Remove 2010 Remove Data Pipeline Remove Python
article thumbnail

Improving air quality with generative AI

AWS Machine Learning Blog

The solution harnesses the capabilities of generative AI, specifically Large Language Models (LLMs), to address the challenges posed by diverse sensor data and automatically generate Python functions based on various data formats. The solution only invokes the LLM for new device data file type (code has not yet been generated).

AWS 132
article thumbnail

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

AWS Machine Learning Blog

Overview of RAG RAG solutions are inspired by representation learning and semantic search ideas that have been gradually adopted in ranking problems (for example, recommendation and search) and natural language processing (NLP) tasks since 2010. We use the following Python script to recreate tables as pandas DataFrames.

SQL 126
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

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. He currently is working on Generative AI for data integration.

Database 158
article thumbnail

A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. Both use cases require the ability to move data around the chip quickly and controllably.

AWS 113