AWS Machine Learning - AI

MARCH 1, 2024

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With a knowledge base, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data for fully managed Retrieval Augmented Generation (RAG).

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AWS Machine Learning - AI

FEBRUARY 19, 2024

One way to enable more contextual conversations is by linking the chatbot to internal knowledge bases and information systems. Integrating proprietary enterprise data from internal knowledge bases enables chatbots to contextualize their responses to each user’s individual needs and interests.

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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. However, some components may incur additional usage-based costs.

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AWS Machine Learning - AI

JULY 1, 2024

Generative artificial intelligence (AI)-powered chatbots play a crucial role in delivering human-like interactions by providing responses from a knowledge base without the involvement of live agents. You can simply connect QnAIntent to company knowledge sources and the bot can immediately handle questions using the allowed content.

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AWS Machine Learning - AI

OCTOBER 31, 2024

The Lambda function interacts with Amazon Bedrock through its runtime APIs, using either the RetrieveAndGenerate API that connects to a knowledge base, or the Converse API to chat directly with an LLM available on Amazon Bedrock. If you don’t have an existing knowledge base, refer to Create an Amazon Bedrock knowledge base.

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AWS Machine Learning - AI

FEBRUARY 8, 2024

You can now use Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock to configure specialized agents that seamlessly run actions based on natural language input and your organization’s data. Knowledge Bases for Amazon Bedrock provides fully managed RAG to supply the agent with access to your data.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

The solution presented in this post takes approximately 15–30 minutes to deploy and consists of the following key components: Amazon OpenSearch Service Serverless maintains three indexes : the inventory index, the compatible parts index, and the owner manuals index. The following diagram illustrates the workflow of the agent.

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AWS Machine Learning - AI

SEPTEMBER 25, 2024

Amazon Bedrock Knowledge Bases is a fully managed capability that helps you implement the entire RAG workflow—from ingestion to retrieval and prompt augmentation—without having to build custom integrations to data sources and manage data flows. Latest innovations in Amazon Bedrock Knowledge Base provide a resolution to this issue.

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AWS Machine Learning - AI

MARCH 4, 2025

Knowledge base integration Incorporates up-to-date WAFR documentation and cloud best practices using Amazon Bedrock Knowledge Bases , providing accurate and context-aware evaluations. Amazon Textract extracts the content from the uploaded documents, making it machine-readable for further processing.

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AWS Machine Learning - AI

JANUARY 29, 2025

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. Accelerate your generative AI application development by integrating your supported custom models with native Bedrock tools and features like Knowledge Bases, Guardrails, and Agents.

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AWS Machine Learning - AI

JANUARY 22, 2025

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and quickly integrate and deploy them into your applications using AWS tools without having to manage the infrastructure. With six years of experience in ML and cybersecurity, he brings a wealth of knowledge to his work.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

API Gateway is serverless and hence automatically scales with traffic. The advantage of using Application Load Balancer is that it can seamlessly route the request to virtually any managed, serverless or self-hosted component and can also scale well. It’s serverless so you don’t have to manage the infrastructure.

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AWS Machine Learning - AI

AUGUST 28, 2024

The complexity of developing and deploying an end-to-end RAG solution involves several components, including a knowledge base, retrieval system, and generative language model. Solution overview The solution provides an automated end-to-end deployment of a RAG workflow using Knowledge Bases for Amazon Bedrock.

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AWS Machine Learning - AI

AUGUST 5, 2024

Included with Amazon Bedrock is Knowledge Bases for Amazon Bedrock. As a fully managed service, Knowledge Bases for Amazon Bedrock makes it straightforward to set up a Retrieval Augmented Generation (RAG) workflow. With Knowledge Bases for Amazon Bedrock, we first set up a vector database on AWS.

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AWS Machine Learning - AI

SEPTEMBER 24, 2024

It’s a fully serverless architecture that uses Amazon OpenSearch Serverless , which can run petabyte-scale workloads, without you having to manage the underlying infrastructure. This solution uses Amazon Bedrock LLMs to find answers to questions from your knowledge base. Choose your new knowledge base to open it.

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AWS Machine Learning - AI

OCTOBER 11, 2024

The assistant can filter out irrelevant events (based on your organization’s policies), recommend actions, create and manage issue tickets in integrated IT service management (ITSM) tools to track actions, and query knowledge bases for insights related to operational events. It has several key components.

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AWS Machine Learning - AI

NOVEMBER 22, 2023

In addition, customers are looking for choices to select the most performant and cost-effective machine learning (ML) model and the ability to perform necessary customization (fine-tuning) to fit their business use cases. The LLM generated text, and the IR system retrieves relevant information from a knowledge base.

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AWS Machine Learning - AI

NOVEMBER 22, 2024

Since Amazon Bedrock is serverless, you don’t have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.

