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Narrowing the confidence gap for wider AI adoption

AI News

Avi Perez, CTO of Pyramid Analytics, explained that his business intelligence software’s AI infrastructure was deliberately built to keep data away from the LLM , sharing only metadata that describes the problem and interfacing with the LLM as the best way for locally-hosted engines to run analysis.”There’s

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OpenAI takes steps to boost AI-generated content transparency

AI News

OpenAI is joining the Coalition for Content Provenance and Authenticity (C2PA) steering committee and will integrate the open standard’s metadata into its generative AI models to increase transparency around generated content.

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Metadata filtering for tabular data with Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

However, information about one dataset can be in another dataset, called metadata. Without using metadata, your retrieval process can cause the retrieval of unrelated results, thereby decreasing FM accuracy and increasing cost in the FM prompt token. This change allows you to use metadata fields during the retrieval process.

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Inna Tokarev Sela, CEO and Founder of illumex – Interview Series

Unite.AI

The platform automatically analyzes metadata to locate and label structured data without moving or altering it, adding semantic meaning and aligning definitions to ensure clarity and transparency. Can you explain the core concept and what motivated you to tackle this specific challenge in AI and data analytics?

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LLM-Powered Metadata Extraction Algorithm

Towards AI

This article will focus on LLM capabilities to extract meaningful metadata from product reviews, specifically using OpenAI API. Data processing Since our main area of interest is extracting metadata from reviews, we had to choose a subset of reviews and label it manually with selected fields of interest.

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

Marktechpost

Database metadata can be expressed in various formats, including schema.org and DCAT. ML data has unique requirements, like combining and extracting data from structured and unstructured sources, having metadata allowing for responsible data use, or describing ML usage characteristics like training, test, and validation sets.

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DeepSeek Distractions: Why AI-Native Infrastructure, Not Models, Will Define Enterprise Success

Unite.AI

It can also enable consistent access to metadata and context no matter what models you are using. Explainability and Trust AI outputs can often feel like black boxesuseful, but hard to trust. This enhances trust and ensures repeatable, consistent results. A well nourished semantic layer can significantly reduce LLM hallucinations..

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