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How DPG Media uses Amazon Bedrock and Amazon Transcribe to enhance video metadata with AI-powered pipelines

AWS Machine Learning Blog

With a growing library of long-form video content, DPG Media recognizes the importance of efficiently managing and enhancing video metadata such as actor information, genre, summary of episodes, the mood of the video, and more. Video data analysis with AI wasn’t required for generating detailed, accurate, and high-quality metadata.

Metadata 116
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How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning Blog

The embedding representations of text chunks along with related metadata are indexed in OpenSearch Service. In this step, the user asks a question about the ingested documents and expects a response in natural language. The application uses Amazon Textract to get the text and tables from the input documents.

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Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

AWS Machine Learning Blog

This layer serves as the cornerstone for secure, compliant, and agile consumption of FMs through the Generative AI Gateway, promoting responsible AI practices within the organization. This table will hold the endpoint, metadata, and configuration parameters for the model.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. Can you compare images?

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Read graphs, diagrams, tables, and scanned pages using multimodal prompts in Amazon Bedrock

AWS Machine Learning Blog

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. However, we’re not limited to using generative AI for only software engineering.

LLM 105
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From concept to reality: Navigating the Journey of RAG from proof of concept to production

AWS Machine Learning Blog

You can use metadata filtering to narrow down search results by specifying inclusion and exclusion criteria. Responsible AI Implementing responsible AI practices is crucial for maintaining ethical and safe deployment of RAG systems. You can use Amazon Bedrock Guardrails for implementing responsible AI policies.

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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning Blog

By investing in robust evaluation practices, companies can maximize the benefits of LLMs while maintaining responsible AI implementation and minimizing potential drawbacks. To support robust generative AI application development, its essential to keep track of models, prompt templates, and datasets used throughout the process.

LLM 114