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AWS Machine Learning - AI

MARCH 20, 2025

It integrates with existing applications and includes key Amazon Bedrock features like foundation models (FMs), prompts, knowledge bases, agents, flows, evaluation, and guardrails. The chat agent bridges complex information systems and user-friendly communication.

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AWS Machine Learning - AI

DECEMBER 11, 2024

When Amazon Q Business became generally available in April 2024, we quickly saw an opportunity to simplify our architecture, because the service was designed to meet the needs of our use caseto provide a conversational assistant that could tap into our vast (sales) domain-specific knowledge bases.

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AWS Machine Learning - AI

MARCH 5, 2025

To scale ground truth generation and curation, you can apply a risk-based approach in conjunction with a prompt-based strategy using LLMs. Scaling ground truth generation with a pipeline To automate ground truth generation, we provide a serverless batch pipeline architecture, shown in the following figure. 201% $12.2B

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AWS Machine Learning - AI

OCTOBER 1, 2024

Voice-based assistants like Alexa demonstrate how we are entering an era of conversational interfaces. We explore how to build a fully serverless, voice-based contextual chatbot tailored for individuals who need it. All the services that we use are serverless and fully managed by AWS. We discuss this later in the post.

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AWS Machine Learning - AI

SEPTEMBER 26, 2024

Without a mechanism to manage this knowledge transfer gap, productivity across all phases of the lifecycle might suffer from losing expert knowledge and repeating past mistakes. Generative AI is a modern form of machine learning (ML) that has recently shown significant gains in reasoning, content comprehension, and human interaction.

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AWS Machine Learning - AI

NOVEMBER 6, 2024

Going forward, the team enriched the knowledge base (S3 buckets) and implemented a feedback loop to facilitate continuous improvement of the solution. Oleg Chugaev is a Principal Solutions Architect and Serverless evangelist with 20+ years in IT, holding multiple AWS certifications.

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AWS Machine Learning - AI

JUNE 26, 2024

You can now use Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock to build specialized agents and AI-powered assistants that run actions based on natural language input prompts and your organization’s data. Both the action groups and knowledge base are optional and not required for the agent itself.

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AWS Machine Learning - AI

MARCH 20, 2025

Amazon Bedrock offers fine-tuning capabilities that allow you to customize these pre-trained models using proprietary call transcript data, facilitating high accuracy and relevance without the need for extensive machine learning (ML) expertise.

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AWS Machine Learning - AI

MAY 13, 2024

It’s serverless, so you don’t have to manage any infrastructure. Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. To implement our RAG system, we utilized a dataset of 95,000 radiology report findings-impressions pairs as the knowledge source.

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AWS Machine Learning - AI

JANUARY 29, 2025

Centralized model In a centralized operating model, all generative AI activities go through a central generative artificial intelligence and machine learning (AI/ML) team that provisions and manages end-to-end AI workflows, models, and data across the enterprise.

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CIO

APRIL 11, 2024

One example is with its recently introduced OCI Generative AI Agents, a managed service that combines large language models with an intelligent retrieval system to create contextually relevant answers by searching a knowledge base. And, according to Tricentis’ Thompson, Oracle’s biggest challenge may be its release cadence.

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AWS Machine Learning - AI

MAY 14, 2024

An important aspect of developing effective generative AI application is Reinforcement Learning from Human Feedback (RLHF). RLHF is a technique that combines rewards and comparisons, with human feedback to pre-train or fine-tune a machine learning (ML) model. You can build such chatbots following the same process.

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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

MARCH 7, 2025

During the solution design process, Verisk also considered using Amazon Bedrock Knowledge Bases because its purpose built for creating and storing embeddings within Amazon OpenSearch Serverless. Vaibhav Singh is a Product Innovation Analyst at Verisk, based out of New Jersey.

Generative AI 73

Generative AI Technical Review Insurance Policies 73

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. Deploy an embedding model from the Amazon SageMaker JumpStart hub.

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AWS Machine Learning - AI

MAY 30, 2024

With Bedrock’s serverless experience, one can get started quickly, privately customize FMs with their own data, and easily integrate and deploy them into applications using the AWS tools without having to manage any infrastructure. The VitechIQ user experience can be split into two process flows: document repository, and knowledge retrieval.

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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

FEBRUARY 28, 2024

However, you can also use knowledge bases in Amazon Bedrock to build RAG solutions quickly. Using the Titan-Text-Embeddings model on Amazon Bedrock , convert the metadata into embeddings and store it in an Amazon OpenSearch Serverless vector store , which serves as our knowledge base in our RAG framework.

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AWS Machine Learning - AI

MARCH 14, 2024

Beyond hardware, data cleaning and processing, model architecture design, hyperparameter tuning, and training pipeline development demand specialized machine learning (ML) skills. Knowledge base responses come with source citations to improve transparency and minimize hallucinations.

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