Category: Artificial Intelligence

In this blog post, we introduce you to Glean – an enterprise-ready search and knowledge discovery solution that’s tailor-made for the enterprise workplace. Glean has been adopted by leading enterprise customers, including Databricks, Okta, and Grammarly, to solve their internal search and knowledge discovery needs. Now available in AWS Marketplace, Glean uses powerful large language models (LLMs) hosted by Amazon Bedrock to deliver generative AI solutions to the millions of customers building on AWS.

In this post, we will show how it may be possible to avoid wastage and better forecast food needs using PredictHQ’s dataset with  Amazon Forecast and other machine learning services.

In this blog post, Sandeep, Malini, Bakha, and Aparna will show how to convert your healthcare data to FHIR format and load it into AWS HealthLake using HiPaaS FHIR data converter solution. This solution enables you to access and manage the data from various sources without the need for manual data entry or reconciliation.

In this post, Brian, Snehanshu, and I’ll show you how to mask healthcare data for regulatory compliance using Amazon HealthLake and DataMasque.

In this post, I show how to use InfinStor MLflow with Amazon SageMaker Studio to experiment, collaborate, train, and run inferences using this ML platform. With this solution, you do not need to write special code for experiment tracking or model management. You can also share experiments and models with authorized colleagues. SageMaker Studio provides the Notebook and remote IPython kernel portion of the solution, and InfinStor MLflow provides the experiment tracking and model management.

In this blog post, I highlight success stories featuring solutions available in AWS Marketplace. Industry experts from Generali Thailand, an insurance firm, and C2L BIZ Solutions Pvt. Ltd., an insurance technology firm, share their business challenges and the business impact of using solutions available in AWS Marketplace.

This post shares AWS Marketplace re:Invent breakout sessions happening on Monday, November 28, along with other information.

In this blog post, Jeff, Mike, and I will show you how to discover and use no-cost open data datasets on AWS Data Exchange. We will also show you how to enrich the open data with a paid dataset and how to import these datasets into Amazon SageMaker and do an analysis against them.

In the past two years, use of media has changed considerably. Media production companies had to accelerate their adoption of cloud-based infrastructure and technologies to support the shift to home consumption and remote work. As this shift occurs, media providers are looking to diversify revenue streams to take better advantage of consumer spending for entertainment. […]

As AWS consultants, Victor and I often get asked about recommendations on the right instance configuration to use for real-time inference. Finding the correct instance size to host your trained machine learning (ML) models might be a challenging task. However, choosing the right instance and auto scaling configuration can help reduce model serving costs without […]