NVIDIA and Google’s long-standing collaboration is founded on a shared commitment to advancing artificial intelligence innovation and empowering the global developer community. This partnership extends beyond infrastructure, delving into all facets of engineering to optimize the entire computing stack.
The most recent outcomes of this collaboration encompass substantial contributions to community software such as JAX, OpenXLA, MaxText, and llm-d. These underlying optimizations directly support Google’s cutting-edge Gemini models and the Gemma family of open-source models.
Furthermore, performance-optimized NVIDIA AI software, including NVIDIA NeMo, NVIDIA TensorRT-LLM, NVIDIA Dynamo, and NVIDIA NIM microservices, are tightly integrated into Google Cloud’s diverse platforms - Vertex AI, Google Kubernetes Engine (GKE), and Cloud Run – to accelerate performance and streamline AI deployment.
NVIDIA Blackwell on Google Cloud
Google Cloud is at the forefront, offering NVIDIA HGX B200 and NVIDIA GB200 NVL72, integrating them into A4 and A4X virtual machines (VMs).
These new VMs, powered by Google Cloud AI Hypercomputer architecture, are accessible through managed services like Vertex AI and GKE, enabling organizations to select the appropriate path for developing and deploying autonomous AI applications on a large scale. Google Cloud A4 VMs, accelerated by NVIDIA HGX B200, are now generally available.
Google Cloud’s A4X VMs can provide over one million teraflops of computing power per rack and can scale to tens of thousands of GPUs seamlessly via Google’s Jupiter networking fabric and NVIDIA ConnectX-7 NICs. Google’s third-generation liquid cooling infrastructure ensures consistent, high-efficiency performance, even with the largest AI workloads.
Deploying Google Gemini and NVIDIA Blackwell On-Premises via Google Distributed Cloud
Gemini’s advanced reasoning capabilities already fuel cloud-based autonomous AI applications. However, customers in sectors such as the public sector, healthcare, and financial services have faced challenges leveraging this technology because of strict data residency, regulatory, or security requirements.
With the NVIDIA Blackwell platform coming to Google Distributed Cloud—Google Cloud’s fully managed solution for on-premises, air-gapped environments, and the edge—organizations can now securely deploy Gemini models within their own data centers, unlocking autonomous AI for these customers.
NVIDIA Blackwell uniquely combines groundbreaking performance with confidential computing capabilities, ensuring user prompts and fine-tuning data are protected. This allows customers to innovate with Gemini while maintaining complete control over their information, meeting the highest privacy and compliance standards. Google Distributed Cloud expands Gemini’s reach, enabling more organizations than ever to harness the power of next-generation autonomous AI.
Optimizing AI Inference Performance for Google Gemini and Gemma
The Gemini family of models is purpose-built for the age of autonomous AI, representing Google’s most advanced and capable AI model to date, excelling in complex reasoning, coding, and multi-modal understanding.
NVIDIA and Google are dedicated to performance optimization, ensuring that Gemini-based inference workloads run efficiently on NVIDIA GPUs, particularly within Google Cloud’s Vertex AI platform. This allows Google to handle a massive volume of Gemini model user queries on Vertex AI and Google Distributed Cloud, using NVIDIA-accelerated infrastructure.
Additionally, the lightweight Gemma family of open models has been optimized for inference using the NVIDIA TensorRT-LLM library and is expected to be available as easy-to-deploy NVIDIA NIM microservices. These optimizations maximize performance and make advanced AI accessible to developers, streamlining the running of workloads across various deployment architectures, from data centers to local NVIDIA RTX-powered PCs and workstations.
Building a Robust Developer Community and Ecosystem
NVIDIA and Google Cloud are also supporting the developer community by optimizing open-source frameworks like JAX, providing seamless scaling and breakthrough performance on Blackwell GPUs so that AI workloads can run efficiently across tens of thousands of nodes.
This collaboration extends beyond technology, with the launch of new developer communities co-created by Google Cloud and NVIDIA, bringing together experts and peers to accelerate skillsets and innovation.
By combining engineering excellence, open-source leadership, and a vibrant developer ecosystem, both companies are making it easier than ever for developers to build, scale, and deploy next-generation AI applications.
Deeper Dive: Strategic Significance of NVIDIA and Google Collaboration
The collaboration between NVIDIA and Google is more than just a technological alliance; it represents a significant shift in the strategic direction of artificial intelligence. Here are some more in-depth observations that explore the significance and future implications of this partnership:
1. Accelerating AI Innovation:
The combination of NVIDIA’s leading position in GPU technology with Google’s expertise in AI software and platforms creates a powerful synergy that can accelerate the pace of AI innovation. By working together, the two companies are pushing the boundaries of what is possible with AI and opening up new avenues for applications across various industries.
