AWS Machine Learning - AI

AUGUST 5, 2024

Amazon Transcribe is an AWS AI service that makes it straightforward to convert speech to text. In this post, we show how Amazon Transcribe and Amazon Bedrock can streamline the process to catalog, query, and search through audio programs, using an example from the AWS re:Think podcast series. and the AWS SDK for Python (Boto3).

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AWS Machine Learning - AI

NOVEMBER 19, 2024

In this post, we demonstrate how to create an automated email response solution using Amazon Bedrock and its features, including Amazon Bedrock Agents , Amazon Bedrock Knowledge Bases , and Amazon Bedrock Guardrails. These indexed documents provide a comprehensive knowledge base that the AI agents consult to inform their responses.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

Amazon Bedrock Agents coordinates interactions between foundation models (FMs), knowledge bases, and user conversations. The agents also automatically call APIs to perform actions and access knowledge bases to provide additional information. The documents are chunked into smaller segments for more effective processing.

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AWS Machine Learning - AI

JULY 11, 2024

This solution shows how Amazon Bedrock agents can be configured to accept cloud architecture diagrams, automatically analyze them, and generate Terraform or AWS CloudFormation templates. Diagram analysis and query generation : The Amazon Bedrock agent forwards the architecture diagram location to an action group that invokes an AWS Lambda.

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Dzone - DevOps

JULY 1, 2024

In this blog, we will use the AWS Generative AI Constructs Library to deploy a complete RAG application composed of the following components: Knowledge Bases for Amazon Bedrock : This is the foundation for the RAG solution. An S3 bucket: This will act as the data source for the Knowledge Base.

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AWS Machine Learning - AI

AUGUST 15, 2024

QnABot on AWS (an AWS Solution) now provides access to Amazon Bedrock foundational models (FMs) and Knowledge Bases for Amazon Bedrock , a fully managed end-to-end Retrieval Augmented Generation (RAG) workflow. Deploying the QnABot solution builds the following environment in the AWS Cloud.

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AWS Machine Learning - AI

MAY 14, 2024

The entire conversation in this use case, starting with generative AI and then bringing in human agents who take over, is logged so that the interaction can be used as part of the knowledge base. We also have another expert group providing feedback using Amazon SageMaker GroundTruth on completion quality for the RLHF based training.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. You also need to consider the operational characteristics and noisy neighbor risks.

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AWS Machine Learning - AI

APRIL 24, 2024

With AWS generative AI services like Amazon Bedrock , developers can create systems that expertly manage and respond to user requests. It uses the provided conversation history, action groups, and knowledge bases to understand the context and determine the necessary tasks. The AI assistant interprets the user’s text input.

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AWS Machine Learning - AI

NOVEMBER 27, 2024

Custom orchestrator overview Implemented by users as an AWS Lambda function, the Amazon Bedrock Agents custom orchestrator offers granular control over task planning, completion, and verification. Use Amazon Bedrock Agents built-in integrations with action groups, knowledge bases, and guardrails to streamline interactions.

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AWS Machine Learning - AI

NOVEMBER 27, 2024

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, integrate and deploy them into your application using Amazon Web Services (AWS) tools without having to manage any infrastructure. Grant the agent permissions to AWS services through the IAM service role.

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AWS Machine Learning - AI

OCTOBER 29, 2024

We have built a custom observability solution that Amazon Bedrock users can quickly implement using just a few key building blocks and existing logs using FMs, Amazon Bedrock Knowledge Bases , Amazon Bedrock Guardrails , and Amazon Bedrock Agents.

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AWS Machine Learning - AI

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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AWS Machine Learning - AI

OCTOBER 23, 2024

Built using Amazon Bedrock Knowledge Bases , Amazon Lex , and Amazon Connect , with WhatsApp as the channel, our solution provides users with a familiar and convenient interface. The solution’s scalability quickly accommodates growing data volumes and user queries thanks to AWS serverless offerings.

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AWS Machine Learning - AI

OCTOBER 15, 2024

Despite the existence of AWS Application Discovery Service or the presence of some form of configuration management database (CMDB), customers still face many challenges. Guidance : To ensure accurate and consistent responses from your migration assistant, implement Amazon Bedrock Knowledge Bases.

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AWS Machine Learning - AI

NOVEMBER 27, 2024

This allows FMs to retain their inductive abilities while grounding their language understanding and generation in well-structured domain knowledge and logical reasoning. The RDF is converted into text and loaded into an S3 bucket, which is accessed by Amazon Bedrock (4) as the source of the knowledge base.

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AWS Machine Learning - AI

NOVEMBER 1, 2024

Although tagging is supported on a variety of Amazon Bedrock resources —including provisioned models, custom models, agents and agent aliases, model evaluations, prompts, prompt flows, knowledge bases, batch inference jobs, custom model jobs, and model duplication jobs—there was previously no capability for tagging on-demand foundation models.

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AWS Machine Learning - AI

JUNE 26, 2024

This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. These managed agents act as intelligent orchestrators, coordinating interactions between foundation models, API integrations, user questions and instructions, and knowledge sources loaded with your proprietary data.

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AWS Machine Learning - AI

SEPTEMBER 20, 2024

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. With just a few configuration steps, you can dramatically expand your chatbot’s knowledge base and capabilities, all while maintaining a streamlined UI.

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AWS Machine Learning - AI

NOVEMBER 22, 2024

This post discusses how to use AWS Step Functions to efficiently coordinate multi-step generative AI workflows, such as parallelizing API calls to Amazon Bedrock to quickly gather answers to lists of submitted questions.

