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Build a read-through semantic cache with Amazon OpenSearch Serverless and Amazon Bedrock

AWS Machine Learning - AI

In the field of generative AI , latency and cost pose significant challenges. The commonly used large language models (LLMs) often process text sequentially, predicting one token at a time in an autoregressive manner. This post presents a strategy for optimizing LLM-based applications.

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Building Generative AI prompt chaining workflows with human in the loop

AWS Machine Learning - AI

Generative AI is a type of artificial intelligence (AI) that can be used to create new content, including conversations, stories, images, videos, and music. Like all AI, generative AI works by using machine learning models—very large models that are pretrained on vast amounts of data called foundation models (FMs).

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Improving air quality with generative AI

AWS Machine Learning - AI

More than 170 tech teams used the latest cloud, machine learning and artificial intelligence technologies to build 33 solutions. The fundamental objective is to build a manufacturer-agnostic database, leveraging generative AI’s ability to standardize sensor outputs, synchronize data, and facilitate precise corrections.

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eSentire delivers private and secure generative AI interactions to customers with Amazon SageMaker

AWS Machine Learning - AI

To accomplish this, eSentire built AI Investigator, a natural language query tool for their customers to access security platform data by using AWS generative artificial intelligence (AI) capabilities. Therefore, eSentire decided to build their own LLM using Llama 1 and Llama 2 foundational models.

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

The emergence of generative AI has ushered in a new era of possibilities, enabling the creation of human-like text, images, code, and more. Solution overview For this solution, you deploy a demo application that provides a clean and intuitive UI for interacting with a generative AI model, as illustrated in the following screenshot.

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Build generative AI–powered Salesforce applications with Amazon Bedrock

AWS Machine Learning - AI

In Part 3 , we demonstrate how business analysts and citizen data scientists can create machine learning (ML) models, without code, in Amazon SageMaker Canvas and deploy trained models for integration with Salesforce Einstein Studio to create powerful business applications.

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Streamline financial workflows with generative AI for email automation

AWS Machine Learning - AI

Intelligent automation presents a chance to revolutionize document workflows across sectors through digitization and process optimization. This post explains a generative artificial intelligence (AI) technique to extract insights from business emails and attachments. These samples demonstrate using various LLMs.