Remove Architecture Remove Lambda Remove Storage Remove Virtualization
article thumbnail

Enhance conversational AI with advanced routing techniques with Amazon Bedrock

AWS Machine Learning - AI

This is done using ReAct prompting, which breaks down the task into a series of steps that are processed sequentially: For device metrics checks, we use the check-device-metrics action group, which involves an API call to Lambda functions that then query Amazon Athena for the requested data. It serves as the data source to the knowledge base.

article thumbnail

5 Questions to Ask Before Going Serverless

Modus Create

When serverless architecture became all the rage a few years ago, we wondered whether it was just marketing hype. Serverless architecture’s popularity has risen over the past 5 years. You don’t have to manage servers to run apps, storage systems, or databases at any scale. Was serverless really cloud 2.0

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

Fundamentals of Data Engineering

Xebia

The data engineer is also expected to create agile data architectures that evolve as new trends emerge. Building architectures that optimize performance and cost at a high level is no longer enough. The best data engineers view their responsibilities through business and technical lenses.

article thumbnail

Boost employee productivity with automated meeting summaries using Amazon Transcribe, Amazon SageMaker, and LLMs from Hugging Face

AWS Machine Learning - AI

The prevalence of virtual business meetings in the corporate world, largely accelerated by the COVID-19 pandemic, is here to stay. Based on a survey conducted by American Express in 2023, 41% of business meetings are expected to take place in hybrid or virtual format by 2024.

article thumbnail

AWS Microservices Architecture – Enabling Faster Application Development

RapidValue

In an effort to avoid the pitfalls that come with monolithic applications, Microservices aim to break your architecture into loosely-coupled components (or, services) that are easier to update independently, improve, scale and manage. Key Features of Microservices Architecture. Microservices Architecture on AWS.

article thumbnail

Build generative AI agents with Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain

AWS Machine Learning - AI

This solution is intended to act as a launchpad for developers to create their own personalized conversational agents for various applications, such as virtual workers and customer support systems. Solution architecture The following diagram illustrates the solution architecture. ConversationTable – Stores conversation history.

article thumbnail

Automate the insurance claim lifecycle using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Solution overview The objective of this solution is to act as a foundation for customers, empowering you to create your own specialized agents for various needs such as virtual assistants and automation tasks. The following diagram illustrates the solution architecture. The following are some example prompts: Create a new claim.