EDGE OSDEFINITION
Zero-shot learning refers to using an AI model on tasks, or predicting classes it has never seen before. The model uses previously learnt knowledge, contextual information and descriptions of new classes to understand new inputs.
In generative AI, zero-shot learning allows large language models to perform tasks based purely on instructions/prompts. This is useful when trying to make more flexible AI applications as there is no requirement to have labeled examples.
Why Zero-Shot Learning is Important
- Enable the model to be used on new tasks or classes.
- Less need to have labeled examples for specific tasks.
- More flexible AI systems.
- Able to quickly experiment with new AI applications.
Applications of Zero-Shot Learning
- Text classification
- Sentiment analysis using natural language instructions.
- Object/Concept recognition.
- Summary, translation and question answering with LLMs.
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