LLM Adoption in the Enterprise

Chapter 1. AI in the Enterprise

This chapter introduces the intuition behind LLMs, as well as the key concepts from the world of AI and machine learning that are necessary to understand LLMs. Equipped with these concepts, we’ll move on to see the most common uses of LLMs in the enterprise today, before taking a deeper dive into four exemplary projects that encourage a pragmatic understanding of how these language models can be used in industry applications.

AI in Context

As a field that is rapidly evolving and constantly drawing new people into the conversation, many terms in AI (such as “artificial intelligence” itself) aren’t very well defined. Let’s clarify our understanding of them for the purposes of this report.

AI Today Is Mostly Machine Learning

Our everyday use of the word “AI” describes machines that mimic intelligent human behavior. The means by which they do this are not limited to any one technique, and of course intelligence itself is a fuzzy concept. Machine learning (ML), on the other hand, is the study of algorithms that use data to construct models (i.e., predictive representations) of a given domain.

Not all AI is machine learning. But the vast majority of AI technologies making waves today—such as generative AI for images or text—rely on machine learning as their driving force.

An Algorithm Trains a Model with Data

The concepts of algorithms, models, and data are critical in ML. However, their relationship—as well as the nature of an ML model itself—is ...