Introduction to Large Language Models

updated 29 Sep 2023

John Ewald from Google Cloud explains that large language models (LLMs) are a subset of deep learning, intersecting with generative AI. LLMs are versatile models trained for general language tasks and can be fine-tuned for specific applications. The concept is broken down into three key features: "Large" refers to both the extensive training data and parameter count, "general purpose" indicates their suitability for common language problems, and "pre-trained and fine-tuned" describes the process of initially training on a broad dataset and then refining for specific tasks using smaller datasets. The benefits of using such models are highlighted.

Introduction to Large Language Models

Benefits of using Large Language Models

Pathways Language Model (PaLM)

LLM Development vs. Traditional Development

What are Prompts and Prompt Engineering?

Chain of Thought Reasoning

Model Garden Task Specific Models

More efficient methods of tuning

If you enjoyed this, checkout A Hackers Guide to Large Language Models