Artificial Intelligence: refers to actions that mimic human intelligence displayed by machines and to the field of study focused on this type of intelligence. AI consists of computer programs that are typically built to adaptively update and enhance their own performance over time. They are used to process, analyze, and recognize patterns in large datasets, and they use those patterns to get better at completing tasks or solving problems.

Generative AI: is a system of algorithms or computer processes that can create novel output in text, images or other media based on user prompts. These systems are created by programmers who train them on large sets of data. The AI learns by finding patterns in the data and can then provide novel outputs to users’ queries based on its findings. Examples include ChatGPT, Bing, and Microsoft Co-Pilot

Machine Learning: Machine learning is a type of artificial intelligence that involves sophisticated algorithms which can be trained to sort information, identify patterns, and make predictions within large data sets without being explicitly programmed to do so.

~The above definitions were taken from the National Library of Medicine~

Traditional AI: relies on pre-programmed rules and algorithms to perform specific tasks. It’s good at solving well-defined problems and repetitive tasks, but unlike Generative AI, it can’t adapt to new situations or create new ideas. Examples include voice assistants such as Siri and Alexa or Google’s search engine.