In this workshop, we'll build an AI application that allows users to perform data queries and extract insights from massive datasets using natural language. We’ll explore the potential of combining Iceberg, Spark and LLMs. We'll start with understanding the structure and architecture of a large dataset. Then we'll look at options for querying the dataset using Apache Spark and Trino. Finally, we'll use an LLM to query the dataset using natural language. We'll also look at other uses of LLMs as part of an overall solution, and explore the differences between different LLMs.

This workshop will give you a real take-home example to take away and explore how to build your own data-driven AI applications. We will use these technologies:
* Apache Iceberg
* Apache Spark
* Trino
* LM Studio for running your own LLM

You will need a laptop with an IDE, Docker, and the ability to install LM Studio and download data and AI models. We'll use Spring Boot and SpringAI as the base for the application.