Generative AI has opened up a lot of potential in the field of AI. We are seeing numerous uses, including text generation, code generation,...

Customers are faced with increasing security threats and vulnerabilities across infrastructure and application resources as their digital footprint has expanded and the business impact...

Organizations are acutely aware of the value of data in today's data-driven financial services world. However, many organizations continue to face a significant challenge: data silos. These...

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative...

The driving element behind decision-making is data. Marketers and advertisers rely on a plethora of data to fine-tune their plans, optimize campaigns, and efficiently reach their target...

Amazon SageMaker Domain supports SageMaker machine learning (ML) environments, including SageMaker Studio and SageMaker Canvas. SageMaker Studio is a fully integrated development environment (IDE)...

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. You can...

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every...

In computer vision (CV), adding tags to identify objects of interest or bounding boxes to locate the objects is called labeling. It’s one of...

This post is co-written with Aruna Abeyakoon and Denisse Colin from Light and Wonder (L&W). Headquartered in Las Vegas, Light & Wonder, Inc. is...

Implementing a modern data architecture provides a scalable method to integrate data from disparate sources. By organizing data by business domains instead of infrastructure,...

Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet...