Published on March 19, 2024, 8:13 pm

CIO Dive’s recent reports shed light on the potential for a lucrative venture in the realm of enterprise data. During a statement on Monday, Nvidia CEO Jensen Huang emphasized that SAP holds a wealth of enterprise data that could be converted into personalized generative AI agents. Nvidia’s prowess in AI processing power has positioned them as a desirable partner for cloud providers and enterprise software companies alike.

At the Nvidia GTC technology conference held in San Jose, significant strides were made in strengthening alliances with hyperscalers like Azure and Google Cloud. Both tech giants have committed to implementing Nvidia’s groundbreaking Grace Blackwell AI computing platform, unveiled by Huang at the conference.

The collaboration between SAP and Nvidia involves tapping into numerous enterprise-grade Nvidia AI microservices integrated within the Nvidia CUDA developer platform. These services are fine-tuned for various functions such as data processing, model customization, inference, retrieval-augmented generation, and imposing guardrails.

The introduction of composable microservices marks a pivotal moment as it allows users to optimize models from leading AI companies such as Cohere, Google, Hugging Face, Meta, Stability AI, both on cloud environments or on-premises infrastructure. This flexibility addresses the challenges faced by customers due to the constant influx of new models hitting the market regularly.

Kari Briski, VP of generative AI software product management at Nvidia highlighted how these microservices streamline model optimization processes prior to deployment. An example provided was the collaborative effort with Google in optimizing Gemma models before their release to ensure seamless integration within diverse environments.

Furthermore, extensive testing involving thousands of users has demonstrated substantial time savings equating to 97 minutes per week on average with these features. Additionally, findings from ProsperOps evaluating $1.5 billion in AWS compute expenditure revealed missed opportunities by organizations in leveraging built-in discounts effectively.

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