2. Empowering Developers:
NVIDIA and Google are committed to building a thriving developer ecosystem. By providing tools, resources, and support, they are making it easier for developers to build, scale, and deploy AI applications. This focus on empowering developers will drive the widespread adoption of AI and spur broader innovation.
3. Unlocking the Potential of On-Premises AI Deployments:
The introduction of the NVIDIA Blackwell platform to on-premises environments through Google Distributed Cloud opens up new possibilities for businesses. Companies that are unable to use cloud-based AI solutions due to data residency, regulatory, or security concerns can now leverage the power of Gemini models within their own data centers.
4. Optimizing AI Inference Performance:
Optimizing the inference performance of Gemini and Gemma models on NVIDIA GPUs is crucial for ensuring that AI applications can run efficiently and cost-effectively. The partnership between NVIDIA and Google enables them to improve inference performance and reduce the cost of AI deployments.
5. Advancing Open-Source AI:
NVIDIA and Google share a commitment to open-source AI development by supporting open-source frameworks like JAX. This commitment to open source fosters collaboration and innovation within the community and ensures that AI technology is more broadly accessible and usable.
6. Shaping the Future of AI:
The collaboration between NVIDIA and Google is shaping the future of AI. By working together, the two companies are defining the direction of AI technology and setting new standards for AI applications across different sectors.
Specific Technical Details of NVIDIA and Google Collaboration
The following will further explore some of the specific technical details behind the NVIDIA and Google collaboration, providing a more in-depth understanding of the partnership’s depth and breadth:
1. NVIDIA Blackwell GPU:
The NVIDIA Blackwell GPU is NVIDIA’s latest GPU architecture, specifically designed to meet the demands of AI and high-performance computing workloads. The Blackwell GPU features breakthrough performance, larger memory capacity, and advanced capabilities like confidential computing.
2. Google Gemini Models:
Gemini models are Google’s most advanced and capable AI models to date. Gemini models possess superior reasoning capabilities, multi-modal understanding, and code generation abilities.
3. NVIDIA TensorRT-LLM:
NVIDIA TensorRT-LLM is a library that optimizes the inference performance of large language models (LLMs) on NVIDIA GPUs. TensorRT-LLM helps developers deploy AI applications with higher performance and efficiency.
4. NVIDIA NIM Microservices:
NVIDIA NIM microservices are a set of containerized software components designed to simplify the deployment and management of AI applications. NIM microservices help developers run AI workloads, including data centers and local NVIDIA RTX-powered PCs and workstations.
5. Google Vertex AI:
Google Vertex AI is a platform providing a comprehensive set of tools and services for building, deploying, and managing machine learning models. Vertex AI simplifies the AI development process and helps businesses realize AI faster.
6. Google Distributed Cloud:
Google Distributed Cloud is a solution that allows businesses to run Google Cloud services on-premises or in edge environments. Distributed Cloud enables businesses to leverage Google Cloud’s innovative technologies while meeting regulatory and data residency requirements.
Potential Impact of Collaboration on Various Industries
The collaboration between NVIDIA and Google has profound implications for various sectors, including healthcare, financial services, manufacturing, and entertainment. Here are some examples of what this partnership can bring to different industries:
1. Healthcare:
- Improved diagnostics: AI can analyze medical images, such as X-rays and MRIs, to detect diseases in the early stages.
- Personalized treatment: AI can tailor treatment plans based on a patient’s genome, lifestyle, and medical history.
- Accelerated drug discovery: AI can identify potential drug targets and predict the efficacy of drugs.
2. Financial Services:
- Fraud detection: AI can identify fraudulent transactions and prevent financial crimes.
- Risk assessment: AI can assess credit risk and make more informed lending decisions.
- Customer service: AI can provide personalized support and advice to customers.
3. Manufacturing:
- Predictive maintenance: AI can predict equipment failures and perform maintenance before failures occur.
- Quality control: AI can detect defects in products and improve manufacturing quality.
- Optimized production: AI can optimize production processes and reduce costs.
4. Entertainment:
- Content creation: AI can generate realistic images, videos, and audio.
- Personalized media: AI can recommend media content based on a user’s interests.
- Gaming: AI can create smarter and more realistic game characters.
In conclusion, the collaboration between NVIDIA and Google is driving AI innovation, empowering developers, and creating new possibilities for various sectors. By combining their strengths, the two companies are shaping the future of AI and ensuring that AI technology is more broadly accessible and usable.