predicting and computing the desired outcomes for the users. NLP is used to help machines understand and process human language. RNN is employed to facilitate the machine in comprehending the input's logic. LSTM enables the control of memory elements, allowing the machine to combine unrelated elements in memory. RLHF serves as a switch button, controlling the machine's output and improving the accuracy of results. Chat-GPT can be used for image editing, coding, translation, paper editing and other tasks. However, it is critical to exercise caution while using Chat-GPT and not to become overly reliant on it, given the potential problems it may create.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
