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

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.

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Lambda Enterprise Automotive Knowledge Base 129

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.

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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.

Knowledge Base 126

Knowledge Base Artificial Inteligence Generative AI AWS 126

AWS Machine Learning - AI

FEBRUARY 29, 2024

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.

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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 137

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. Verisk also has a legal review for IP protection and compliance within their contracts.

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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. System integration – Agents make API calls to integrated company systems to run specific actions.

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Knowledge Base Insurance Lambda AWS 140

AWS Machine Learning - AI

MARCH 5, 2025

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. By providing an expected outcome to measure against, ground truth data unlocks the ability to deterministically evaluate system quality. 201% $12.2B What was Amazons operating margin in 2023?

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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 79

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

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 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

APRIL 9, 2025

Its essential for admins to periodically review these metrics to understand how users are engaging with Amazon Q Business and identify potential areas of improvement. We begin with an overview of the available metrics and how they can be used for measuring user engagement and system effectiveness.

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AWS Machine Learning - AI

NOVEMBER 22, 2023

In this post, we demonstrate question answering tasks using a Retrieval Augmented Generation (RAG)-based approach with large language models (LLMs) in SageMaker JumpStart using a simple financial domain use case. RAG is a framework for improving the quality of text generation by combining an LLM with an information retrieval (IR) system.

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AWS Machine Learning - AI

JUNE 26, 2024

The interaction shows how AI-powered assistants recognize and plan based on user’s prompts, come up with steps to retrieve context from data stores, and pass through various tools and LLM to arrive at a response. Both the action groups and knowledge base are optional and not required for the agent itself.

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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

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. Prompt engineering Prompt engineering is crucial for the knowledge retrieval system.

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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. With Amazon Bedrock Knowledge Bases , you securely connect FMs in Amazon Bedrock to your company data for RAG. These safeguards are FM agnostic.

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AWS Machine Learning - AI

SEPTEMBER 23, 2024

Evaluating your Retrieval Augmented Generation (RAG) system to make sure it fulfils your business requirements is paramount before deploying it to production environments. With synthetic data, you can streamline the evaluation process and gain confidence in your system’s capabilities before unleashing it to the real world.

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AWS Machine Learning - AI

MAY 13, 2024

It’s serverless, so you don’t have to manage any infrastructure. In this part of the blog series, we review techniques of prompt engineering and Retrieval Augmented Generation (RAG) that can be employed to accomplish the task of clinical report summarization by using Amazon Bedrock.

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AWS Machine Learning - AI

MARCH 20, 2025

Furthermore, by integrating a knowledge base containing organizational data, policies, and domain-specific information, the generative AI models can deliver more contextual, accurate, and relevant insights from the call transcripts. The following screenshots show the UI.

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AWS Machine Learning - AI

AUGUST 2, 2024

An approach to product stewardship with generative AI Large language models (LLMs) are trained with vast amounts of information crawled from the internet, capturing considerable knowledge from multiple domains. However, their knowledge is static and tied to the data used during the pre-training phase.

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Artificial Inteligence Generative AI Energy Knowledge Base 124

AWS Machine Learning - AI

MAY 9, 2024

The Opportunity Verisk FAST’s initial foray into using AI was due to the immense breadth and complexity of the platform. Having that transparency helped Verisk identify areas of the system where their documents were lacking and needed some restructuring. However, they understood that this was not a one-and-done effort.

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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

OCTOBER 15, 2024

By using Amazon Bedrock Agents , action groups , and Amazon Bedrock Knowledge Bases , we demonstrate how to build a migration assistant application that rapidly generates migration plans, R-dispositions, and cost estimates for applications migrating to AWS. Choose Create knowledge base and enter a name and optional description.

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Lambda Knowledge Base AWS Generative AI 93

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 result is improved accuracy in FM responses, with reduced hallucinations due to grounding in verified data.

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Lambda Knowledge Base Generative AI AWS 93

CIO

APRIL 11, 2024

Even so, many clients tell Gartner they are not ready to trust Oracle as their primary provider, Wright says, due to past experiences with Oracle’s aggressive sales practices. The allure of such a system for enterprises cannot be overstated, Lee says.

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AWS Machine Learning - AI

MAY 14, 2024

In this post, we introduce a solution for integrating a “near-real-time human workflow” where humans are prompted by the generative AI system to take action when a situation or issue arises. This can also be a ruled-based method that can determine where, when and how your expert teams can be part of generative AI – user conversations.

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AWS Machine Learning - AI

SEPTEMBER 18, 2024

Generative AI and large language models (LLMs) offer new possibilities, although some businesses might hesitate due to concerns about consistency and adherence to company guidelines. UX/UI designers have established best practices and design systems applicable to all of their websites.

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AWS Machine Learning - AI

MARCH 14, 2024

The skills needed to properly integrate, customize, and validate FMs within existing systems and data are in short supply. With Knowledge Bases for Amazon Bedrock , you can give FMs and agents contextual information from your company’s private data sources for RAG to deliver more relevant, accurate, and customized responses.

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AWS Machine Learning - AI

SEPTEMBER 9, 2024

However, companies can face challenges when using generative AI for data insights, including maintaining data quality, addressing privacy concerns, managing model biases, and integrating AI systems with existing workflows. For details, see Identity-based policy examples for Amazon Bedrock.

Artificial Inteligence 120

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AWS Machine Learning - AI

JUNE 5, 2024

Although new features were released every other week, documentation for the features took an average of 3 weeks to complete, including drafting, review, and publication. The review process could also be long depending on the number of inaccuracies found, leading to additional revisions, additional reviews, and additional delays.

Technical Review 125

Technical Review Artificial Inteligence Generative AI Systems Review 125

Codegiant

JULY 18, 2020

The Complete Review [2020] I’ve created this “BitBucket vs GitHub” content piece to help you make a better decision when picking between the two. It boasts features like highlighted code comments and code reviews so you can easily enhance your software build by effectively communicating with your teammates. GitHub code reviews.

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AWS Machine Learning - AI

MARCH 28, 2024

If you’re implementing complex RAG applications into your daily tasks, you may encounter common challenges with your RAG systems such as inaccurate retrieval, increasing size and complexity of documents, and overflow of context, which can significantly impact the quality and reliability of generated answers.

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Altexsoft

MARCH 30, 2023

These improvements become possible due to the core components of the Databricks architecture — Delta Lake and Unity Catalog. No vendor lock-in and interoperability Databricks doesn’t make you move data to a proprietary system. Databricks lakehouse platform architecture.

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Weak Development Team Artificial Inteligence Machine Learning Software Review 64

Codegiant

JULY 2, 2020

Pull and Merge Requests You can use pull and merge requests to peer review and enhance the quality of your code. Based on the Acceptable Use Policy , Microsoft Windows operating systems are not permitted with GitLab. You can also utilize code reviews for text instead of code. Code review?—?use Security?—?BitBucket

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