October 11, 2018
Nvidia announced this week at GTC Europe that Kings College London would deploy Nvidia’s DGX-2 and Clara medical imaging analysis platform to improve radiology and pathology practices. This is the first Clara deployment in Europe and evidence of AI’s growing adoption in health care where for years a wide variety of instruments, not least imaging devices, have been producing large datasets. Read more…
January 5, 2015
The Veterans Health Administration wants to improve efficiency and patient care and it's counting on IBM Watson analytics technology to help it achieve these go Read more…
August 21, 2013
San Diego Supercomputer Center (SDSC) is announcing a bold new cloud and analytics-based initiative, called Sherlock. Established by SDSC with the assistance of SD Technology and Chickasaw Nation Industries, the Sherlock-branded project represents an "extensive portfolio of information technology services for healthcare and government." Read more…
March 12, 2013
University of Southern California students compete to identify Watson's next gig. Read more…
September 15, 2011
IBM Watson to start new job as WellPoint analyst. Read more…
September 13, 2011
Health care analytics is an emerging application area that promises to help cut costs and provide better patient outcomes. To reach that goal though requires sophisticated software that can mimic some of the intelligence of real live physicians. In Sweden, researchers are attempting to do just that by building a model of heart-transplant recipients and donors to improve survival times. Read more…
June 2, 2011
Advanced analytics sets its sights on health care. Read more…
March 11, 2010
US health care is sick, but help may be on the way, says Leroy Hood. Read more…
The increasing complexity of electric vehicles result in large and complex computational models for simulations that demand enormous compute resources. On-premises high-performance computing (HPC) clusters and computer-aided engineering (CAE) tools are commonly used but some limitations occur when the models are too big or when multiple iterations need to be done in a very short term, leading to a lack of available compute resources. In this hybrid approach, cloud computing offers a flexible and cost-effective alternative, allowing engineers to utilize the latest hardware and software on-demand. Ansys Gateway powered by AWS, a cloud-based simulation software platform, drives efficiencies in automotive engineering simulations. Complete Ansys simulation and CAE/CAD developments can be managed in the cloud with access to AWS’s latest hardware instances, providing significant runtime acceleration.
Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.
Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
With so many applications and diverse requirements for data types, management systems, workloads, and compliance regulations, these challenges are only amplified. Without a clear, continuous flow of data throughout the AI data lifecycle, AI models can perform poorly or even dangerously.
To ensure your AI systems are optimized, follow these five essential steps to eliminate bottlenecks and maximize efficiency.
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