Wednesday, April 9th 2025

NVIDIA Will Bring Agentic AI Reasoning to Enterprises with Google Cloud

NVIDIA is collaborating with Google Cloud to bring agentic AI to enterprises seeking to locally harness the Google Gemini family of AI models using the NVIDIA Blackwell HGX and DGX platforms and NVIDIA Confidential Computing for data safety. With the NVIDIA Blackwell platform on Google Distributed Cloud, on-premises data centers can stay aligned with regulatory requirements and data sovereignty laws by locking down access to sensitive information, such as patient records, financial transactions and classified government information. NVIDIA Confidential Computing also secures sensitive code in the Gemini models from unauthorized access and data leaks.

"By bringing our Gemini models on premises with NVIDIA Blackwell's breakthrough performance and confidential computing capabilities, we're enabling enterprises to unlock the full potential of agentic AI," said Sachin Gupta, vice president and general manager of infrastructure and solutions at Google Cloud. "This collaboration helps ensure customers can innovate securely without compromising on performance or operational ease." Confidential computing with NVIDIA Blackwell provides enterprises with the technical assurance that their user prompts to the Gemini models' application programming interface—as well as the data they used for fine-tuning—remain secure and cannot be viewed or modified. At the same time, model owners can protect against unauthorized access or tampering, providing dual-layer protection that enables enterprises to innovate with Gemini models while maintaining data privacy.
AI Agents Driving New Enterprise Applications
This new offering arrives as agentic AI is transforming enterprise technology, offering more advanced problem-solving capabilities. Unlike AI models that perceive or generate based on learned knowledge, agentic AI systems can reason, adapt and make decisions in dynamic environments. For example, in enterprise IT support, while a knowledge-based AI model can retrieve and present troubleshooting guides, an agentic AI system can diagnose issues, execute fixes and escalate complex problems autonomously.


Similarly, in finance, a traditional AI model could flag potentially fraudulent transactions based on patterns, but an agentic AI system could go even further by investigating anomalies and taking proactive measures such as blocking transactions before they occur or adjusting fraud detection rules in real time.

The On-Premises Dilemma
While many can already use the models with multimodal reasoning—integrating text, images, code and other data types to solve complex problems and build cloud-based agentic AI applications—those with stringent security or data sovereignty requirements have yet been unable to do so. With this announcement, Google Cloud will be one of the first cloud service providers to offer confidential computing capabilities to secure agentic AI workloads across every environment—whether cloud or hybrid.
Powered by the NVIDIA HGX B200 platform with Blackwell GPUs and NVIDIA Confidential Computing, this solution will enable customers to safeguard AI models and data. This lets users achieve breakthrough performance and energy efficiency without compromising data security or model integrity.

AI Observability and Security for Agentic AI
Scaling agentic AI in production requires robust observability and security to ensure reliable performance and compliance. Google Cloud today announced a new GKE Inference Gateway built to optimize the deployment of AI inference workloads with advanced routing and scalability. Integrating with NVIDIA Triton Inference Server and NVIDIA NeMo Guardrails, it offers intelligent load balancing that improves performance and reduces serving costs while enabling centralized model security and governance.

Looking ahead, Google Cloud is working to enhance observability for agentic AI workloads by integrating NVIDIA Dynamo, an open-source library built to serve and scale reasoning AI models across AI factories.
At Google Cloud Next, attend NVIDIA's special address, explore sessions, view demos and talk to NVIDIA experts.
Source: NVIDIA Blog
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2 Comments on NVIDIA Will Bring Agentic AI Reasoning to Enterprises with Google Cloud

#1
Wye
Ladies and gentlemen,

As we gather here today at the forefront of technological innovation, I am excited to discuss the transformative power of Artificial Intelligence within the enterprise landscape. Our focus is on harnessing the immense capabilities of AI models on premises, a strategy that promises to drive unprecedented levels of innovation and operational efficiency.

In the ever-evolving digital ecosystem, enterprises are increasingly recognizing the value of deploying AI models within their own infrastructure. This approach, often referred to as on-premises AI, allows organizations to innovate securely while maintaining complete control over their data. By keeping AI processing in-house, businesses can ensure that sensitive information remains confidential, safeguarding against potential breaches and external threats.

One of the key advantages of on-premises AI is the ability to tailor solutions specifically to the unique needs of the organization. By leveraging bespoke models, enterprises can optimize their operations, streamline processes, and unlock new avenues for growth. This customization is akin to setting a gem in a crown – it elevates the entire enterprise to new heights of performance and competitiveness.

Moreover, on-premises AI empowers enterprises to harness the full potential of their data assets. By having AI capabilities embedded within their infrastructure, businesses can process and analyze vast quantities of data in real-time, gaining actionable insights that drive strategic decision-making. This agility is crucial in today’s fast-paced market, where the ability to pivot quickly can be the difference between success and obsolescence.

The concept of Gemini, representing dual innovation and security, is particularly relevant here. On-premises AI serves as a dual force, enhancing both the innovative capacity and the security posture of enterprises. By deploying AI models on premises, businesses can innovate without compromising on data security, ensuring that their competitive edge is both sharp and shielded.

In conclusion, as you consider the future trajectory of your enterprise, I encourage you to explore the possibilities that on-premises AI offers. It is not merely a tool, but a dynamic force that can redefine how your business operates and competes. By embracing this approach, you position your enterprise to not only adapt to the challenges of tomorrow but to lead with confidence and vision.

Thank you for your attention and for your commitment to advancing the frontier of enterprise technology. Let us continue to innovate securely, with the brilliance of AI shining brightly in our endeavors.

Thank you.
Yeah that took me 3 seconds to generate. Should I be a CEO? /s

I wish companies would pay more for the employees preparing their press releases or their main website page.

In the last decades these pages became unreadable because of their desperate and obviously unqualified attempts to make the company/announcements looks great and cover everything ... and nothing.

I find it ridiculous that customers these days have to visit the wikipedia page for the company to get any idea wtf is that company doing, any official company pages are buried in disgusting and generic corporate speak.
Posted on Reply
#2
KLMR
A lot of smart people is working to get the best of this neural-network/LLM revolution.
The problem is a lot of higher-paid dumb people doesn't know whats buying.
Posted on Reply
Apr 13th, 2025 05:15 EDT change timezone

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