ml 14481 image001

Capture public health insights more quickly with no-code machine learning using Amazon SageMaker Canvas

Public health organizations have a wealth of data about different types of diseases, health trends, and risk factors. Their staff has long used statistical models and regression analyses to make important decisions such as targeting populations with the highest risk factors for a disease with therapeutics, or forecasting the progression of concerning outbreaks. When public …

CrowdAI NVIDIA blog photo

Watch This Space: New Field of Spatial Finance Uses AI to Estimate Risk, Monitor Assets, Analyze Claims

When making financial decisions, it’s important to look at the big picture — say, one taken from a drone, satellite or AI-powered sensor. The emerging field of spatial finance harnesses AI insights from remote sensors and aerial imagery to help banks, insurers, investment firms and businesses analyze risks and opportunities, enable new services and products, …

Prefix2520conditioning2520hero

Unifying image-caption and image-classification datasets with prefix conditioning

Posted by Kuniaki Saito, Student Researcher, Cloud AI Team, and Kihyuk Sohn, Research Scientist, Perception Team Pre-training visual language (VL) models on web-scale image-caption datasets has recently emerged as a powerful alternative to traditional pre-training on image classification data. Image-caption datasets are considered to be more “open-domain” because they contain broader scene types and vocabulary …

ml 14479 image001

Use proprietary foundation models from Amazon SageMaker JumpStart in Amazon SageMaker Studio

Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. With SageMaker JumpStart, you can discover and deploy publicly available and proprietary foundation models to dedicated Amazon SageMaker instances for your generative AI applications. SageMaker JumpStart allows you to deploy foundation models from a network isolated environment, and …