How does the underlying architecture of Chat GPT, such as GPT-3.5, work?
The GPT-3.5 architecture builds upon the transformer-based model known as the Generative Pre-trained Transformer (GPT). It consists of multiple layers of self-attention mechanisms and feed-forward neural networks. The model is pre-trained on a massive amount of text data, using an unsupervised learning approach to learn the statistical patterns and relationships in the data. During pre-training, the model learns to predict the next word in a sentence given the previous context. This process enables the model to capture semantic and syntactic information, as well as long-range dependencies in text. The GPT-3.5 model has 175 billion parameters, which allows it to generate coherent and contextually relevant responses.
