Term: Few-Shot Learning
Day: 13
Level: Fluency
Category: Learning & Models
🪄 Simple Definition:
Teaching an AI to do a task by showing it just a few examples instead of thousands.
🌟 Expanded Definition:
Few-shot learning is a technique where a model learns to perform a task with very limited examples. Instead of needing huge datasets, the model adapts quickly from a handful of inputs, often by leveraging the general knowledge it already gained during pre-training. This is especially useful in areas where data is scarce or expensive to label.
⚡ In Action:
A chatbot is given only 5 examples of how to politely decline requests. After seeing those, it can consistently generate polite refusals in many different situations.
💡 AIS+ Pro Tip:
Use few-shot learning when you want quick adaptability without the cost of full fine-tuning. Try pairing it with Prompt Engineering by including examples directly in your prompt to steer model behavior.
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