What Makes ChatGPT Different from Previous Models
A large language model developed by OpenAI, ChatGPT is based on Generative Pre-trained Transformer architecture, specifically the GPT-3.5 architecture. The model is trained on a massive dataset of text, such as books, articles, and websites, to learn the structure, patterns, and relationships between words, and the nuances of natural language.
When given a prompt, such as a question, ChatGPT generates a sequence of text in response that is logically in line with the prompt. It does this by using the context of the prompt and the previous words in the generated response to calculate the probability of possible next words. The model then chooses the word with the highest probability as the next word in the sequence.
ChatGPT uses a technique called “attention” to weigh the importance of different parts of the input when making predictions. This allows the model to focus on specific words or phrases in the input when generating a response, helping it understand the prompt’s meaning and intent.







