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The Data and AI Summit is just around the corner, promising an unparalleled opportunity to delve into the world of artificial intelligence (AI) and machine learning (ML). This year’s Summit will have hundreds of sessions for people to attend - including many of them dedicated to Generative AI and Large Language Models (LLMs). You’ll get to learn about the innovations that our teams have been working on for the last several months, covering the end-to-end AI/ ML lifecycle and simplifying the path of building and productionizing AI solutions. There are also dedicated training sessions to get skilled in all things AI/ ML, including dedicated training on LLMs. While you can explore all the training and sessions here, we have pulled a select list of our must-attend sessions! We can’t wait to see you at the Data and AI Summit.

You'll also hear directly from customers, such as Adidas and Comcast, about their AI/ ML use cases and how they are using Lakehouse AI to deliver AI solutions faster.

AI wordmap
Word cloud of the select AI sessions at summit

We are excited to see you at Summit and learn how Lakehouse AI can help you accelerate your AI and ML solutions.

Maximizing Value From Your Data with Lakehouse AI

Discover how a data-centric AI environment simplifies the ML lifecycle with standardized tools, frameworks, and governance across your lakehouse data. 

Learn How to Reliably Monitor Your Data and Model Quality in the Lakehouse

This session shows how you Lakehouse Monitoring can combine with powerful governance and lineage tools like Unity Catalog to monitor your data quality, features, and models to gain a comprehensive view of your lakehouse.

Navigating the Complexities of LLMs: Insights from Practitioners
Come delve into a panel session with some of our customers to discuss the complexities of getting LLMs to perform accurately and efficiently, the challenges, and the dynamic nature of LLM technology as it constantly evolves.

Deep Dive into the latest Lakehouse AI Capabilities

Take a deeper look into the various features of Lakehouse AI and see how they all tie together to help train, deploy, and monitor your AI projects on the lakehouse.

Building LLMs on Your Company's Data on a Budget

Discover the potential of LLMs for your business as we explore practical applications and strategies to leverage cutting-edge technology in real-world scenarios.

Advancements in Open Source LLM Tooling, including MLflow 

In this session, explore MLflow's seamless integration with leading generative AI tools like Hugging Face, LangChain, and OpenAI to build AI pipelines effortlessly.

LLMOps: Everything You Need to Know to Manage LLMs

Explore the inner workings and practical considerations of deploying large language models in real-world production environments, gaining valuable insights on architecture and integration into your lakehouse.

Adidas ML journey: Accleraring ML in production using Databricks

Learn how Adidas leveraged Databricks, Jenkin and MLflow to build an ML template to accelerate model deployment.

How the Texas Rangers Revolutionized Baseball Analytics with a Modern Data Lakehouse

Learn how the Texas Rangers baseball team organized their predictive models using MLflow and ML Registry with Databricks.

Improving Hospital Operations with Streaming Data and Real-Time AI/ML

Learn how Providence Health streamlined clinical operations across 52 hospitals and 100 ambulatory clinics leveraging AI on the lakehouse.

Unleashing Large Language Models with Databricks SQL's AI Functions

Come see how AI Functions democratizes AI and puts the power of LLMs directly into the hands of your data analysts and scientists.

MLOps at Gucci: From Zero to Hero

Discover how Gucci leveraged Databricks to streamline the deployment of a data science tool for media budget allocation, including code versioning, automated processes, model monitoring, and result visualization.

IFC's MALENA Provides Analytics for ESG Reviews in Emerging Markets Using NLP and LLMs

Explore how International Finance Corporation (IFC) is using ML on the lakehouse to build machine learning solutions that enable the review of ESG issues at scale.

Training: Deep Learning with Databricks - Two-day training focused on the basics of neural networks and how to build and deploy LLMs