Zero to generative AI with Databricks and AWS

This article discusses how businesses can leverage tools from Databricks and Amazon Web Services (AWS) to build production-quality generative AI applications and overcome common challenges.

Specifically, the article covers:

• Challenge 1: Choosing the right foundation model by comparing capabilities across models, mixing and matching models, and using model evaluation tools from Databricks and Amazon Bedrock.
• Challenge 2: Improving model performance with business context through Retrieval-Augmented Generation (RAG) using Databricks' Mosaic AI Vector Search, and fine-tuning or continued pre-training of models using Databricks' Mosaic AI Model Training and AWS Trainium.
• Challenge 3: Operationalizing and ensuring model quality by setting safeguards with Amazon Bedrock Guardrails, continuous monitoring with Databricks' Mosaic AI Gateway and Inference Tables, and evaluating outputs using LLM judges and Databricks Lakehouse Monitoring.
• Conclusion: Databricks on AWS offers a comprehensive platform for building production-grade generative AI applications, enabling innovation, scalability, performance, and business alignment.