AI fundamentals

Welcome! If you’re new to AI, you don’t need a technical background to get started. What helps most is a simple map of the landscape—so you can understand what AI systems can do, how they’re packaged, and how to choose the right tool for your needs.

What is AI?

Artificial intelligence (AI) is a broad category of software that can recognize patterns, learn from data, and produce useful outputs. 

You’ve probably seen AI show up in everyday moments, like when:

• Your map app reroutes you around traffic

• Your bank flags a purchase as “unusual”

• A customer support chatbot answers common questions

AI is a category—not one single tool. Within that category are models: trained systems that learn from data and then apply what they’ve learned to new situations. Some models specialize in speech, vision, or forecasting. 

You’re likely starting your AI journey by using conversational AI tools, like ChatGPT. The models behind ChatGPT specialize in language—these are called large language models.

Understanding how large language models work

A large language model (LLM) is a model designed to work with language. It learns patterns from large amounts of text from many sources so it can generate and transform text in helpful ways. An LLM doesn’t “know” things the way a person does. Instead, it predicts the most likely next piece of language based on context. Over time, advances in computing power, training methods, and access to large datasets made it possible to build larger and more capable large language models. 

OpenAI and other frontier research labs build these models as a core part of their offerings, then make them available through user-facing products (like ChatGPT or Codex) and through APIs, which let developers use those models to build their own AI tools and integrate AI into existing software.

How models evolve over time

Reasoning and non-reasoning models

Summary

Here’s the simple hierarchy: