Large language models

Large language models (LLMs) are extensions of deep neural networks that are trained on large datasets and tuned for a vast number of parameters (billions of parameters) and are capable of understanding and generating human-like content. We represent it as follows:

Figure 12.4 – LLMs

Although LLMs can understand other media types as well (such as audio, video, and images), their focus is primarily on understanding textual input and generating textual output. The key difference between LLMs and other query resolvers/chatbots is that LLMs can build an understanding of the overall context by correlating a set of queries (and responses) and can answer complex queries in a more nuanced manner. This enables it to perform tasks such as computer vision (CV) and NLP with a precision that is close to human-generated output.

Training over a large dataset enables these technologies to generate natural (human-like) responses rather than canned...