Large Language Models explained briefly

The post explains large language models (LLMs), how they function, and the complexities behind their training. LLMs predict the next word in a sequence based on probabilities, using vast amounts of text data for training. The introduction of transformers in 2017 allowed for parallel processing of text, enhancing computation efficiency. Pre-training is supplemented by reinforcement learning with human feedback to refine model predictions. The sheer scale of data and computation involved is formidable, taking advantage of specialized hardware like GPUs.