Foundation models are pre-trained on extensive datasets and consist of vast amounts of parameters, designed to understand language, visuals, or other types of data comprehensively. Their general knowledge allows them to be fine-tuned or adapted to specific tasks like translation or image recognition with minimal additional training. This versatility makes them fundamental in developing applications such as virtual assistants or automated content creation, similar to other pre-trained models but on a much larger and more effective scale.