what are foundation models in generative ai

Foundation models are large deep learning neural networks that are trained on massive datasets using self-supervised learning to create labels from input data. They are a form of generative artificial intelligence (generative AI) that can generate output from one or more inputs (prompts) in the form of human language instructions. Foundation models are capable of performing a wide variety of general tasks such as understanding language, generating text and images, and conversing in natural language. They are trained on broad data sets that are generally unlabeled and can be adapted and fine-tuned for a wide variety of applications and downstream tasks. Foundation models are known for their generality and adaptability, and they are poised to significantly change the machine learning lifecycle. Rather than developing artificial intelligence (AI) from scratch, data scientists use a foundation model as a starting point to develop ML models that power new applications more quickly and cost-effectively.