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Implementing advanced prompt engineering with Amazon Bedrock

Implementing advanced prompt engineering with Amazon Bedrock

Despite the ability of generative artificial intelligence (AI) to mimic human behavior, it often requires detailed instructions to generate high-quality and relevant content. Prompt engineering is the process of crafting these inputs, called prompts, that guide foundation models (FMs) and large language models (LLMs) to produce desired outputs. Prompt templates can also be used as …

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Accelerate Generative AI Inference with NVIDIA NIM Microservices on Amazon SageMaker

Accelerate Generative AI Inference with NVIDIA NIM Microservices on Amazon SageMaker

This post is co-written with Eliuth Triana, Abhishek Sawarkar, Jiahong Liu, Kshitiz Gupta, JR Morgan and Deepika Padmanabhan from NVIDIA.  At the 2024 NVIDIA GTC conference, we announced support for NVIDIA NIM Inference Microservices in Amazon SageMaker Inference. This integration allows you to deploy industry-leading large language models (LLMs) on SageMaker and optimize their performance and …

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Celebrating the final AWS DeepRacer  League championship and road ahead

Celebrating the final AWS DeepRacer League championship and road ahead

The AWS DeepRacer League is the world’s first autonomous racing league, open to everyone and powered by machine learning (ML). AWS DeepRacer brings builders together from around the world, creating a community where you learn ML hands-on through friendly autonomous racing competitions. As we celebrate the achievements of over 560,000 participants from more than 150 …

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Provide a personalized experience for news readers using Amazon Personalize and Amazon Titan Text Embeddings on Amazon Bedrock

Provide a personalized experience for news readers using Amazon Personalize and Amazon Titan Text Embeddings on Amazon Bedrock

News publishers want to provide a personalized and informative experience to their readers, but the short shelf life of news articles can make this quite difficult. In news publishing, articles typically have peak readership within the same day of publication. Additionally, news publishers frequently publish new articles and want to show these articles to interested …

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Implementing tenant isolation using Agents for Amazon Bedrock in a multi-tenant environment

Implementing tenant isolation using Agents for Amazon Bedrock in a multi-tenant environment

The number of generative artificial intelligence (AI) features is growing within software offerings, especially after market-leading foundational models (FMs) became consumable through an API using Amazon Bedrock. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and …

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Connect the Amazon Q Business generative AI coding companion to your GitHub repositories with Amazon Q GitHub (Cloud) connector

Connect the Amazon Q Business generative AI coding companion to your GitHub repositories with Amazon Q GitHub (Cloud) connector

Incorporating generative artificial intelligence (AI) into your development lifecycle can offer several benefits. For example, using an AI-based coding companion such as Amazon Q Developer can boost development productivity by up to 30 percent. Additionally, reducing the developer context switching that stems from frequent interactions with many different development tools can also increase developer productivity. …

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Elevate customer experience through an intelligent email automation solution using Amazon Bedrock

Elevate customer experience through an intelligent email automation solution using Amazon Bedrock

Organizations spend a lot of resources, effort, and money on running their customer care operations to answer customer questions and provide solutions. Your customers may ask questions through various channels, such as email, chat, or phone, and deploying a workforce to answer those queries can be resource intensive, time-consuming, and unproductive if the answers to …

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Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS CDK

Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS CDK

Retrieval Augmented Generation (RAG) is a state-of-the-art approach to building question answering systems that combines the strengths of retrieval and generative language models. RAG models retrieve relevant information from a large corpus of text and then use a generative language model to synthesize an answer based on the retrieved information. The complexity of developing and …

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Index website contents using the Amazon Q Web Crawler connector for Amazon Q Business

Index website contents using the Amazon Q Web Crawler connector for Amazon Q Business

Amazon Q Business is a fully managed service that lets you build interactive chat applications using your enterprise data. These applications can generate answers based on your data or a large language model (LLM) knowledge. Your data is not used for training purposes, and the answers provided by Amazon Q Business are based solely on …

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Getting started with cross-region inference in Amazon Bedrock

Getting started with cross-region inference in Amazon Bedrock

With the advent of generative AI solutions, a paradigm shift is underway across industries, driven by organizations embracing foundation models to unlock unprecedented opportunities. Amazon Bedrock has emerged as the preferred choice for numerous customers seeking to innovate and launch generative AI applications, leading to an exponential surge in demand for model inference capabilities. Bedrock …

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