Artificial Intelligence – Language and Text

A major endeavor of AI and machine learning has been reasoning about natural language.

Under the larger topic of "natural language processing" (NLP), these methods are comprised both non-generative methods to analyze various aspects of natural language and generative methods to create new text for other purposes. This is also adjacent to the field of "computational linguistics," the use of computation for modeling natural language.

Non-generative methods include tasks like:

• sentiment analysis – Extracting a quantitative sense of emotion from text.
• sentence similarity - Computing values that represent how similar two sentences are in meaning or structure.
• token classification - Assigning labels to words, like parts of speech or named entities.

Generative methods include tasks like:

• text generation - Generating text to complete a given prompt.
• summarization - Generating text that represents the original meaning of a longer text.
• translation - Generating semantically similar text using a different natural language from the source text.

Contents

1. Text Generation with Large Language Models
2. LLM Chat
3. Code Generation with LLMs
4. Function Calling with LLMs

Upcoming Modules

1. LLM Prompting Tactics
2. Non-Generative Text Methods