AWS Machine Learning

OCTOBER 31, 2024

After you set up the connector, you can create one or multiple data sources within Amazon Q Business and configure them to start indexing emails from your Gmail account. The connector supports authentication using a Google service account. We describe the process of creating an account later in this post. Choose Create.

APIs 115

APIs Accountability Enterprise Engineering 115

AWS Machine Learning

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts. Mitigation strategies : Implementing measures to minimize or eliminate risks.

Government 93

Government Management APIs Accountability 93

AWS Machine Learning

MARCH 19, 2025

Note that these APIs use objects as namespaces, alleviating the need for explicit imports. API Gateway supports multiple mechanisms for controlling and managing access to an API. AWS Lambda handles the REST API integration, processing the requests and invoking the appropriate AWS services. Sonnet).

APIs 104

APIs Automotive Accountability Analytics 104

AWS Machine Learning

NOVEMBER 13, 2024

The solution also uses Amazon Cognito user pools and identity pools for managing authentication and authorization of users, Amazon API Gateway REST APIs, AWS Lambda functions, and an Amazon Simple Storage Service (Amazon S3) bucket. To launch the solution in a different Region, change the aws_region parameter accordingly.

APIs 127

APIs Scripts Accountability Entertainment 127

AWS Machine Learning

NOVEMBER 15, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability 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.

APIs 109

APIs Government Best practices Metrics 109

AWS Machine Learning

NOVEMBER 19, 2024

Prerequisites Before you start, make sure you have the following prerequisites in place: Create an AWS account , or sign in to your existing account. Based on the API response, you can determine the guardrail’s action. Additionally, each row of the API response is saved so the user can explore the response as needed.

APIs 112

APIs Government Banking Engineering 112

AWS Machine Learning

MARCH 19, 2025

They use a highly optimized inference stack built with NVIDIA TensorRT-LLM and NVIDIA Triton Inference Server to serve both their search application and pplx-api, their public API service that gives developers access to their proprietary models. The results speak for themselvestheir inference stack achieves up to 3.1

Healthcare 140

Healthcare Enterprise APIs Transportation 140

AWS Machine Learning

MARCH 25, 2025

For more information about the SageMaker AI API, refer to the SageMaker AI API Reference. 8B-Instruct to DeepSeek-R1-Distill-Llama-8B, but the new model version has different API expectations. In this use case, you have configured a CloudWatch alarm to monitor for 4xx errors, which would indicate API compatibility issues.

APIs 94

APIs Engineering Accountability Metrics 94

AWS Machine Learning

MARCH 27, 2025

This requirement translates into time and effort investment of trained personnel, who could be support engineers or other technical staff, to review tens of thousands of support cases to arrive at an even distribution of 3,000 per category. Sonnet prediction accuracy through prompt engineering. client = boto3.client("bedrock-runtime",

Education 105

Education Engineering APIs Enterprise 105

AWS Machine Learning

JANUARY 28, 2025

By documenting the specific model versions, fine-tuning parameters, and prompt engineering techniques employed, teams can better understand the factors contributing to their AI systems performance. It functions as a standalone HTTP server that provides various REST API endpoints for monitoring, recording, and visualizing experiment runs.

Management 100

Management APIs Engineering Metrics 100

AWS Machine Learning

MARCH 11, 2025

Amazon Bedrock APIs make it straightforward to use Amazon Titan Text Embeddings V2 for embedding data. The implementation used the universal gateway provided by the FloTorch enterprise version to enable consistent API calls using the same function and to track token count and latency metrics uniformly. get("message", {}).get("content")

Benchmark 99

Benchmark APIs Enterprise Scripts 99

AWS Machine Learning

FEBRUARY 21, 2025

Solution overview Our solution implements a verified semantic cache using the Amazon Bedrock Knowledge Bases Retrieve API to reduce hallucinations in LLM responses while simultaneously improving latency and reducing costs. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API.

