Dell Technologies Expands Generative AI Portfolio
Dell Technologies expands its Dell Generative AI Solutions portfolio, helping businesses transform how they work along every step of their generative AI (GenAI) journeys. "To maximize AI efforts and support workloads across public clouds, on-premises environments and at the edge, companies need a robust data foundation with the right infrastructure, software and services," said Jeff Boudreau, chief AI officer, Dell Technologies. "That's what we are building with our expanded validated designs, professional services, modern data lakehouse and the world's broadest GenAI solutions portfolio."
Customizing GenAI models to maximize proprietary data
The Dell Validated Design for Generative AI with NVIDIA for Model Customization offers pre-trained models that extract intelligence from data without building models from scratch. This solution provides best practices for customizing and fine-tuning GenAI models based on desired outcomes while helping keep information secure and on-premises. With a scalable blueprint for customization, organizations now have multiple ways to tailor GenAI models to accomplish specific tasks with their proprietary data. Its modular and flexible design supports a wide range of computational requirements and use cases, spanning training diffusion, transfer learning and prompt tuning.
Customizing GenAI models to maximize proprietary data
The Dell Validated Design for Generative AI with NVIDIA for Model Customization offers pre-trained models that extract intelligence from data without building models from scratch. This solution provides best practices for customizing and fine-tuning GenAI models based on desired outcomes while helping keep information secure and on-premises. With a scalable blueprint for customization, organizations now have multiple ways to tailor GenAI models to accomplish specific tasks with their proprietary data. Its modular and flexible design supports a wide range of computational requirements and use cases, spanning training diffusion, transfer learning and prompt tuning.