Automate document processing with Amazon Bedrock Prompt Flows (preview)

Favorite Enterprises in industries like manufacturing, finance, and healthcare are inundated with a constant flow of documents—from financial reports and contracts to patient records and supply chain documents. Historically, processing and extracting insights from these unstructured data sources has been a manual, time-consuming, and error-prone task. However, the rise of

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Shared by AWS Machine Learning October 29, 2024

Empower your generative AI application with a comprehensive custom observability solution

Favorite Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics.

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Shared by AWS Machine Learning October 29, 2024

Customized model monitoring for near real-time batch inference with Amazon SageMaker

Favorite Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. Examples include financial systems processing transaction data streams, recommendation engines processing user activity data, and computer vision models processing video frames. In these scenarios, customized model monitoring for

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Shared by AWS Machine Learning October 28, 2024

Import data from Google Cloud Platform BigQuery for no-code machine learning with Amazon SageMaker Canvas

Favorite In the modern, cloud-centric business landscape, data is often scattered across numerous clouds and on-site systems. This fragmentation can complicate efforts by organizations to consolidate and analyze data for their machine learning (ML) initiatives. This post presents an architectural approach to extract data from different cloud environments, such as

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Shared by AWS Machine Learning October 28, 2024

Using Amazon Q Business with AWS HealthScribe to gain insights from patient consultations

Favorite With the advent of generative AI and machine learning, new opportunities for enhancement became available for different industries and processes. During re:Invent 2023, we launched AWS HealthScribe, a HIPAA eligible service that empowers healthcare software vendors to build their clinical applications to use speech recognition and generative AI to

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Shared by AWS Machine Learning October 26, 2024

Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 2

Favorite In Part 1 of this series, we explored best practices for creating accurate and reliable agents using Amazon Bedrock Agents. Amazon Bedrock Agents help you accelerate generative AI application development by orchestrating multistep tasks. Agents use the reasoning capability of foundation models (FMs) to create a plan that decomposes

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Shared by AWS Machine Learning October 26, 2024

Brilliant words, brilliant writing: Using AWS AI chips to quickly deploy Meta LLama 3-powered applications

Favorite Many organizations are building generative AI applications powered by large language models (LLMs) to boost productivity and build differentiated experiences. These LLMs are large and complex and deploying them requires powerful computing resources and results in high inference costs. For businesses and researchers with limited resources, the high inference

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Shared by AWS Machine Learning October 26, 2024