SAN JOSE, CA (GTC), Mar 24, 2025 – NVIDIA, Alphabet, and Google have strengthened their collaboration by announcing new efforts to expand and accelerate the use of AI. The initiatives aim to make AI tools accessible, drive advancements in robotics, and revolutionize industries such as healthcare, manufacturing, and energy.
Teams across Alphabet, including Google DeepMind, Isomorphic Labs, and Intrinsic, are working with NVIDIA’s engineers to push the boundaries of AI and simulation. They tackle challenges like improving robotic grasping, speeding up drug discovery, and optimizing energy systems. Using platforms like NVIDIA Omniverse, Cosmos, and Isaac, the teams shared updates on their progress during the NVIDIA GTC global AI conference.
To support researchers and businesses leveraging AI, Google Cloud will adopt NVIDIA’s latest innovations, including the GB300 NVL72 rack-scale solution and the RTX PRO 6000 Blackwell Server Edition GPU – both unveiled at GTC. Additionally, NVIDIA is partnering with Google DeepMind to integrate SynthID, a watermarking tool that embeds identifiers into AI-generated content, ensuring trust and transparency.
“I’m proud of our ongoing and deep partnership with NVIDIA, which spans the early days of Android and our cutting-edge AI collaborations across Alphabet,” said Sundar Pichai, CEO of Google and Alphabet. “I’m really excited about the next phase of our partnership as we work together on agentic AI, robotics and bringing the benefits of AI to more people around the world.”
“Alphabet and NVIDIA have a longstanding partnership that extends from building AI infrastructure and software to advancing the use of AI in the largest industries,” said Jensen Huang, founder and CEO of NVIDIA. “It’s a great joy to see Google and NVIDIA researchers and engineers collaborate to solve incredible challenges, from drug discovery to robotics.”
Developing Responsible AI and Open Models
Google DeepMind and NVIDIA are working to build trust in generative AI through content transparency.
NVIDIA will use Google DeepMind’s SynthID to embed digital watermarks into AI-generated images, audio, text, and video. This supports content attribution and output tracking for NVIDIA Cosmos foundation models while maintaining video quality.
Google DeepMind and NVIDIA partnered to optimize Gemma, a set of lightweight open models from Google, for use on NVIDIA GPUs. Gemma 3 includes updated capabilities.
NVIDIA has supported efforts to make Gemma accessible for developers. Supercharged by the NVIDIA AI platform, Gemma is available as an optimized NVIDIA NIM microservice using the open-source TensorRT-LLM library to improve inference performance.
In addition, the collaboration will extend to optimizing Gemini-based workloads on NVIDIA accelerated computing via Vertex AI.
The Age of Intelligent Robots
Intrinsic is an Alphabet company focused on making adaptive AI for robotics usable and valuable for manufacturers across industries. Currently, the majority of the world’s installed industrial robots are manually programmed, with every movement hard-coded in a complex, expensive process.
The collaboration with NVIDIA has enabled the development of efficient and user-friendly tools in Intrinsic Flowstate. The tools support NVIDIA Isaac Manipulator foundation models, facilitating universal robot grasping capabilities. Using the foundation models can cut development time and improve flexibility, allowing AI to adjust seamlessly to different tasks. At GTC, Intrinsic will demonstrate an initial OpenUSD framework that streams data between Intrinsic Flowstate and NVIDIA Omniverse. The connection allows for real-time visualization of robotic workcells across various platforms.
Concurrently, NVIDIA and Google DeepMind are announcing a collaboration with Disney Research to develop Newton, an open-source physics engine accelerated by the NVIDIA Warp framework compatible with MuJoCo. Powered by Newton, MuJoCo will accelerate robotics machine learning workloads by more than 70x compared with MuJoCo’s existing GPU-accelerated simulator, MJX.
Applying Innovation to Real-World Challenges
Isomorphic Labs, created by Google DeepMind CEO Demis Hassabis, uses AI to improve drug discovery. The company has developed a drug design platform on Google Cloud, powered by NVIDIA GPUs. This setup provides the capacity and speed needed to advance AI models for health research.
Tapestry, X’s initiative for the electric grid, develops AI-based tools to support a cleaner and reliable energy system. Tapestry and NVIDIA are working together to improve the speed and accuracy of electric grid simulations.
The collaboration will address challenges in integrating new energy sources and expanding grid capacity to support growing data center and AI needs. The companies will explore solutions, including using AI to improve the interconnection process, to support energy infrastructure planning and updates for a sustainable future.
The Next Generation of AI-Optimized Infrastructure
Google Cloud is introducing the latest NVIDIA Blackwell GPUs, including the NVIDIA GB300 NVL72 and NVIDIA RTX PRO 6000 Blackwell Server Edition, as part of its AI infrastructure offerings.
Powered by the Blackwell architecture, Blackwell Ultra features the NVIDIA GB300 NVL72 rack-scale solution and the NVIDIA HGX B300 NVL16 system. The GB300 NVL72 offers 1.5x more AI performance than the previous GB200 NVL72 model. It also expands Blackwell’s AI factory revenue potential by 50x compared to systems using NVIDIA Hopper. The NVIDIA RTX PRO 6000 Blackwell serves as a universal GPU, designed to handle both AI and visual computing tasks across industries like healthcare, manufacturing, retail, live broadcast, and more.
With last month’s preview launches of its A4 and A4X virtual machines, Google Cloud became the first cloud provider to offer both NVIDIA B200- and GB200-based instances. A4 is available – with A4X coming soon – so customers can take advantage of Blackwell’s powerful performance with the added benefits of Google Cloud’s AI Hypercomputer.
Google Cloud and NVIDIA have worked together to optimize popular open-source frameworks like JAX, a popular Python library for machine learning, and MaxText to run on NVIDIA GPUs at scale. MaxText, an advanced framework for scaling large models across massive GPU clusters, uses optimizations codeveloped with NVIDIA to enable training on tens of thousands of GPUs.
Source: NVIDIA
About NVIDIA
NVIDIA Corp. is an American tech company headquartered in Santa Clara, CA. Renowned for designing and manufacturing graphics processing units (GPUs), NVIDIA’s innovations have significantly impacted various sectors. The company’s products and services cater to industries such as gaming, where its GPUs enhance visual experiences; artificial intelligence (AI), providing high-performance computing solutions; automotive, contributing to autonomous vehicle technologies; and robotics, offering advanced AI perception and simulation tools. Over its more than three decades in business, NVIDIA has experienced substantial growth. In the fiscal quarter ending January 2025, the company reported record revenue of $39.3 billion and a net income of $22.1 billion. NVIDIA’s headquarters, designed to facilitate a flat organizational structure, emphasizes information flow and harmony between leadership and employees.