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How AI powers innovation in federal government services

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lloyd-granville
Lloyd Granville
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Most of us can remember a time before the internet when terms like "artificial intelligence," "smart city," and “Internet of Things” (IoT) didn't even exist—except maybe in sci-fi movies. Today, as the horizons of our world expand, we can't imagine life without the internet. As we continue to innovate, public sector resources must also evolve exponentially to accommodate current and future growth. There is a seemingly endless cycle of urban planning and infrastructure improvements. Addressing social impacts and economic functions—down to the locations where different services and activities will reside—as well as environmental, social, and political concerns, are all areas that fall under the purview of federal government services. All of these areas are being revolutionized by artificial intelligence (AI) applications, which are reshaping our cities in the hope of a better tomorrow.

Public sector government services that support our lives, like power, sewer, trash and recycling, public safety (police, fire, and emergency medical services), and so on are constantly evolving as technology makes them smaller, smarter, faster, and more interconnected. AI, coupled with data ingested from the vast number of IoT tools, enables government services to study what works well in cities and what causes most problems or disruptions.

Solving public sector challenges with AI

This data is used to power AI-assisted technologies that help improve things like the construction trades, removing analog issues and challenges and improving our cities' infrastructures. Safety concerns, labor shortages, and cost and schedule overruns can be efficiently and accurately overcome by using AI systems to manage public sector infrastructure improvement projects. In fact, AI, robotics, and IoT can reduce building costs by up to 20%,  thanks to the ability of AI to optimize workflows and processes in ways that human beings can’t.

AI–evolving our tomorrow

AI is the driving force behind the vast improvements in many public safety organizations like law enforcement and first responder agencies. These organizations use a wide range of IoT sensors to gather video and data that’s crucial to crime investigations and other public safety initiatives. At the core of these solutions, the data is inferenced using purpose-built compute and storage resources available on premises and in the cloud to speed AI results.

As AI systems become exponentially more powerful and cost effective, they will continue to evolve and be deployed throughout the public safety and infrastructure operational environment.

In order to simplify infrastructure and accelerate ROI, the underlying platforms that support AI systems for federal government services must be able to scale and unify AI workloads across the hybrid cloud or multicloud for training, inferencing, and data analytics. And all of this must happen at lightning speed, which means that you can’t run your workloads on underperforming compute and storage resources.

Building your AI framework for federal government services

NVIDA DGX A100 is a universal building block for data center AI, supporting deep learning training, inferencing, data science, and other high-performance workloads from a single platform. NetApp and NVIDIA have been collaborating for several years to deliver AI solutions that help enterprises accelerate AI adoption. DGX A100-based solutions, built using the new NVIDIA Ampere architecture, deliver up to 6 times the training performance of the previous generation. The solutions provide the equivalent of a data center of computing infrastructure for analytics, training, and inferencing, consolidated in a single system.

NetApp and NVIDIA are collaborating closely on the following solutions that combine the benefits of DGX A100 and NetApp's proven solutions for high-performance storage and advanced data management.

  • NetApp® ONTAP® AI. This joint solution, which combines NVIDIA DGX systems and NetApp AFF storage, simplifies procurement, configuration, installation, and support for AI workloads.
  • NVIDIA DGX SuperPOD with NetApp. SuperPOD is NVIDIA’s flagship large-scale AI infrastructure; NVIDIA and NetApp have announced their commitment to support NetApp EF-Series AI with BeeGFS.

ONTAP AI helps you simplify, accelerate, and scale the data pipeline needed for AI to gain a deeper understanding in less time. NetApp AFF systems keep data flowing with the industry's fastest and most flexible all-flash storage, featuring end-to-end NVMe technologies. AFF and a data fabric powered by NetApp enable you to create a data pipeline that spans from edge to core to cloud. To learn more about NetApp AI solutions for federal government services, visit our public sector page.

Lloyd Granville

Lloyd Granville is Deputy CTO, Department of Defense at NetApp. Lloyd works as part of a team of Deputy CTOs within NetApp's Global Strategy and Technology Office. Supporting NetApp's U.S. Public Sector division, he is responsible for developing CIO/CTO/Director level strategies, solution architectures, and supporting partner initiatives for customers across the Department of Defense. His activities result in secure and scalable Data Services for hybrid cloud or traditional & non-traditional IT environments that enhance the warfighter's ability to execute challenging missions. He has deep technical knowledge of Public Sector Infrastructures, especially within the DoD. Before his role as our CTO for the Department of Defense, Lloyd retired as an Army Chief Warrant Officer 4, serving 23 years on active duty, designing, implementing, and managing IT enterprise architectures that supported many efforts from Military Intelligence to Special Operations missions throughout his Army career.

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