What is In-Context Learning?
A method where models are guided to perform tasks using examples provided in the input prompt.
More about In-Context Learning:
In-Context Learning enables AI models to perform tasks by including examples or context directly in the input prompt. This approach leverages pre-trained models like PLMs to adapt to new tasks without additional fine-tuning.
In-context learning is particularly effective for tasks like question answering, prompt engineering, and retrieval fusion, where contextual examples guide model behavior.
Frequently Asked Questions
How does in-context learning differ from few-shot learning?
In-context learning provides examples in the input prompt, while few-shot learning involves fine-tuning with minimal labeled data.
What tasks are well-suited for in-context learning?
Tasks like semantic search, context-aware generation, and dialogue systems benefit greatly from in-context learning.
From the blog

ChatGPT 3.5 vs ChatGPT 4 for customer support
Now that the latest version of ChatGPT 4 has been released, users of SiteSpeakAI can use the latest model for their customer support automation. I've put ChatGPT 3.5 and ChatGPT 4 to the test with some customer support questions to see how they compare.

Herman Schutte
Founder

Interview With The Founder Of SiteSpeakAI
SafetyDetectives recently had an interview with Herman Schutte, the innovative founder of SiteSpeakAI, to delve into his journey and the evolution of his groundbreaking platform.

Shauli Zacks
Contributor