Engineering 116

Engineering APIs Analytics Enterprise 116

AWS Machine Learning

JULY 31, 2024

The new ApplyGuardrail API enables you to assess any text using your preconfigured guardrails in Amazon Bedrock, without invoking the FMs. In this post, we demonstrate how to use the ApplyGuardrail API with long-context inputs and streaming outputs. For example, you can now use the API with models hosted on Amazon SageMaker.

APIs 123

APIs Banking Best practices Engineering 123

AWS Machine Learning

FEBRUARY 14, 2024

Amazon Bedrock offers a choice of high-performing foundation models from leading AI companies, including AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon, via a single API. Prompt engineering makes generative AI applications more efficient and effective.

Engineering 136

Engineering Chatbots Accountability Enterprise 136

AWS Machine Learning

DECEMBER 11, 2024

Weve seen our sales teams use this capability to do things like consolidate meeting notes from multiple team members, analyze business reports, and develop account strategies. Amazon Q Business makes these features available through the service API, allowing for a customized look and feel on the frontend.

Sales 97

Sales Accountability APIs CRM 97

AWS Machine Learning

FEBRUARY 11, 2025

Enhancing AWS Support Engineering efficiency The AWS Support Engineering team faced the daunting task of manually sifting through numerous tools, internal sources, and AWS public documentation to find solutions for customer inquiries. For example, the Datastore API might require certain input like date periods to query data.

Enterprise 89

Enterprise Engineering APIs Best practices 89

AWS Machine Learning

OCTOBER 30, 2024

Enabling Global Resiliency for an Amazon Lex bot is straightforward using the AWS Management Console , AWS Command Line Interface (AWS CLI), or APIs. If this option isn’t visible, the Global Resiliency feature may not be enabled for your account. To better understand the solution, refer to the following architecture diagram.

Chatbots 102

Chatbots Interactive Voice Response APIs Telecommunications 102

AWS Machine Learning

DECEMBER 9, 2024

SageMaker is a comprehensive, fully managed ML service designed to provide data scientists and ML engineers with the tools they need to handle the entire ML workflow. Prerequisites You need an AWS account with an AWS Identity and Access Management (IAM) role with permissions to manage resources created as part of the solution.

Metrics 91

Metrics APIs Engineering Accountability 91

AWS Machine Learning

FEBRUARY 13, 2024

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM).

Accountability 127

Accountability Government Engineering Scripts 127

AWS Machine Learning

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. In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application.

APIs 105

APIs Chatbots Construction Engineering 105

AWS Machine Learning

JANUARY 24, 2025

These steps might involve both the use of an LLM and external data sources and APIs. Agent plugin controller This component is responsible for the API integration to external data sources and APIs. The LLM agent is an orchestrator of a set of steps that might be necessary to complete the desired request.

APIs 105

APIs Scripts Best practices Management 105

AWS Machine Learning

FEBRUARY 12, 2025

Amazon Bedrock , a fully managed service offering high-performing foundation models from leading AI companies through a single API, has recently introduced two significant evaluation capabilities: LLM-as-a-judge under Amazon Bedrock Model Evaluation and RAG evaluation for Amazon Bedrock Knowledge Bases.

Metrics 91

Metrics Engineering Benchmark APIs 91

AWS Machine Learning

NOVEMBER 21, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability 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.

APIs 109

APIs Call Center Engineering Personalization 109

AWS Machine Learning

OCTOBER 29, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Best practices 108

Best practices Feedback Metrics APIs 108

AWS Machine Learning

FEBRUARY 25, 2025

Prerequisites For this walkthrough, you should have the following prerequisites: An AWS account Access to the Alation service with the ability to create new policies and access tokens. With the connector ready, move over to the SageMaker Studio notebook and perform data synchronization operations by invoking Amazon Q Business APIs.

Enterprise 89

Enterprise Engineering APIs Accountability 89

AWS Machine Learning

JULY 2, 2024

Amazon Bedrock is a fully managed service that makes a wide range of foundation models (FMs) available though an API without having to manage any infrastructure. An Amazon OpenSearch Serverless vector engine to store enterprise data as vectors to perform semantic search. The request is sent by the web application to the API.

