AI News

AUGUST 29, 2023

“If you think about building a data pipeline, whether you’re doing a simple BI project or a complex AI or machine learning project, you’ve got data ingestion, data storage and processing, and data insight – and underneath all of those four stages, there’s a variety of different technologies being used,” explains Faruqui.

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AI News

SEPTEMBER 29, 2024

Additionally, they accelerate time-to-market for AI-driven innovations by enabling rapid data ingestion and retrieval, facilitating faster experimentation. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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AWS Machine Learning Blog

OCTOBER 23, 2024

By automating document ingestion, chunking, and embedding, it eliminates the need to manually set up complex vector databases or custom retrieval systems, significantly reducing development complexity and time. Deploying the agent with other resources is automated through the provided AWS CloudFormation template.

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Snorkel AI

JANUARY 8, 2025

At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform. Ingesting raw data from Databricks into Snorkel Flow Efficient data ingestion is the foundation of any machine learning project. Sign up here!

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AWS Machine Learning Blog

AUGUST 5, 2024

Building and deploying these components can be complex and error-prone, especially when dealing with large-scale data and models. Solution overview The solution provides an automated end-to-end deployment of a RAG workflow using Knowledge Bases for Amazon Bedrock. Choose Sync to initiate the data ingestion job.

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AWS Machine Learning Blog

AUGUST 28, 2024

This post demonstrates how to seamlessly automate the deployment of an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS Cloud Development Kit (AWS CDK), enabling organizations to quickly set up a powerful question answering system. Choose Sync to initiate the data ingestion job.

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Marktechpost

DECEMBER 3, 2024

As generative AI continues to grow, the need for an efficient, automated solution to transform various data types into an LLM-ready format has become even more apparent. Meet MegaParse : an open-source tool for parsing various types of documents for LLM ingestion. Check out the GitHub Page.

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