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

Favorite Generative AI agents are a versatile and powerful tool for large enterprises. They can enhance operational efficiency, customer service, and decision-making while reducing costs and enabling innovation. These agents excel at automating a wide range of routine and repetitive tasks, such as data entry, customer support inquiries, and content

Read More
Shared by AWS Machine Learning February 8, 2024

Integrate QnABot on AWS with ServiceNow

Favorite Do your employees wait for hours on the telephone to open an IT ticket? Do they wait for an agent to triage an issue, which sometimes only requires restarting the computer? Providing excellent IT support is crucial for any organization, but legacy systems have relied heavily on human agents

Read More
Shared by AWS Machine Learning February 6, 2024

How HSR.health is limiting risks of disease spillover from animals to humans using Amazon SageMaker geospatial capabilities

Favorite This is a guest post co-authored by Ajay K Gupta, Jean Felipe Teotonio and Paul A Churchyard from HSR.health. HSR.health is a geospatial health risk analytics firm whose vision is that global health challenges are solvable through human ingenuity and the focused and accurate application of data analytics. In

Read More
Shared by AWS Machine Learning February 5, 2024

Announcing support for Llama 2 and Mistral models and streaming responses in Amazon SageMaker Canvas

Favorite Launched in 2021, Amazon SageMaker Canvas is a visual, point-and-click service for building and deploying machine learning (ML) models without the need to write any code. Ready-to-use Foundation Models (FMs) available in SageMaker Canvas enable customers to use generative AI for tasks such as content generation and summarization. We

Read More
Shared by AWS Machine Learning February 5, 2024

Getting started with Amazon Titan Text Embeddings

Favorite Embeddings play a key role in natural language processing (NLP) and machine learning (ML). Text embedding refers to the process of transforming text into numerical representations that reside in a high-dimensional vector space. This technique is achieved through the use of ML algorithms that enable the understanding of the

Read More
Shared by AWS Machine Learning February 1, 2024