This Solution Brief illustrates how Arya.ai provides a relatively simple and cost-effective pathway for financial services organizations and other enterprise customers to integrate AI into their business models.
This Solution Brief illustrates how Mphasis was able to run demanding machine learning and deep learning workloads on industry-standard servers, without the need for costly, specialized hardware platforms achieving faster performance for Mphasis DeepInsights* with Intel® Xeon® Scalable processors.
This Solution Brief explains how an integrated solution advances artificial intelligence (AI) with development with H2O.ai's industry-leading software, validated and benchmarked on optimized Intel® technologies.
This Solution Brief explains how Verbio uses network edge servers based on Intel® Xeon® Scalable processors with optimized software to maximize performance and take advantage of reduced latency.
This Solution Brief explains how BigData Corp is taking advantage of the latest advances in AI to help its customers extract even higher value from available data and using Intel software tools to greatly increase inference performance.
This Solution Brief highlights how engineers and developers at HOOBOX are using hardware and software technologies from the Intel® artificial intelligence portfolio to optimize their algorithms that detect and interpret facial expressions, giving tetraplegic (quadriplegic) individuals new autonomy to control their wheelchairs with just a glance.
This Data Sheet explains how Gamalon Idea Learning Studio can help you better understand your customers through next generation natural language understanding.
Forrester Consulting conducted a Total Economic Impact™ (TEI) study to provide readers with a framework to evaluate the potential financial impact of Ready Solutions for AI on their organizations. To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed six customers with experience using Ready Solutions for AI.
In this joint work, DellEMC, SURFsara, and Intel extended the research using VGG-16 and ResNet-50 CNN models scaled out across a large number of Intel® Xeon® Scalable processors running on Dell EMC’s Zenith supercomputer and accurately pre-trained on the ImageNet2012-1K dataset. The team was able to significantly reduce the training time and outperform the CheXNet-121 published results in four pathological categories using VGG-16 and up to 10 categories (including pneumonia and emphysema).
This post illustrates how upgrading to servers based on the latest Intel® Xeon® Platinum 8168 processor provided a 1.49X boost in neural network performance for Taboola.