The Basics
Understanding AI
AI is already woven into many of the tools you use every day, sometimes in ways you might not even notice. Getting familiar with these key terms will help you understand what AI can and cannot do, and make more informed choices about how you use it.
Productivity Tools
AI-powered software you probably already use, like smart email features, grammar checkers, design assistants, and voice helpers like Siri and Alexa.
Generative AI
AI that creates new content, such as text, images, audio, and video, based on patterns it learned from large amounts of training data. ChatGPT and DALL-E are common examples.
Multimodal AI
AI that can work with multiple types of content at once, like reading text, analyzing images, and generating audio in the same conversation.
Large Language Models
The technology behind tools like ChatGPT, Claude, Gemini, and Copilot. Large Language Models (LLMs) are trained on massive text datasets to understand and generate human-like responses.
LLM Implementations
The actual products and apps built on top of LLMs. When you chat with ChatGPT or use Copilot in Word, you are using an LLM implementation.
Machine Learning
A branch of AI where computers learn to perform tasks by finding patterns in data, rather than being explicitly programmed for every scenario.
Deep Learning
A more advanced form of machine learning that uses layered neural networks to tackle complex tasks like image recognition and language translation.
Language Processing
The area of AI focused on understanding and generating human language. It is what allows you to type a question in plain English and get a coherent response.
Computer Vision
AI that can interpret visual information from images and videos, powering features like photo search, facial recognition, and accessibility tools.