Databricks helped unite data engineers and data scientists for AI innovation by integrating generative AI capabilities with robust data engineering workflows on its unified Lakehouse Platform. Databricks enables efficient data preparation, scalable training, and fine-tuning of large language models (LLMs) using real enterprise data. Its MLflow tool tracks experiments, while serverless model serving accelerates deployment. Features like Retrieval-Augmented Generation (RAG) ensure AI models use up-to-date, context-rich data, driving accurate and business-relevant AI applications at scale.

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