APIs 131

APIs Scripts Enterprise Engineering 131

AWS Machine Learning

MARCH 6, 2025

Amazon Bedrock is a fully managed service that offers a choice of high-performing Foundation Models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Metrics 107

Metrics Enterprise APIs Engineering 107

AWS Machine Learning

MARCH 4, 2025

Customizable Uses prompt engineering , which enables customization and iterative refinement of the prompts used to drive the large language model (LLM), allowing for refining and continuous enhancement of the assessment process. Your data remains in the AWS Region where the API call is processed.

Best practices 105

Best practices Enterprise Engineering Strategic Value 105

AWS Machine Learning

NOVEMBER 15, 2024

Use cases we have worked on include: Technical assistance for field engineers – We built a system that aggregates information about a company’s specific products and field expertise. A chatbot enables field engineers to quickly access relevant information, troubleshoot issues more effectively, and share knowledge across the organization.

APIs 117

APIs Engineering Chatbots Construction 117

AWS Machine Learning

JANUARY 7, 2025

The solution proposed in this post relies on LLMs context learning capabilities and prompt engineering. The translation playground could be adapted into a scalable serverless solution as represented by the following diagram using AWS Lambda , Amazon Simple Storage Service (Amazon S3), and Amazon API Gateway.

Engineering 104

Engineering Metrics industry standards Finance 104

AWS Machine Learning

FEBRUARY 25, 2025

These delays can lead to missed security errors or compliance violations, especially in complex, multi-account environments. Amazon Bedrock Agents is a fully managed service that helps developers create AI agents that can break down complex tasks into steps and execute them using FMs and APIs to accomplish specific business objectives.

APIs 64

APIs Accountability Engineering Construction 64

AWS Machine Learning

OCTOBER 30, 2023

It allows developers to build and scale generative AI applications using FMs through an API, without managing infrastructure. Customers are building innovative generative AI applications using Amazon Bedrock APIs using their own proprietary data.

APIs 140

APIs Big data Accountability Enterprise 140

AWS Machine Learning

NOVEMBER 22, 2023

We also use Vector Engine for Amazon OpenSearch Serverless (currently in preview) as the vector data store to store embeddings. Here’s how RAG operates: Data sources – RAG can draw from varied data sources, including document repositories, databases, or APIs. Lewis et al. An Amazon SageMaker Studio domain and user.

Engineering 118

Engineering Chatbots Benchmark APIs 118

AWS Machine Learning

OCTOBER 8, 2024

Challenges with traditional onboarding The traditional onboarding process for banks faces challenges in the current digital landscape because many institutions don’t have fully automated account-opening systems. This constraint impacts the flexibility for customers to initiate account opening at their preferred time.

Banking 110

Banking APIs Accountability Engineering 110

AWS Machine Learning

MAY 15, 2024

Here, Amazon SageMaker Ground Truth allowed ML engineers to easily build the human-in-the-loop workflow (step v). Under the hood, this tool uses artifacts generated by SageMaker (step vii) which is then deployed into the production AWS account (step viii), using SageMaker SDKs. The Amazon API Gateway receives the PUT request (step 1).

Advertising 127

Advertising APIs Engineering Benchmark 127

AWS Machine Learning

MAY 15, 2024

This post demonstrates how to use advanced prompt engineering to control an LLM’s behavior and responses. The Amazon Bedrock API returns the output Q&A JSON file to the Lambda function. The container image sends the REST API request to Amazon API Gateway (using the GET method). The Docker engine.

Education 134

Education APIs Engineering Banking 134

AWS Machine Learning

NOVEMBER 19, 2024

Leave the session inspired to bring Amazon Q Apps to supercharge your teams’ productivity engines. Learn how they created specialized agents for different tasks like account management, repos, pipeline management, and more to help their developers go faster.

APIs 92

APIs Enterprise Best practices Government 92