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. Solution overview This section outlines the architecture designed for an email support system using generative AI.

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AWS Machine Learning - AI

MARCH 5, 2025

These assistants can be powered by various backend architectures including Retrieval Augmented Generation (RAG), agentic workflows, fine-tuned large language models (LLMs), or a combination of these techniques. To learn more about FMEval, see Evaluate large language models for quality and responsibility of LLMs.

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Generative AI Systems Review Software Review Artificial Inteligence 75

CIO

DECEMBER 10, 2024

A second area is improving data quality and integrating systems for marketing departments, then tracking how these changes impact marketing metrics. The CIO and CMO partnership must ensure seamless system integration and data sharing, enhancing insights and decision-making.

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Weak Development Team Metrics Software Review Technical Review 215

AWS Machine Learning - AI

APRIL 1, 2025

Whether youre an experienced AWS developer or just getting started with cloud development, youll discover how to use AI-powered coding assistants to tackle common challenges such as complex service configurations, infrastructure as code (IaC) implementation, and knowledge base integration.

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AWS Software Review Knowledge Base Artificial Inteligence 117

AWS Machine Learning - AI

DECEMBER 4, 2024

They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels. The system will take a few minutes to set up your project. On the next screen, leave all settings at their default values.

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Generative AI Applications Technical Review Software Review 101

AWS Machine Learning - AI

APRIL 1, 2025

AI agents extend large language models (LLMs) by interacting with external systems, executing complex workflows, and maintaining contextual awareness across operations. Whether youre connecting to external systems or internal data stores or tools, you can now use MCP to interface with all of them in the same way.

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AWS Machine Learning - AI

NOVEMBER 22, 2024

Seamless integration of latest foundation models (FMs), Prompts, Agents, Knowledge Bases, Guardrails, and other AWS services. Flexibility to define the workflow based on your business logic. Knowledge base node : Apply guardrails to responses generated from your knowledge base.

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Generative AI Artificial Inteligence Knowledge Base AWS 109

Perficient

NOVEMBER 20, 2024

Introduction to Multiclass Text Classification with LLMs Multiclass text classification (MTC) is a natural language processing (NLP) task where text is categorized into multiple predefined categories or classes. Traditional approaches rely on training machine learning models, requiring labeled data and iterative fine-tuning.

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Artificial Inteligence Metrics Airlines Travel 52

AWS Machine Learning - AI

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications.

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Artificial Inteligence Generative AI Training Metrics 91

AWS Machine Learning - AI

FEBRUARY 29, 2024

Amazon Bedrock provides a broad range of models from Amazon and third-party providers, including Anthropic, AI21, Meta, Cohere, and Stability AI, and covers a wide range of use cases, including text and image generation, embedding, chat, high-level agents with reasoning and orchestration, and more.

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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. Create new generative AI-powered intent in Amazon Lex using the built-in QnAIntent and point the knowledge base.

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Knowledge Base Artificial Inteligence Generative AI AWS 119

AWS Machine Learning - AI

FEBRUARY 19, 2024

Chatbots also offer valuable data-driven insights into customer behavior while scaling effortlessly as the user base grows; therefore, they present a cost-effective solution for engaging customers. Chatbots use the advanced natural language capabilities of large language models (LLMs) to respond to customer questions.

Knowledge Base 114

Knowledge Base Artificial Inteligence Applications Lambda 114

AWS Machine Learning - AI

NOVEMBER 7, 2024

AI agents , powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses. Amazon Bedrock Agents coordinates interactions between foundation models (FMs), knowledge bases, and user conversations.

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Lambda Enterprise Automotive Knowledge Base 122

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. In the future, Verisk intends to use the Amazon Titan Embeddings V2 model.

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Generative AI Technical Review Insurance Policies 83

AWS Machine Learning - AI

MAY 31, 2024

This means that individuals can ask companies to erase their personal data from their systems and from the systems of any third parties with whom the data was shared. Knowledge Bases for Amazon Bedrock is a fully managed RAG capability that allows you to customize FM responses with contextual and relevant company data.

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Knowledge Base Artificial Inteligence AWS Serverless 126

AWS Machine Learning - AI

NOVEMBER 15, 2024

As Principal grew, its internal support knowledge base considerably expanded. Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles.

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Generative AI AWS Groups Artificial Inteligence 113

AWS Machine Learning - AI

APRIL 26, 2024

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With Knowledge Bases for Amazon Bedrock, 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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Knowledge Base Generative AI Artificial Inteligence AWS 121

AWS Machine Learning - AI

MARCH 20, 2025

Traditionally, transforming raw data into actionable intelligence has demanded significant engineering effort. It often requires managing multiple machine learning (ML) models, designing complex workflows, and integrating diverse data sources into production-ready formats.

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AWS Machine Learning - AI

DECEMBER 11, 2024

In the same spirit of using generative AI to equip our sales teams to most effectively meet customer needs, this post reviews how weve delivered an internally-facing conversational sales assistant using Amazon Q Business. The following screenshot shows an example of an interaction with Field Advisor.

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AWS Generative AI Technical Review Artificial Inteligence 92

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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Knowledge Base Artificial Inteligence AWS Generative AI 127

AWS Machine Learning - AI

AUGUST 5, 2024

Retrieval Augmented Generation (RAG) is a state-of-the-art approach to building question answering systems that combines the strengths of retrieval and foundation models (FMs). RAG models first retrieve relevant information from a large corpus of text and then use a FM to synthesize an answer based on the retrieved information.

