Category: Artificial Intelligence

Organizations have matured and have overcome the initial hurdles of proving the capabilities of AI. The challenge now is operationalizing AI and building engineering excellence to successfully adopt and manage machine learning at scale. Learn how Quantiphi assisted Venterra Realty in bringing in the best ML solution development and deployment practices through NeuralOps—a framework built on Amazon SageMaker.

With Amazon Comprehend, the implementation of natural language processing and machine learning has become a simple, routine task. Organizations no longer have to spend hours trying to pick the right algorithm, as Amazon Comprehend automatically selects the best ones for any given use case. To explore this benefit, learn about an implementation of Amazon Comprehend for risk prediction and sentiment analysis on the observations in clinical trials sites.

In computer vision applications, the transmission of video data to the cloud for analysis can result in added delays due to various contributing factors such as queuing, propagation, and network latency. Learn how the Nordcloud team, in collaboration with AWS, has designed a “Computer Vision at the Edge” solution based on AWS Panorama. It caters to organizations seeking low-latency decision making without the burden of managing complex technology.

Metal Toad has been working with major entertainment brands for decades, including keeping some of the highest-profile media sites live under unique traffic conditions. Keeping these sites up and running is one of Metal Toad’s superpowers, but the AWS Digital Customer Experience Competency Partner couldn’t do it without the tools provided by AWS. Explore some of the strategies Metal Toad deployed to protect a customer’s site during an event where failure was not an option.

Customer service agents communicate with many individuals using channels such as inbound and outbound calls, emails, chats, and social media messaging. For channels like email or social media messaging, there is typically a target timeframe within which the agent needs to reply to the customer. Learn about an AI-powered solution called Smart Reply developed by Axrail, an AWS Advanced Tier Services Partner that provides outcome-based digital transformation through analytics and application modernization.

Increased competition, labor shortages, and changing customer expectations have forced organizations to rethink their document-based processes. Learn how Hyperscience addresses the limitations of legacy automation solutions to help insurance agencies optimize document processing. Explore how incorporating machine learning into automation solutions leads to greater end-to-end automation, more engaging work, and better business outcomes.

A small number of companies manage to leverage the true value of their machine learning proofs of concept, and the majority of those are still struggling to overcome the experiment-production gap for their AI applications fueled by machine learning and data. Learn about MLOps, why organizations should care about it on their AI journey, and how DXC Technology and AWS can help to quickly integrate MLOps best practices into your daily business using the MLOps Quick Start for MLOps on AWS.

Amazon Redshift is a column-oriented database management system that stores data in columns, making it quicker to analyze data. The platform also performs a continuous backup of data, eliminating the risk of losing data or the need to plan for backup hardware. Learn how Hexaware’s automated platform, Amaze for Data & AI, transforms on-premises data warehouse ecosystems to the cloud while ensuring business keeps running smoothly and uninterrupted.

CLEAR Vison Cloud from Prime Focus Technologies (PFT) enables streaming platforms, studios, and broadcasters to automatically process, manage, and monetize their content supply chain using cloud-based AI/ML workflows and media services. Learn how the solution leverages a blend of AI/ML models deployed using Amazon EKS with a zero-node design. This model results in a >90% increase in compute efficiency and processor utilization, while maintaining customer SLA-mandated delivery timelines.

Traditional content process workflows are expensive and complex to enhance with artificial intelligence and machine learning technologies. Kablamo’s Digital Asset Management (DAM) solution on AWS leverages leading AI/ML services to enable customers to secure, index, cold-store, and access digital assets across the enterprise. Learn how Kablamo DAM is right-sized for all customer industries and integrates into existing workflows with ease.