🚀 KV Cache: The Secret Weapon Making Your LLMs 10x Faster

Author(s): MahendraMedapati

Originally published on Towards AI.

Why Your AI Apps Are Painfully Slow (And How to Fix It)

Picture this: You’re building the next revolutionary AI chatbot. You’ve got the latest LLM running locally, users are excited, but then… disaster. Each response takes 3 minutes to generate. Users abandon your app faster than they found it. Sound familiar?

This article discusses the importance of KV Cache in optimizing LLM (large language model) applications to significantly improve response times and user experience. It explains the challenges faced without KV Cache, such as lengthy token generation times and high computational costs. Understanding and implementing KV Cache emerges as crucial, particularly in scenarios involving multiple queries or users, with practical examples and tips for efficient deployment provided throughout the article.

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