Understanding Text Completion Process

One of the most important features that makes LLMs stand out is their ability to generate human-like text. This capability is referred to as text completion. Text completion is not merely the ability of LLMs to generate random words; instead, it's the algorithms, the vast amounts of data, and the training that goes behind it that make it so powerful. OpenAI, being the mind behind some of these algorithms, has been at the forefront of conducting research and developing models, making them a leading figure in the text completion space. Throughout this section, we are going to take a look at the magic behind this technology and how it works.

The science behind text completion

When we view text completion from the perspective of artificial intelligence and language modeling, we can describe it as the capability of machines to generate human-like text automatically. What truly occurs behind the scenes is that these completions are predictions made by various models based on the patterns they've discerned from the data on which they were trained. The model will attempt to understand what it's provided, and based on its training data, it will endeavor to produce relevant responses.

How the models generate text

There are a few steps that go into generating text.

1. Training the model
Before any language model can predict or complete text, it first goes under the training phase. The training phase comprises several things, some of which are:

• Data ingestion: The model is first exposed to large amounts of data ranging from textual data which includes books, articles, sites, and any other forms of written ...