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Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

APIs 128
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Transitioning off Amazon Lookout for Metrics 

AWS Machine Learning

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

Metrics 97
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How to decide between Amazon Rekognition image and video API for video moderation

AWS Machine Learning

Amazon Rekognition has two sets of APIs that help you moderate images or videos to keep digital communities safe and engaged. Some customers have asked if they could use this approach to moderate videos by sampling image frames and sending them to the Amazon Rekognition image moderation API.

APIs 87
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Achieve DevOps maturity with BMC AMI zAdviser Enterprise and Amazon Bedrock

AWS Machine Learning

This requires carefully combining applications and metrics to provide complete awareness, accuracy, and control. The zAdviser uses Amazon Bedrock to provide summarization, analysis, and recommendations for improvement based on the DORA metrics data.

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Integrate dynamic web content in your generative AI application using a web search API and Amazon Bedrock Agents

AWS Machine Learning

Amazon Bedrock agents use LLMs to break down tasks, interact dynamically with users, run actions through API calls, and augment knowledge using Amazon Bedrock Knowledge Bases. In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application.

APIs 108
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Real-time analysis of customer sentiment using AWS

AWS Machine Learning

Traditionally, this data is collected via a batch process and sent to a data warehouse for storage, analysis, and reporting, and is made available to decision-makers after several hours, if not days. Use cases for real-time sentiment analysis. The Amazon Comprehend sentiment API identifies the overall sentiment for a text document.

APIs 89
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Accelerate your financial statement analysis with Amazon Bedrock and generative AI

AWS Machine Learning

The financial and banking industry can significantly enhance investment research by integrating generative AI into daily tasks like financial statement analysis. Trend analysis and forecasting – Identifying trends and forecasting requires domain expertise and advanced mathematics.

APIs 122