Mini toolsDefinition
A learning approach where AI models can learn new tasks from just a few examples unlike traditional methods requiring large datasets.
Detailed Explanation
Few-shot learning enables AI systems to recognize patterns and perform tasks with minimal training examples by leveraging pre-existing knowledge and rapid adaptation capabilities. This approach uses sophisticated neural network architectures and meta-learning techniques to extract maximum information from limited examples and generalize effectively to new situations.
Use Cases
Image classification with limited data rapid prototyping personalized AI systems and specialized industrial applications
