Towards AI Can Help your Team Adopt AI: Corporate Training, Consulting, and Talent Solutions.

Publication

Speak Only About What You Have Read: Can LLMs Generalize Beyond Their Pretraining Data?
Artificial Intelligence   Data Science   Latest   Machine Learning

Speak Only About What You Have Read: Can LLMs Generalize Beyond Their Pretraining Data?

Last Updated on November 11, 2023 by Editorial Team

Author(s): Salvatore Raieli

Originally published on Towards AI.

Unveiling the Limits and Wonders of In-Context Learning in Large Language Models
Photo by Hans-Peter Gauster on Unsplash

In-context learning is one of the secret weapons that has made Large Language Models so successful, but even today, many points remain unclear. What are the limits of this incredible capability? Where does it come from? Is it the secret ingredient to allows LLMs to bring us closer to artificial general intelligence?

Photo by Thao LEE on Unsplash

One of the most amazing capabilities of Large language models (LLMs) is in-context learning (ICL). By simply providing a few examples to a model, it is able to generate a response, mapping input to output. For example, by providing… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