A Beginners Guide to Key Large Language Model Terms With Examples
1. Generative AI:
Generative AI models are designed to produce new, original content based on their training data. They can create a variety of outputs, from text and images to music.
Example: Consider a Generative AI trained on classical music. When prompted, it can compose a new piece of music that sounds classical but is entirely original and wasn’t part of its training data.
2. Large Language Model (LLM):
LLMs are trained on vast amounts of text data, enabling them to understand the context and generate human-like text. They can answer questions, write essays, and even generate poetry.
Example: If you ask an LLM, “Write a short poem about the moon,” it might produce:
Silver orb in the night sky,
Casting shadows, shining high.
Guardian of dreams, so bright,
Guiding us with gentle light.3. Tokens:
In LLMs, a token can represent a character, a word, or anything in between. Tokens are the building blocks the model reads.
Example: The sentence “ChatGPT is fun!” is tokenized into
[“Chat”, “G”, “PT”, “ is”, “ fun”, “!”].
