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Google AI Introduces Croissant: A Metadata Format for Machine Learning-Ready Datasets

Marktechpost

Even among datasets that include the same subject matter, there is no standard layout of files or data formats. This obstacle lowers productivity through machine learning development—from data discovery to model training. Database metadata can be expressed in various formats, including schema.org and DCAT.

Metadata 118
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Datasets at your fingertips in Google Search

Google Research AI blog

Dataset Search shows users essential metadata about datasets and previews of the data where available. Users can then follow the links to the data repositories that host the datasets. Dataset Search primarily indexes dataset pages on the Web that contain schema.org structured data.

Metadata 116
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Implementing Knowledge Bases for Amazon Bedrock in support of GDPR (right to be forgotten) requests

AWS Machine Learning Blog

This begins the process of converting the data stored in the S3 bucket into vector embeddings in your OpenSearch Serverless vector collection. Also consider storing the metadata of the files being loaded in your knowledge bases for effective tracking. Data discovery and findability Findability is an important step of the process.

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Search enterprise data assets using LLMs backed by knowledge graphs

Flipboard

The application needs to search through the catalog and show the metadata information related to all of the data assets that are relevant to the search context. Solution overview The solution integrates with your existing data catalogs and repositories, creating a unified, scalable semantic layer across the entire data landscape.

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