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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

To overcome these limitations, we propose a solution that combines RAG with metadata and entity extraction, SQL querying, and LLM agents, as described in the following sections. Typically, these analytical operations are done on structured data, using tools such as pandas or SQL engines.

SQL 119
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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

A provisioned or serverless Amazon Redshift data warehouse. Basic knowledge of a SQL query editor. Implementation steps Load data to the Amazon Redshift cluster Connect to your Amazon Redshift cluster using Query Editor v2. For this post we’ll use a provisioned Amazon Redshift cluster. A SageMaker domain.

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Snowflake Snowpark: cloud SQL and Python ML pipelines

Snorkel AI

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

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Snowflake Snowpark: cloud SQL and Python ML pipelines

Snorkel AI

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52
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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Enter a stack name, such as Demo-Redshift. yaml locally.

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phData Toolkit August 2023 Update

phData

Over the last month, we’ve been heavily focused on adding additional support for SQL translations to our SQL Translations tool. Specifically, we’ve been introducing fixes and features for our Microsoft SQL Server to Snowflake translation. This is where the SQL Translation tool can be a massive accelerator for your migration.

SQL 52
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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

Database 158