Knowledge Base 120

Knowledge Base AWS Generative AI Artificial Inteligence 120

CIO

MARCH 14, 2025

Legacy Systems Complicate the Adoption of New Technology The Challenge: Many organizations still have outdated IT infrastructure, which makes integration complicated and costly. (See also: How to know a business process is ripe for agentic AI. )

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Technical Review Weak Development Team B2B Software Review 191

AWS Machine Learning - AI

MARCH 11, 2025

OpenAI launched GPT-4o in May 2024, and Amazon introduced Amazon Nova models at AWS re:Invent in December 2024. Although GPT-4o has gained traction in the AI community, enterprises are showing increased interest in Amazon Nova due to its lower latency and cost-effectiveness. In this section, we explore each component in more detail.

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AWS Machine Learning - AI

FEBRUARY 8, 2024

At the forefront of this evolution sits Amazon Bedrock , a fully managed service that makes high-performing foundation models (FMs) from Amazon and other leading AI companies available through an API. The following demo recording highlights Agents and Knowledge Bases for Amazon Bedrock functionality and technical implementation details.

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Knowledge Base Insurance Lambda AWS 137

AWS Machine Learning - AI

MARCH 20, 2025

Companies of all sizes face mounting pressure to operate efficiently as they manage growing volumes of data, systems, and customer interactions. It integrates with existing applications and includes key Amazon Bedrock features like foundation models (FMs), prompts, knowledge bases, agents, flows, evaluation, and guardrails.

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AWS Machine Learning - AI

AUGUST 6, 2024

Now I’d like to turn to a slightly more technical, but equally important differentiator for Bedrock—the multiple techniques that you can use to customize models and meet your specific business needs. Customization unlocks the transformative potential of large language models.

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AWS Machine Learning - AI

JANUARY 22, 2025

Users can review different types of events such as security, connectivity, system, and management, each categorized by specific criteria like threat protection, LAN monitoring, and firmware updates. Retrieval Augmented Generation (RAG) Retrieve relevant context from a knowledge base, based on the input query.

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AWS Machine Learning - AI

NOVEMBER 22, 2024

Using Amazon Bedrock, you can easily experiment with and evaluate top FMs for your use case, privately customize them with your data using techniques such as fine-tuning and Retrieval Augmented Generation (RAG), and build agents that execute tasks using your enterprise systems and data sources.

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AWS Machine Learning - AI

NOVEMBER 7, 2024

Depending on the use case and data isolation requirements, tenants can have a pooled knowledge base or a siloed one and implement item-level isolation or resource level isolation for the data respectively. You can also bring your own customized models and deploy them to Amazon Bedrock for supported architectures.

Generative AI 106

Generative AI AWS Enterprise Artificial Inteligence 106

AWS Machine Learning - AI

MAY 30, 2024

Hosting large language models Vitech explored the option of hosting Large Language Models (LLMs) models using Amazon Sagemaker. Vitech needed a fully managed and secure experience to host LLMs and eliminate the undifferentiated heavy lifting associated with hosting 3P models.

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Artificial Inteligence Technical Review Development Team Review Software Review 123

AWS Machine Learning - AI

APRIL 22, 2025

Infosys Event AI is designed to make knowledge universally accessible, making sure that valuable insights are not lost and can be efficiently utilized by individuals and organizations across diverse industries both during the event and after the event has concluded. MediaConnect securely transmits the stream to MediaLive for processing.

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Media Knowledge Base AWS Systems Review 60

AWS Machine Learning - AI

MAY 13, 2024

In part 1 of this blog series, we discussed how a large language model (LLM) available on Amazon SageMaker JumpStart can be fine-tuned for the task of radiology report impression generation. Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline.

Generative AI 125

Generative AI Artificial Inteligence Report Healthcare 125

AWS Machine Learning - AI

MAY 9, 2024

Verisk is using generative artificial intelligence (AI) to enhance operational efficiencies and profitability for insurance clients while adhering to its ethical AI principles. The Opportunity Verisk FAST’s initial foray into using AI was due to the immense breadth and complexity of the platform.

Generative AI 128

Generative AI Artificial Inteligence Technical Review Development Team Review 128

AWS Machine Learning - AI

APRIL 24, 2024

Conversational artificial intelligence (AI) assistants are engineered to provide precise, real-time responses through intelligent routing of queries to the most suitable AI functions. With AWS generative AI services like Amazon Bedrock , developers can create systems that expertly manage and respond to user requests.

Artificial Inteligence 127

Artificial Inteligence Lambda Knowledge Base IoT 127

AWS Machine Learning - AI

APRIL 9, 2025

Amazon Q Business is a fully managed, generative AI-powered assistant that lets you build interactive chat applications using your enterprise data, generating answers based on your data or large language model (LLM) knowledge. Then we provide instructions for accessing and navigating this dashboard.

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Weak Development Team Metrics AWS Systems Review 71

AWS Machine Learning - AI

DECEMBER 18, 2024

Generative AIpowered assistants such as Amazon Q Business can be configured to answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. In Response settings under Application guardrails , select Allow Amazon Q to fall back to LLM knowledge.

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AWS Machine Learning - AI

JANUARY 29, 2025

It encompasses a range of measures aimed at mitigating risks, promoting accountability, and aligning generative AI systems with ethical principles and organizational objectives. Three common operating model patterns are decentralized, centralized, and federated, as shown in the following diagram.

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