AWS Machine Learning - AI

MARCH 13, 2025

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular.

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AWS Machine Learning - AI

SEPTEMBER 25, 2024

In the realm of generative artificial intelligence (AI) , Retrieval Augmented Generation (RAG) has emerged as a powerful technique, enabling foundation models (FMs) to use external knowledge sources for enhanced text generation. Latest innovations in Amazon Bedrock Knowledge Base provide a resolution to this issue.

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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

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.

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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

JULY 10, 2024

Knowledge Bases for Amazon Bedrock is a fully managed service that helps you implement the entire Retrieval Augmented Generation (RAG) workflow from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows, pushing the boundaries for what you can do in your RAG workflows.

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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. 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.

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AWS Machine Learning - AI

JULY 2, 2024

In November 2023, we announced Knowledge Bases for Amazon Bedrock as generally available. Knowledge bases allow Amazon Bedrock users to unlock the full potential of Retrieval Augmented Generation (RAG) by seamlessly integrating their company data into the language model’s generation process.

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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. The WAFR reviewer, based on Lambda and AWS Step Functions , is activated by Amazon SQS.

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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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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. The Content Designer AWS Lambda function saves the input in Amazon OpenSearch Service in a questions bank index.

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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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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. It uses the provided conversation history, action groups, and knowledge bases to understand the context and determine the necessary tasks.

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AWS Machine Learning - AI

SEPTEMBER 24, 2024

It also enables operational capabilities including automated testing, conversation analytics, monitoring and observability, and LLM hallucination prevention and detection. “We An optional CloudFormation stack to enable an asynchronous LLM hallucination detection feature. seconds or less.

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AWS Machine Learning - AI

AUGUST 5, 2024

Finding relevant content usually requires searching through text-based metadata such as timestamps, which need to be manually added to these files. Included with Amazon Bedrock is Knowledge Bases for Amazon Bedrock. With Knowledge Bases for Amazon Bedrock, we first set up a vector database on AWS.

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CIO

APRIL 25, 2023

ChatGPT was trained with 175 billion parameters; for comparison, GPT-2 was 1.5B (2019), Google’s LaMBDA was 137B (2021), and Google’s BERT was 0.3B (2018). ChatGPT’s conversational interface is a distinguished method of accessing its knowledge. Learn more about Protiviti’s Artificial Intelligence Services.

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AWS Machine Learning - AI

MARCH 20, 2025

Amazon Bedrock in SageMaker Unified Studio addresses these challenges by providing a unified service for building AI-driven solutions that centralize customer data and enable natural language interactions. The Lambda function performs the actions by calling the JIRA API or database with the required parameters provided from the agent.

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AWS Machine Learning - AI

MAY 14, 2024

Recent advances in artificial intelligence have led to the emergence of generative AI that can produce human-like novel content such as images, text, and audio. These models are pre-trained on massive datasets and, to sometimes fine-tuned with smaller sets of more task specific data.

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AWS Machine Learning - AI

NOVEMBER 14, 2024

We use Anthropic’s Claude 3 Sonnet model in Amazon Bedrock and Streamlit for building the application front-end. 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. endswith('.pdf'):

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AWS Machine Learning - AI

NOVEMBER 22, 2024

RAG and other possible integrations RAG is a strategy that enhances the output of a large language model (LLM) by allowing it to reference an authoritative external knowledge base, generating more accurate or secure responses. sync) pattern, which automatically waits for the completion of asynchronous jobs.

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AWS Machine Learning - AI

JUNE 26, 2024

Artificial intelligence (AI)-powered assistants can boost the productivity of a financial analysts, research analysts, and quantitative trading in capital markets by automating many of the tasks, freeing them to focus on high-value creative work. AI-powered assistants for investment research So, what are AI-powered assistants?

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AWS Machine Learning - AI

MAY 7, 2024

A more efficient way to manage meeting summaries is to create them automatically at the end of a call through the use of generative artificial intelligence (AI) and speech-to-text technologies. The Hugging Face containers host a large language model (LLM) from the Hugging Face Hub.

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AWS Machine Learning - AI

OCTOBER 24, 2024

Agentic workflows are a fresh new perspective in building dynamic and complex business use- case based workflows with the help of large language models (LLM) as their reasoning engine or brain. We use Amazon Bedrock Agents with two knowledge bases for this assistant. What are some S3 best practices?

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AWS Machine Learning - AI

SEPTEMBER 12, 2024

BGE Large overview The embedding model BGE Large stands for BAAI general embedding large. It’s developed by BAAI and is designed to enhance retrieval capabilities within large language models (LLMs). First, relevant content is retrieved from an external knowledge base based on the user’s query.

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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

APRIL 8, 2024

Unlocking accurate and insightful answers from vast amounts of text is an exciting capability enabled by large language models (LLMs). When building LLM applications, it is often necessary to connect and query external data sources to provide relevant context to the model.

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AWS Machine Learning - AI

JULY 11, 2024

Diagram analysis and query generation : The Amazon Bedrock agent forwards the architecture diagram location to an action group that invokes an AWS Lambda. This function retrieves the architecture diagram from the specified S3 bucket, analyzes it using the Amazon Bedrock model, and produces a summary of the diagram.

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AWS Machine Learning - AI

APRIL 18, 2024

Generative artificial intelligence (AI) with Amazon Bedrock directly addresses these challenges. This standardization is made possible by using advanced prompts in conjunction with Knowledge Bases for Amazon Bedrock , which stores information on organization-specific Terraform modules. Access to Amazon Bedrock models.

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AWS Machine Learning - AI

DECEMBER 6, 2023

Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback.

Artificial Inteligence 120

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AWS Machine Learning - AI

SEPTEMBER 12, 2024

In this post, we discuss how generative artificial intelligence (AI) can help health insurance plan members get the information they need. A pre-configured prompt template is used to call the LLM and generate a valid SQL query. The Amazon Bedrock API endpoint is used to invoke the Anthropic Claude 3 Sonnet LLM.

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

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AWS Machine Learning - AI

MARCH 14, 2024

Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval.

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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

FEBRUARY 25, 2025

Error retrieval and context gathering The Amazon Bedrock agent forwards these details to an action group that invokes the first AWS Lambda function (see the following Lambda function code ). This contextual information is then sent back to the first Lambda function. Refer to the Lambda function code for more details.

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AWS Machine Learning - AI

JANUARY 22, 2025

For general travel inquiries, users receive instant responses powered by an LLM. For this node, the condition value is: Name: Booking Condition: categoryLetter=="A" Create a second prompt node for the LLM guide invocation. The flow offers two distinct interaction paths.

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AWS Machine Learning - AI

OCTOBER 2, 2024

It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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AWS Machine Learning - AI

DECEMBER 22, 2023

We start off with a baseline foundation model from SageMaker JumpStart and evaluate it with TruLens , an open source library for evaluating and tracking large language model (LLM) apps. In development, you can use open source TruLens to quickly evaluate, debug, and iterate on your LLM apps in your environment.

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