How can corporate enterprises make the most of generative AI? High-tech giants are quickly ramping up efforts to help answer that question, and this week saw Nvidia working with two big partners–Dell Technologies and Microsoft–on separate projects designed to smooth the path of generative AI options for enterprises.
The partnership with Dell nods to the notion that some enterprise are going to want to have on-premises use of generative AI to customize applications built on their own proprietary data, while the work with Microsoft brings the full power of Nvidia’s AI software frameworks to an Azure cloud offering.
At the Dell Technologies World event in Las Vegas, Dell and Nvidia announced a joint initiative to provide businesses with the blueprints, infrastructure, and software to help them quickly and easily build and use generative AI models on-premises to support better customer service, market intelligence, enterprise search, and a range of other capabilities.
“We have worked with a lot enterprise companies on generative AI in the last few months, what we have learned is that there are a large number of enterprise companies that would like to leverage the power of generative AI but in fact, do it in their own datacenter or do it outside of the public cloud,” said Manuvir Das, vice president of enterprise computing at Nvidia.
The partners’ Project Helix effort aims to support “the complete generative AI lifecycle” by delivering a series of full-stack solutions with technical expertise and pre-built tools based on Dell and Nvidia infrastructure and software, along with a complete blueprint for how to leverage proprietary enterprise data and more easily deploy generative AI responsibly and accurately, the companies said.
The hardware and software involved includes Dell PowerEdge servers with Nvidia H100 GPUs, such as the PowerEdge XE9680 and PowerEdge R760xa, which Dell says are optimized to deliver performance for generative AI training and AI inferencing; unstructured data storage through Dell PowerScale and Dell ECS Enterprise Object Storage; and Nvidia’s AI Enterprise software, including the NeMo large language model framework and NeMo Guardrails software for building topical, safe, and secure generative AI chatbots.
“It is soup to nuts all the hardware and software and services and support and architecture that data scientists need to put a solution together,” reducing teh complexity of bringing generative AI to the enterprise premises, Das said..
“Companies are eager to explore the opportunities that generative AI tools enable for their organizations, but many aren’t sure how to get started,” said Bob O’Donnell, president and chief analyst, TECHnalysis Research, in a statement provided by Nvidia. “By putting together a complete hardware and software solution from trusted brands, Dell Technologies and Nvidia are offering enterprises a head start to building and refining AI-powered models that can leverage their own company’s unique assets and create powerful, customized tools.”
At the Dell event this week, Jeff Clarke, vice chairman and co-chief operating officer, Dell Technologies, added, “Project Helix gives enterprises purpose-built AI models to more quickly and securely gain value from the immense amounts of data underused today. With highly scalable and efficient infrastructure, enterprises can create a new wave of generative AI solutions that can reinvent their industries.”
Meanwhile, up in Seattle this week at the Microsoft Build 2023 event, Nvidia and Microsoft announced that Nvidia’s AI Enterprise software is being integrated with Microsoft’s Azure Machine Learning platform with a similar intent–to help enterprises accelerate their path from development to production with generative AI and other AI initiatives, Das said. The integration is now available in a limited technical preview
“Microsoft Azure Machine Learning users come to the platform expecting the highest performing, most secure development platform available,” said John Montgomery, corporate vice president of AI platform at Microsoft. “Our integration with NVIDIA AI Enterprise software allows us to meet that expectation, enabling enterprises and developers to easily access everything they need to train and deploy custom, secure large language models.”
With Azure Machine Learning, developers can scale applications from testing to massive deployments, while using the platform’s data encryption, access control and compliance certifications to meet security and compliance with their organizational policies requirements. Nvidia AI Enterprise complements Azure Machine Learning with secure, production-ready AI capabilities and includes access to Nvidia experts and support, Das noted, adding, “The customer can automatically, seamlessly get enterprise grade, accelerated computing for AI applications in the cloud, and so we think this is a pretty important step forward.”