What is Prompt Engineering?

Prompt engineering is the art and science of crafting the input text (the "prompt") provided to a large language model (LLM) to produce the desired output. By carefully choosing the words, phrases, and structure of the prompt, you can influence the model to generate specific types of responses. This process involves understanding how the model interprets the input and making adjustments to guide it toward producing more accurate or creative results.

Matrix Multiplication in LLMs

Matrix multiplication plays a crucial role in the functioning of large language models. When a prompt is input into the model, it is first converted into a numerical form known as embeddings. These embeddings are vectors, and the model processes them using a series of matrix multiplications.

Each layer in the neural network of the LLM performs matrix multiplication on the input vector with a weight matrix. This process transforms the input data step by step, allowing the model to capture complex patterns and relationships in the data. The final output is a vector that is then converted back into text, which forms the response generated by the model.

This entire process is computationally intensive and relies on optimized algorithms to perform matrix multiplication efficiently, especially given the massive size of LLMs.