The term 'parameter' is fundamental to understanding Large Language Models (LLMs) like GPT-4. According to MIT Technology Review, parameters are the internal variables that a model learns from training data. Essentially, they are the 'knobs' or weights the AI adjusts to recognize patterns, generate text, and make predictions.

The sheer volume of parameters—often numbering in the hundreds of billions or even trillions—is what gives modern AI its immense power and capability to handle complex tasks. However, this complexity also makes models harder to interpret. Understanding parameters is crucial for grasping why some models are smarter than others and highlights the massive computational resources required to build them.

This concept is central to the current AI arms race, where bigger models with more parameters often equate to better performance.