Interested in diving deeper into the world of large language models (LLMs) and their real-life applications? In this session, we bring together our experienced team members and some of our esteemed customers to talk about their journey with LLMs. We'll delve into the complexities of getting these models to perform accurately and efficiently, the challenges, and the dynamic nature of LLM technology as it constantly evolves. This engaging conversation will offer you a broader perspective on how LLMs are being applied across different industries and how they’re revolutionizing our interaction with technology. Whether you're well-versed in AI or just beginning to explore, this session promises to enrich your understanding of the practical aspects of LLM implementation.

Talk by: Sai Ravuru, Eric Peter, Ankit Mathur, and Salman Mohammed

Here’s more to explore: LLM Compact Guide: https://dbricks.co/43WuQyb Big Book of MLOps: https://dbricks.co/3r0Pqiz

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

With the recent surge in popularity of ChatGPT and other LLMs such as Dolly, many people are going to start training, tuning, and deploying their own custom models to solve their domain-specific challenges. When training and tuning these models, there are certain considerations that need to be accounted for in the MLOps process that differ from traditional machine learning. Come watch this session where you’ll gain a better understanding of what to look out for when starting to enter the world of applying LLMs in your domain.

In this session, you’ll learn about:

• Grabbing foundational models and fine-tuning them
• Optimizing resource management such as GPUs
• Integrating human feedback and reinforcement learning to improve model performance
• Different evaluation methods for LLMs

Talk by: Joseph Bradley and Eric Peter

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc