ChatGPT is one of the world’s most advanced conversational agents, developed by OpenAI, and built on the groundbreaking pre-trained model which is popularly known as GPT model. As we know that this model is quite proficient in comprehending and creating human like text, this article seeks to unfold the awe-inspiring layers of ChatGPT, how it operates as an intelligent conversational partner, and its various structural components while grasping it’s neural network transformation.
Grasping Chat GPT- What is it:
Chat GPT is an language model AI that enables the user to generate text depending on the prompts given to in. The potential of this application is immense as the scope of text generation tasks is rather broad, and may include answering questions or casual conversations, writing an essay and other creative tasks or even technical support activities. The model is based on a transformer network and has been constructed from extensive data sets, which enable it to accurately guess the succeeding word in a large string of words.
The intricate working and detail-oriented architecture of Chat GPT further aids in deep learning, for a better understanding of its working, let’s analyze it’s generation of responses, the training mechanism and the model structure in depth.
The basic building block for designing neural networks is the Transformer architecture, which was developed Vaswani et al in their 2017 paper “Attention is All You Need”.
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