{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"Few-Shot Learning — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"

AI Glossary — gaks.ai

Few-Shot Learning

The ability of a model to learn a new task or adapt to new examples from just a small number of demonstrations, typically between two and around twenty. In the context of large language models, few-shot learning often refers to providing a handful of examples within the prompt itself, allowing the model to infer the pattern without any weight updates. See also: in-context learning, zero-shot learning, prompt engineering.

Source: gaks.ai/glossary/few-shot-learning →
"}