Microsoft has integrated Nvidia’s AI Enterprise Software Suite with Azure Machine Learning service

Microsoft recently announced its integration of NVIDIA’s AI Enterprise software suite with Azure Machine Learning service. The integration is designed to help enterprise developers build, deploy, and manage applications that are based on large language models. This move aims at improving the machine learning capabilities of Azure, a cloud-based data analytics platform.

This partnership between Microsoft and Nvidia is expected to lead to significant advancements in the field of artificial intelligence. The integration brings together Microsoft’s Azure Machine Learning service and Nvidia’s AI Enterprise software suite, providing developers with access to over 100 frameworks, pre-trained large language models, and development tools.

Available tools under the AI Enterprise Suite integration

NVIDIA’s AI Enterprise software suite is a set of advanced tools for accelerating the development, deployment, and management of machine learning models. As part of the integration with Azure Machine Learning service, developers and enterprises will have access to several tools, including:

1. Nvidia RAPIDS – for accelerating data science workloads
2. Nvidia Metropolis – for accelerating Vision AI model development
3. Nvidia Triton Inference Server – for standardizing model deployment
4. NeMo Guardrails software – enables developers to add safety and security features for AI chatbots.

Benefits of using Nvidia’s AI Enterprise Suite

The integration of Microsoft’s Azure Machine Learning service with Nvidia’s AI Enterprise software suite is expected to provide several benefits. The use of Nvidia’s AI Enterprise Suite helps accelerate the data science pipeline and streamline the development and deployment of production AI. This includes applications such as generative AI, computer vision, and speech AI.

The AI Enterprise Suite is specifically designed to make it easier for enterprises to implement machine learning and AI solutions. The suite comes with several pre-built modules, enabling developers to quickly build and deploy machine learning models. Additionally, it provides support for a wide range of programming languages, making it easy for developers to work with the software suite.

Availability of the integration

Currently, the integration is only available through an invitation-only preview in the Nvidia community registry. However, it is expected that the integration will be made generally available in the near future.

Nvidia experts and support services

Users of the AI Enterprise software suite on Azure Machine Learning service will have access to Nvidia experts and support services. This ensures that developers have access to the necessary support they need to build and deploy machine learning models in an efficient and effective manner.

NVIDIA’s AI Enterprise software suite is available on Azure Marketplace

As part of the collaboration between Microsoft and Nvidia, Microsoft will make Nvidia’s AI Enterprise software suite available on its Azure Marketplace. This move will enable enterprises to access the suite of tools through the Azure Marketplace.

Other areas of collaboration

The collaboration between Microsoft and Nvidia extends beyond the integration of the AI Enterprise software suite with Azure Machine Learning service. Nvidia’s Omniverse Cloud platform-as-a-service (PaaS) is now available on Microsoft Azure as a private offer for enterprises. This will enable enterprises to access the platform, develop, and deploy machine learning models more efficiently and cost-effectively.

In March, Nvidia announced that it would make its DGX Pods, which power ChatGPT, available in the cloud. This move is expected to further improve the development and deployment of generative AI models, enabling enterprises to build more powerful machine learning models.

The integration of Microsoft’s Azure Machine Learning service with Nvidia’s AI Enterprise software suite is a significant step forward in the field of artificial intelligence. The partnership is expected to bring several advancements in the realm of machine learning and AI. The integration offers developers and enterprises access to advanced tools that let them build, deploy, and manage machine learning models quickly and efficiently. The collaboration between Microsoft and Nvidia is anticipated to result in many more exciting developments in the field of machine learning in the coming months.

Explore more

Jenacie AI Debuts Automated Trading With 80% Returns

We’re joined by Nikolai Braiden, a distinguished FinTech expert and an early advocate for blockchain technology. With a deep understanding of how technology is reshaping digital finance, he provides invaluable insight into the innovations driving the industry forward. Today, our conversation will explore the profound shift from manual labor to full automation in financial trading. We’ll delve into the mechanics

Chronic Care Management Retains Your Best Talent

With decades of experience helping organizations navigate change through technology, HRTech expert Ling-yi Tsai offers a crucial perspective on one of today’s most pressing workplace challenges: the hidden costs of chronic illness. As companies grapple with retention and productivity, Tsai’s insights reveal how integrated health benefits are no longer a perk, but a strategic imperative. In our conversation, we explore

DianaHR Launches Autonomous AI for Employee Onboarding

With decades of experience helping organizations navigate change through technology, HRTech expert Ling-Yi Tsai is at the forefront of the AI revolution in human resources. Today, she joins us to discuss a groundbreaking development from DianaHR: a production-grade AI agent that automates the entire employee onboarding process. We’ll explore how this agent “thinks,” the synergy between AI and human specialists,

Is Your Agency Ready for AI and Global SEO?

Today we’re speaking with Aisha Amaira, a leading MarTech expert who specializes in the intricate dance between technology, marketing, and global strategy. With a deep background in CRM technology and customer data platforms, she has a unique vantage point on how innovation shapes customer insights. We’ll be exploring a significant recent acquisition in the SEO world, dissecting what it means

Trend Analysis: BNPL for Essential Spending

The persistent mismatch between rigid bill due dates and the often-variable cadence of personal income has long been a source of financial stress for households, creating a gap that innovative financial tools are now rushing to fill. Among the most prominent of these is Buy Now, Pay Later (BNPL), a payment model once synonymous with discretionary purchases like electronics and