As more companies adopt large language models (LLMs) to address valuable business opportunities, planning ahead to how the model will be deployed and used is key to realizing long-term value.

In this recorded webcast, we considered some unique challenges to deploying artificial intelligence in general, and large language models in particular, into use across your business. From evaluating models and ensuring consistent quality outputs, to optimizing models with a view to managing performance and cost, we shared real-world challenges from customer implementations, and some of the strategies you can use to ensure your model delivers real value for your business. We show how tools like MLflow integrate best practices from MLOps and extend to LLMOps, to support the technical development and management of models throughout the project lifecycle.

What we covered:

• Considerations for deploying and maintaining LLMs in production.
• Introduction to LLMOps, and its significance in supporting operational use of models within your business processes.
• Practical suggestions around model evaluation, monitoring, performance and cost management.

Is it for you?

• Are you investigating the use of large language models to assist with your business processes?
• Are you building models and want to understand the considerations for deploying them for production use?
• Are you excited about the potential of AI, but concerned about the cost of running large models, or the challenge of managing a solution that produces qualitative outputs?