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AWS Machine Learning - AI

DECEMBER 22, 2023

Amazon Lex supplies the natural language understanding (NLU) and natural language processing (NLP) interface for the open source LangChain conversational agent embedded within an AWS Amplify website. Amazon Lex then invokes an AWS Lambda handler for user intent fulfillment. ConversationIndexTable – Tracks the conversation state.

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AWS Machine Learning - AI

OCTOBER 24, 2024

They use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide a final response to the end user. We use Amazon Bedrock Agents with two knowledge bases for this assistant.

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AWS Machine Learning - AI

MAY 7, 2024

For a generative AI powered Live Meeting Assistant that creates post call summaries, but also provides live transcripts, translations, and contextual assistance based on your own company knowledge base, see our new LMA solution. AWS CDK version 2.0

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AWS Machine Learning - AI

NOVEMBER 26, 2024

With Amazon Bedrock, you can create an agent in just a few quick steps by first selecting an FM and providing it access to your enterprise systems, knowledge bases, and actions to securely execute your APIs. These actions can be implemented in the cloud using AWS Lambda , or you can use local business logic with return of control.

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AWS Machine Learning - AI

SEPTEMBER 13, 2024

Managing cloud costs and understanding resource usage can be a daunting task, especially for organizations with complex AWS deployments. AWS Cost and Usage Reports (AWS CUR) provides valuable data insights, but interpreting and querying the raw data can be challenging. This is a proof of concept setup.

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AWS Machine Learning - AI

OCTOBER 11, 2024

It uses Amazon Bedrock , AWS Health , AWS Step Functions , and other AWS services. Some examples of AWS-sourced operational events include: AWS Health events — Notifications related to AWS service availability, operational issues, or scheduled maintenance that might affect your AWS resources.

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AWS Machine Learning - AI

JULY 30, 2024

Mediasearch Q Business supercharges the way you consume media files by using them as part of the knowledge base used by Amazon Q Business to generate reliable answers to user questions. We use a CloudFormation stack to deploy the necessary resources in the us-east-1 AWS Region.

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AWS Machine Learning - AI

SEPTEMBER 12, 2024

Architecture The solution uses Amazon API Gateway , AWS Lambda , Amazon RDS, Amazon Bedrock, and Anthropic Claude 3 Sonnet on Amazon Bedrock to implement the backend of the application. Model deployment accounts – The LLMs offered by various vendors are hosted and operated by AWS in separate accounts dedicated for model deployment.

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AWS Machine Learning - AI

OCTOBER 7, 2024

By harnessing the power of generative AI and Amazon Web Services (AWS) services Amazon Bedrock , Amazon Kendra , and Amazon Lex , this solution provides a sample architecture to build an intelligent Slack chat assistant that can streamline information access, enhance user experiences, and drive productivity and efficiency within organizations.

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AWS Machine Learning - AI

DECEMBER 6, 2023

To create AI assistants that are capable of having discussions grounded in specialized enterprise knowledge, we need to connect these powerful but generic LLMs to internal knowledge bases of documents. To understand these limitations, let’s consider again the example of deciding where to invest based on financial reports.

Artificial Inteligence 124

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Perficient

AUGUST 20, 2024

AWS Bedrock is Amazon Web Services’ comprehensive solution that leverages these models to provide robust AI and machine learning (ML) capabilities. This blog delves into the essentials of AI foundational models in AWS Bedrock, highlighting their significance and applications. What are AI Foundational Models?

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AWS Machine Learning - AI

NOVEMBER 14, 2024

Solution overview This solution uses the Amazon Bedrock Knowledge Bases chat with document feature to analyze and extract key details from your invoices, without needing a knowledge base. Prerequisites To perform this solution, complete the following: Create and activate an AWS account. Install Python 3.7

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AWS Machine Learning - AI

JULY 10, 2024

For information on AWS Regions and models supported, refer to Prompt management in Amazon Bedrock. This feature allows you to link multiple FMs, prompts, and other AWS services, reducing development time and effort. Create a flow by providing a name, description, and AWS Identity and Access Management (IAM) role.

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AWS Machine Learning - AI

MARCH 14, 2024

In this post we highlight how the AWS Generative AI Innovation Center collaborated with the AWS Professional Services and PGA TOUR to develop a prototype virtual assistant using Amazon Bedrock that could enable fans to extract information about any event, player, hole or shot level details in a seamless interactive manner.

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AWS Machine Learning - AI

APRIL 8, 2024

RAG allows models to tap into vast knowledge bases and deliver human-like dialogue for applications like chatbots and enterprise search assistants. Download press releases to use as our external knowledge base. Query the knowledge base. For account setup instructions, see Create an AWS Account.

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AWS Machine Learning - AI

OCTOBER 2, 2024

In this post, we share AWS guidance that we have learned and developed as part of real-world projects into practical guides oriented towards the AWS Well-Architected Framework , which is used to build production infrastructure and applications on AWS. To learn more, see Log Amazon Bedrock API calls using AWS CloudTrail.

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AWS Machine Learning - AI

SEPTEMBER 12, 2024

RAG overview Retrieval-Augmented Generation (RAG) is a technique that enables the integration of external knowledge sources with FM. First, relevant content is retrieved from an external knowledge base based on the user’s query. Basic familiarity with SageMaker and AWS services that support LLMs.

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