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Databricks and AWS SageMaker integrate for governed LLM fine-tuning

By PulseAugur Editorial · [1 sources] ·

Databricks and Amazon SageMaker have collaborated to enable fine-tuning of large language models (LLMs) while maintaining strict data governance. This integration allows users to leverage SageMaker's AI training capabilities with data managed by Databricks Unity Catalog, ensuring compliance and visibility. The solution uses Amazon EMR Serverless for data preprocessing and securely accesses governed data, tracks lineage, and registers trained models back into Unity Catalog. AI

IMPACT Enables enterprises to fine-tune LLMs with enhanced data governance and compliance.

RANK_REASON This is a technical integration guide for using existing products together, not a new product launch from a frontier lab.

Read on AWS Machine Learning Blog →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Databricks and AWS SageMaker integrate for governed LLM fine-tuning

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This is a technical integration guide for using existing products together, not a new product launch from a frontier lab.
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COVERAGE [1]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Genta Watanabe ·

    Fine-tune LLM with Databricks Unity Catalog and Amazon SageMaker AI

    In this post, we demonstrate how to build a secure, complete LLM fine-tuning workflow that integrates Unity Catalog with Amazon SageMaker AI using Amazon EMR Serverless for preprocessing. The solution shows how to securely access governed data, maintain lineage across services, f…

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