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Intermediate (200)

Custom prompts for the RetrieveAndGenerate API are now supported by the Amazon Bedrock Knowledge Bases, along with the ability to configure the maximum number of results retrieved.

Knowledge Bases for Amazon Bedrock is a new feature that allows users to securely connect foundation models (FMs) to their corporate data for Retrieval Augmented Generation (RAG). This improves the precision of responses by providing access to a broader range of data without having to retrain the foundation models. There are two new features specific…

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Amazon Bedrock’s Knowledge Bases now have the functionality to filter metadata, enhancing the precision of data retrieval.

During the AWS re:Invent 2023, Amazon announced the general availability of Knowledge Bases for Amazon Bedrock. This allows secure connection of foundation models in Amazon Bedrock to your company data using a fully managed Retrieval Augmented Generation (RAG) model. This feature helps in improving the accuracy of the generated responses from foundation models depending upon the…

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Effortlessly shift between no-code and code-first machine learning using Amazon SageMaker Canvas and Amazon SageMaker Studio.

Amazon SageMaker Studio and Amazon SageMaker Canvas are powerful tools by AWS designed for machine learning (ML) development and operation. SageMaker Studio is a web-based, integrated development environment (IDE) allowing users to build, train, debug, deploy, and monitor ML models. SageMaker Canvas is a no-code ML tool enabling business and data teams to craft accurate…

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Attain DevOps refinement with BMC AMI zAdviser Enterprise and Amazon Bedrock.

Software engineering performance significantly impacts the building of sturdy, stable applications. The community aims to imbibe the engineering principles typical of software development, including systematic approaches to design, testing, development, and maintenance. This requires the careful amalgamation of applications and metrics to warrant complete control, awareness, and accuracy. This could be achieved through practices such…

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Activate single-use entry to Amazon SageMaker Canvas via AWS IAM Identity Center: Second Part

Amazon SageMaker Canvas offers users end-to-end machine learning (ML) applications without the need for coding. The interface supports functionalities such as data preparation, endpoint deployment, and adjustment of foundation models for generative AI among others. A crucial step in enabling users and ensuring secure environments involves the use of single sign-on (SSO) via AWS IAM Identity…

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Top guidelines for developing secure applications using Amazon Transcribe

Amazon Transcribe is an Amazon Web Services (AWS) tool that converts speech to text using machine learning technologies. It can be used for a wide range of applications such as transcribing customer care calls, voicemail messages, and generating subtitles for videos. Some customers may entrust sensitive and confidential data with the service, such as personal…

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Utilize Amazon Bedrock and AWS Step Functions to facilitate the automation of altering image backgrounds.

Many customers in sectors such as creative advertising, media and entertainment, ecommerce, and fashion often need to change the background in a large number of images, which usually involves a time-consuming manual editing process for each image. Amazon Bedrock, in conjunction with AWS Step Functions, makes it easy to automate the process of changing backgrounds…

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Create a chatbot application, utilizing Knowledge Bases, for Amazon Bedrock that’s equipped to handle context-based interactions.

Modern chatbots are revolutionizing the customer service sector by providing 24/7 support in multiple languages. Their ability to handle concurrent inquiries in real time, provide relevant data-driven insights, and scale effortlessly make them a cost-effective solution for customer engagement. These benefits are magnified when chatbots are integrated with internal knowledge bases and large language models…

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