What Is LLMOps?

Large language models (LLMs), a subcategory of generative AI, have taken the world by storm. Commonly known for their application in ChatGPT, LLMs have unleashed new energy among developers and businesses looking to integrate AI into their applications. But the internet is also full of disjointed information about LLM applications and how to integrate and deploy them reliably into products and applications.

In this report, Abi Aryan takes you through the process of developing a cohesive framework for efficiently and reliably using LLMs to supercharge your applications. It's ideal for data scientists, machine-learning engineers, data engineers, and software engineers.

You'll examine:

• The difference between LLM demos and efficient ML products that require a more robust framework
• How LLMs like GPT-4 can be incredibly complex and resource-intensive
• Key challenges of operationalizing LLMs, including massive data requirements, model size and complexity, performance monitoring, and security and privacy

About the author:

Abi Aryan is an independent consultant with more than 7 years of experience using and adapting ML research to solve real-world engineering challenges.