What is Few-Shot Prompting?
A prompting method where models are shown a small number of examples to guide their outputs for new tasks.
More about Few-Shot Prompting:
Few-Shot Prompting is a technique where an LLM is given a handful of example inputs and outputs within its prompt, helping it learn the desired pattern, style, or logic for a new task. Few-shot prompting is foundational for chain-of-thought reasoning, system prompts, and on-the-fly model adaptation.
It’s especially useful for zero-code configuration and when large amounts of training data aren’t available.
Frequently Asked Questions
How is few-shot prompting different from fine-tuning?
Few-shot prompting adapts behavior at inference time with prompt examples, while fine-tuning requires model retraining.
What types of tasks benefit from few-shot prompting?
Tasks like code generation, dialogue, math problems, and language translation.
From the blog
Using AI to make learning personal and increase your online course sales
Incorporating AI into your courses allows you to create a personalized learning environment that adapts to each student's needs. This personal touch doesn't just improve the learning experience; it also makes your courses more attractive and can increase sales. Let's explore how AI can make online courses more personal and commercially successful.
Herman Schutte
Founder
Revolutionizing University Engagement with AI Chatbots: A Look at SiteSpeakAI
Explore how universities are leveraging AI chatbots to enhance student engagement and streamline administrative tasks. Discover SiteSpeakAI, a tool that trains chatbots on website content to answer visitor queries.
Herman Schutte
Founder