Supervised Learning: In supervised learning, the AI system is trained on a labeled dataset, which means that each example in the training set is paired with the correct output. The system learns to predict the output from the input data.

Unsupervised Learning: This involves training the AI system on data without explicit instructions on what to do. It tries to identify patterns and relationships in the data on its own. Project Valvrein

Reinforcement Learning: In reinforcement learning, an AI system learns to make decisions by taking certain actions and receiving rewards or penalties in return. It's akin to learning through trial and error.