What is Foundation Models?

Foundation models are large, pre-trained AI models that can be adapted or fine-tuned for a wide range of downstream tasks. They are typically trained on massive datasets of unlabeled data using self-supervised learning techniques. Common uses include natural language processing (NLP) tasks like text generation, translation, and summarization, as well as computer vision tasks like image classification and object detection. Their ability to be adapted to various tasks with minimal task-specific training data makes them highly versatile and powerful.