article thumbnail

Getting started with computer use in Amazon Bedrock Agents

AWS Machine Learning

In this post, we create a computer use agent demo that provides the critical orchestration layer that transforms computer use from a perception capability into actionable automation. This demo deploys a containerized application using AWS Fargate across two Availability Zones in the us-west-2 Region.

APIs 135
article thumbnail

AI-Driven Customer Service Demands Humanized CX

TechSee

Check out how Sophie AI’s cognitive engine orchestrates smart interactions using a multi-layered approach to AI reasoning. Book a live demo and discover how Sophie AI can reshape your AI-driven customer service, reduce operational costs, and unlock new revenue opportunities. ” Curious how it works?

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning

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. Add a new user to the Amazon Cognito user pool deployed by the AWS CDK during the setup.

article thumbnail

Large-scale feature engineering with sensitive data protection using AWS Glue interactive sessions and Amazon SageMaker Studio

AWS Machine Learning

As data is growing at an exponential rate, organizations are looking to set up an integrated, cost-effective, and performant data platform in order to preprocess data, perform feature engineering, and build, train, and operationalize ML models at scale. A key component of the model building and development process is feature engineering.

article thumbnail

Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

AWS Machine Learning

We specifically instruct the LLM to first mimic a step-by-step thought process for arriving at the answer (chain-of-thought reasoning), an effective measure of prompt-engineering to improve the output quality. For this demo setup, we describe the manual steps taken in the AWS console.

APIs 114
article thumbnail

Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

AWS Machine Learning

The top-level definitions of these abstractions are included as part of the prompt context for query generation, and the full definitions are provided to the SQL execution engine, along with the generated query. The demo code is available in the GitHub repository. She holds an undergraduate degree in Computer Science & Engineering.

article thumbnail

How Formula 1® uses generative AI to accelerate race-day issue resolution

AWS Machine Learning

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. Because the solution doesnt require domain-specific knowledge, it even allows engineers of different disciplines and levels of expertise to resolve issues.

APIs 71