Few-shot learning

Few-shot learning is a type of machine learning where a model is trained on a very small amount of data. This is in contrast to traditional machine learning, where models are trained on large datasets. Few-shot learning is a key area of research in AI, as it has the potential to make machine learning more accessible and affordable.

Few-shot learning is a key component of any successful AI strategy, as it can help to reduce the cost and complexity of developing and deploying AI systems.