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Generative AI in the Enterprise
Introduction
Executive summary
About this document
Audience
Generative AI background and concepts Business and technical challenges Benefits Use cases Dell and NVIDIA solution architecture Infrastructure component considerations for AI Dell infrastructure and software components NVIDIA infrastructure and software components System Configurations Conclusion References

About this document

About this document

  • In this whitepaper, readers can gain a comprehensive overview of generative AI, including its underlying principles, benefits, architectures, and techniques. They can also learn about the various types of generative AI models, and how they are used in real-world applications.

    This white paper also explores the challenges and limitations of generative AI, such as the difficulty in training large-scale models, the potential for bias and ethical concerns, and the trade-off between generating realistic outputs and maintaining data privacy.

    This white paper also provides guidance about how to develop and deploy generative AI models effectively. It includes considerations about hardware and software infrastructure from Dell Technologies and NVIDIA, data management, and evaluation metrics – all leading to a scalable, high-performance, production architecture for generative AI in the enterprise.