Nvidia launches AI edge and hybrid cloud services to support enterprise workloads

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Nvidia today launched two new products, AI LaunchPad and Fleet Command, designed to connect companies with infrastructure designed for AI workloads. AI LaunchPad delivers access to Nvidia-powered hardware and services through hybrid cloud partners, while Fleet Command — which was announced earlier this year — assists with deploying and managing AI deployments across different locations.

The pandemic has accelerated digital transformations throughout sectors in the enterprise. According to a recent Algorithmia survey, 76% of companies are prioritizing AI and machine learning in their 2021 IT budgets. And AI budgets are up significantly (55%) over the past year, Appen found.

With AI LaunchPad, Nvidia partners including Equinix provide hybrid cloud environments that support AI training and inference, deployment at the edge, and other aspects of data science. For example, Equinix customers can run AI apps on Nvidia DGX SuperPODs and use Base Command, Nvidia’s AI lifecycle management product, to orchestrate and deploy jobs on Nvidia-certified systems.

AI LaunchPad leverages Nvidia’s AI Enterprise analytics software running on VMware vSphere, VMware’s cloud computing virtualization platform, as well as BlueField DPUs, Nvidia’s AI-focused datacenter machine lineup. “Today’s enterprises are looking for a simple, comprehensive solution that provides instant access to the resources they need to build and deploy AI with ease,” Nvidia head of enterprise computing Manuvir Das said in a press release. “AI LaunchPad is putting AI at the fingertips of enterprises everywhere with fully automated, hybrid-cloud infrastructure and software for every stage of the AI lifecycle.”

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Fleet Command

As for Fleet Command, which today became generally available, it lets businesses roll out and manage AI apps by installing, updating, and managing them from a central location. Via Fleet Command, developers can add or delete apps, update system software, and monitor the health of devices in tandem with or independently of Base Command, Nvidia’s AI app development hub.

In these respects, Fleet Command is comparable to existing tools aimed at simplifying internet of things (IoT) development and management at the edge. They include Amazon’s Amazon Web Services (AWS) IoT, Google’s Cloud IoT Edge, Baidu’s OpenEdge, and Microsoft’s Azure Sphere, in addition to Zededa, Particle, and Balena.

“The ability to deploy and manage AI apps at the edge is one of the most complex problems facing businesses as they move toward an IoT era, including smart factories, intelligent retail, and smart cities,” Das continued. “Fleet Command drives efficiency across a business, helping scale edge AI with unprecedented speed.”

Nvidia’s datacenter business is quickly becoming a major revenue driver for the company. In February, Nvidia’s datacenter division posted a record $1.75 billion, up 167% from the same period a year ago. And with the edge computing market anticipated to be worth $43.4 billion by 2027, according to Million Insights, the company’s investment in products that complement and augment datacenter applications, like Fleet Command, seem prescient.

Nvidia recently launched TAO, a product designed to help enterprises choose and deploy models in a range of computing environments. And it made available Jarvis, a framework with pretrained models and software tools to create conversational experiences.


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