Remove Lambda Remove Scalability Remove System Design
article thumbnail

Creating asynchronous AI agents with Amazon Bedrock

AWS Machine Learning - AI

Much like traditional business process automation through technology, the agentic AI architecture is the design of AI systems designed to resolve complex problems with limited or indirect human intervention. Conversely, asynchronous event-driven systems offer greater flexibility and scalability through their distributed nature.

article thumbnail

Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

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. The user can pick the two documents that they want to compare.

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

Knowledge Bases for Amazon Bedrock now supports advanced parsing, chunking, and query reformulation giving greater control of accuracy in RAG based applications

AWS Machine Learning - AI

Now that you understand the concepts for semantic and hierarchical chunking, in case you want to have more flexibility, you can use a Lambda function for adding custom processing logic to chunks such as metadata processing or defining your custom logic for chunking. Make sure to create the Lambda layer for the specific open source framework.

article thumbnail

Medical content creation in the age of generative AI

AWS Machine Learning - AI

The solution has been designed using the following services: Amazon Elastic Container Service (ECS) : to deploy and manage our Streamlit UI. Amazon Lambda : to run the backend code, which encompasses the generative logic. In step 5, the lambda function triggers the Amazon Textract to parse and extract data from pdf documents.

article thumbnail

How Mixbook used generative AI to offer personalized photo book experiences

AWS Machine Learning - AI

S3, in turn, provides efficient, scalable, and secure storage for the media file objects themselves. The inference pipeline is powered by an AWS Lambda -based multi-step architecture, which maximizes cost-efficiency and elasticity by running independent image analysis steps in parallel.

article thumbnail

Journey to Event Driven – Part 3: The Affinity Between Events, Streams and Serverless

Confluent

Given that it is at a relatively early stage, developers are still trying to grok the best approach for each cloud vendor and often face the following question: Should I go cloud native with AWS Lambda, GCP functions, etc., The key to event-first systems design is understanding that a series of events captures behavior.

article thumbnail

Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

At a high level, the AWS Step Functions pipeline accepts source data in Amazon Simple Storage Service (Amazon S3) , and orchestrates AWS Lambda functions for ingestion, chunking, and prompting on Amazon Bedrock to generate the fact-wise JSONLines ground truth.