Category: Artificial Intelligence

One challenge enterprises face when they implement an intelligent search solution for their large data sources, is the ability to quickly provide relevant search results. When working with large data sources, not all features or attributes within your data will be equally relevant to all your users. We want to prioritize identifying and boosting specific […]

Customers are building databases, data warehouses, and data lake solutions in isolation from each other, each having its own separate data ingestion, storage, management, and governance layers. Often these disjointed efforts to build separate data stores end up creating data silos, data integration complexities, excessive data movement, and data consistency issues. These issues are preventing […]

Multi-modal transportation is one of the biggest developments in the logistics industry. There has been a successful collaboration across different transportation partners in supply chain freight forwarding for many decades. But there’s still a considerable overhead of paperwork processing for each leg of the trip. Tens of billions of documents are processed in ocean freight […]

In an evolving world that is increasingly connected, data-centric, and fast-paced, the sports industry is no exception. Amazon Web Services (AWS) has been helping customers in the sports industry gain real-time insights through analytics. You can re-invent and reimagine the fan experience by tracking sports actions and activities. In this blog post, we will highlight […]

Free trial promotions are a popular marketing tactic, but they can also be a common source of fraud for ecommerce retailers. So, how do you identify fraudulent users? And what are some effective ways to prevent free trial abuse? This blog post outlines common free trial abuse attack vectors and presents prevention techniques. We’ll show […]

As part of AWS Professional Services, we work with customers across different industries to understand their needs and supplement their teams with specialized skills and experience. Some of our customers are internal teams from the Amazon retail organization who request our help with their initiatives. One of these teams, the Global Environmental Affairs team, identifies […]

This Field Notes blog post in 2020 explains how to build an Autonomous Driving Data Lake using this Reference Architecture. Many organizations face the challenge of ingesting, transforming, labeling, and cataloging massive amounts of data to develop automated driving systems. In this re:Invent session, we explored an architecture to solve this problem using Amazon EMR, Amazon […]

In this blog post, we demonstrate how to build an automated and scalable data pipeline for autonomous driving. This solution was built with the goal of accelerating the process of analyzing recorded footage and training a model to improve the experience of autonomous driving. We will demonstrate the extraction of images from ROS bag file […]

Organizational analytics systems have shifted from running in the background of IT systems to being critical to an organization’s health. Analytics systems help businesses make better decisions, but they tend to be complex and are often not agile enough to scale quickly. To help with this, customers upgrade their traditional on-premises online analytic processing (OLAP) […]

One of the challenges businesses have is to constantly monitor information via media outlets and be alerted when a key interest is picked up, such as individual, product, or company information. One way to do this is to scan media and news feeds against a company watchlist. The list may contain personal names, organizations or […]