Large Language Model (LLM)

A sophisticated type of deep learning model trained on massive amounts of text to understand and generate human-like language. LLMs are the engines behind modern medical chatbots and note-generation tools. "Large" generally refers to the model's capacity measured by the number of parameters and to the enormous datasets it is trained on.

LLMs use deep learning algorithms to create models (see also machine learning model pre-trained on massive text datasets for the general purpose of analyzing and learning patterns and relationships among characters, words and phrases to perform text-based tasks. There are generally two types of LLMs: 

• generative models
  make text predictions based on the probabilities of word sequences learned from training data (generative Al) 

• discriminative models
  make classification predictions (predictive AI) based on probabilities of data features and weights learned from training data. 

Small Language Models

A smaller version of their better-known and larger counterparts, large language models. Small is a reference to the size of the models. They have fewer parameters and require a much smaller training dataset, optimizing them for efficiency and better suiting them for deployment in environments with limited computational resources or for applications that require faster training and inference time.