Contact: kevin.sebastian@unlv.edu
This guide was developed in part by using ChatGPT-4o, a generative AI language model. It assisted in drafting content, providing recommendations, and refining language to ensure clarity and coherence. All AI-generated text was reviewed and edited for accuracy and relevance to the topic.
Machine learning is a powerful subset of AI that allows computers to learn from data and make predictions or decisions without being explicitly programmed. By analyzing large amounts of information, machine learning models can identify patterns and improve over time. For example, when you use a recommendation system on a website or when AI recognizes images like when your phone automatically tags the faces of people in your photos album, it’s machine learning at work. This technology forms the foundation for many AI applications, including generative AI, enabling systems to create, predict, and learn from experience just like humans.
To further understand how machine learning is an important process in generative AI, watch the 2-minute following video.
Want to see machine learning in action? Try playing Google’s Quick, Draw! game. In this game, the AI tries to guess what you’re drawing by recognizing patterns it has learned from millions of drawings submitted by people worldwide. It’s a fun and interactive way to experience how machine learning works—each time you draw, the AI uses its past training data to predict what your doodle represents. Playing the game will help you better understand how machine learning systems are trained to recognize and respond to new inputs. Give it a try to cement your understanding!