Favorite Your contact center connects your business to your community, enabling customers to order products, callers to request support, clients to make appointments, and much more. When calls go well, callers retain a positive image of your brand, and are likely to return and recommend you to others. And the
Favorite In many industries, including financial services, banking, healthcare, legal, and real estate, automating document handling is an essential part of the business and customer service. In addition, strict compliance regulations make it necessary for businesses to handle sensitive documents, especially customer data, properly. Documents can come in a variety
Favorite In the summer, Dr. Gino Caspari’s day starts at 5:30 a.m. in Siberia, where he studies the ancient Scythians with the Swiss National Science Foundation. There, he looks for burial places of these nomadic warriors who rode through Asia 2,500 years ago. The work isn’t easy, from dealing with
Favorite Discrete and continuous manufacturing lines generate a high volume of products at low latency, ranging from milliseconds to a few seconds. To identify defects at the same throughput of production, camera streams of images must be processed at low latency. Additionally, factories may have low network bandwidth or intermittent
Favorite Computer vision algorithms are at the core of many deep learning applications. Self-driving cars, security systems, healthcare, logistics, and image processing all incorporate various aspects of computer vision. But despite their ubiquity, training computer vision algorithms, like Mask or Cascade RCNN, is hard. These models employ complex architectures, train
Favorite Multi-object tracking (MOT) in video analysis is increasingly in demand in many industries, such as live sports, manufacturing, surveillance, and traffic monitoring. For example, in live sports, MOT can track soccer players in real time to analyze physical performance such as real-time speed and moving distance. Previously, most methods
Favorite AutoML is a powerful capability, provided by Amazon SageMaker Autopilot, that allows non-experts to create machine learning (ML) models to invoke in their applications. The problem that we want to solve arises when, due to governance constraints, Amazon SageMaker resources can’t be deployed in the same AWS account where
Favorite Customers in many different domains tend to work with multiple sources for their data: object-based storage like Amazon Simple Storage Service (Amazon S3), relational databases like Amazon Relational Database Service (Amazon RDS), or data warehouses like Amazon Redshift. Machine learning (ML) practitioners are often driven to work with objects
Favorite GAN is a generative ML model that is widely used in advertising, games, entertainment, media, pharmaceuticals, and other industries. You can use it to create fictional characters and scenes, simulate facial aging, change image styles, produce chemical formulas synthetic data, and more. For example, the following images show the
Favorite Building accurate computer vision models to detect objects in images requires deep knowledge of each step in the process—from labeling, processing, and preparing the training and validation data, to making the right model choice and tuning the model’s hyperparameters adequately to achieve the maximum accuracy. Fortunately, these complex steps