Allen Institute for AI Secures $152M from NSF and Nvidia to Lead National Open AI Project for Scientific Research

Allen Institute for AI lands $152M from Nvidia and NSF to lead national AI project

Is this the Allen Institute for AI's breakout moment? The U.S. National Science Foundation and chip powerhouse Nvidia will provide a total of $152 million in funding and infrastructure to the Seattle-based non-profit research institute to lead a new national project to build open AI models for scientific research. The five-year initiative positions Ai2, as it's known, as a key player in building the technological backbone of U.S. artificial intelligence, while expanding its sources of support beyond its historic reliance on grants and philanthropy from the estate of late Microsoft co-founder Paul Allen. It marks NSF's first major investment in AI software infrastructure for science. The initiative "will supercharge the work we do at Ai2 and increase America's ability to deliver breakthrough AI developments," Ai2 CEO Ali Farhadi said in a statement. The project, Open Multimodal AI Infrastructure to Accelerate Science (OMAI), will develop a family of large, fully open, multimodal AI models trained on scientific literature and data. The goal is to accelerate breakthroughs in fields such as materials science, biology, and energy. AI is becoming "not just a tool for research, but a catalyst for rethinking how discovery happens across every discipline," said the OMAI project leader, Noah Smith, Ai2 senior director of natural language processing research and a computer science professor at the University of Washington's Allen School of Computer Science & Engineering. Consisting of $75 million from the NSF and $77 million from Nvidia, the initiative is part of the White House AI Action Plan to strengthen U.S. leadership in AI-driven research. "The question isn't if AI will transform science -- it's who will lead that transformation, and this investment helps ensure that the answer is America," said Tess deBlanc-Knowles, special assistant for artificial intelligence at NSF, in a briefing with reporters this week. The project gives Ai2 a rare level of access to key AI hardware: Nvidia will supply its HDX B3-100 systems, built on the company's new Blackwell Ultra architecture, along with AI Enterprise software to accelerate training and inference for the new models. Nvidia CEO Jensen Huang said in a statement about the project that the goal is "to generate limitless intelligence, making it America's most powerful and renewable resource." The hardware is designed to handle massive datasets with high efficiency, speeding up the pace of scientific discovery, said Jack Wells, Nvidia's director of higher education and research, during the briefing with reporters. Founded in 2014 by Paul Allen, Ai2 has operated largely behind the scenes of the AI boom in recent years, focusing on research and open-source tools while for-profit giants such as OpenAI, Anthropic, Google DeepMind, and Meta have dominated headlines. Ai2's work -- from natural language models to scientific search engines -- has earned respect in research circles, but the new federal and corporate backing stands to elevate its profile. In leading the OMAI project, Ai2 will build on its experience creating OLMo and Molmo, two families of high-performance open AI models, along with open datasets such as Dolma. Unlike many leading AI systems that are fully proprietary or only partially open, Ai2's models are released with the full weights, training data, code, and evaluation tools needed for researchers to inspect, adapt, and retrain them. The idea is to give scientists the transparency they need to recreate results, and trust the technology used in high-stakes research. Also involved will be research teams from the University of Washington (led by Hanna Hajishirzi, also with Ai2), the University of Hawai'i at Hilo (Travis Mandel), the University of New Hampshire (Samuel Carton), and the University of New Mexico (Sarah Dreier). Ai2 said the funding will primarily be used for computing power to train larger, more advanced models on the open foundations established with OLMo and Molmo. The OMAI models will be designed for scientific workflows, helping researchers process and visualize data, generate code for analysis, and identify patterns they might otherwise miss. The systems could also surface relevant findings from outside a researcher's specialty, linking new insights to past discoveries to speed breakthroughs, according to Ai2. The project will roll out in stages, with datasets, code, and other resources released along the way. Ai2 expects the first major model to be available about 18 months into the five-year effort.

NVIDIA, National Science Foundation Support Ai2 Development of Open AI Models to Drive U.S. Scientific Leadership

Aligned with the White House AI Action Plan, public-private partnership includes $152 million in support of open AI model development in America. NVIDIA is partnering with the U.S. National Science Foundation (NSF) to create an AI system that supports the development of multimodal language models for advancing scientific research in the United States. The partnership supports the NSF Mid-Scale Research Infrastructure project, called Open Multimodal AI Infrastructure to Accelerate Science (OMAI). "Bringing AI into scientific research has been a game changer," said Brian Stone, performing the duties of the NSF director. "NSF is proud to partner with NVIDIA to equip America's scientists with the tools to accelerate breakthroughs. These investments are not just about enabling innovation; they are about securing U.S. global leadership in science and technology and tackling challenges once thought impossible." OMAI, part of the work of the Allen Institute for AI, or Ai2, aims to build a national fully open AI ecosystem to drive scientific discovery through AI, while also advancing the science of AI itself. NVIDIA's support of OMAI includes providing NVIDIA HGX B300 systems -- state-of-the-art AI infrastructure built to accelerate model training and inference with exceptional efficiency -- along with the NVIDIA AI Enterprise software platform, empowering OMAI to transform massive datasets into actionable intelligence and breakthrough innovations. NVIDIA HGX B300 systems are built with NVIDIA Blackwell Ultra GPUs and feature industry-leading high-bandwidth memory and interconnect technologies to deliver groundbreaking acceleration, scalability and efficiency to run the world's largest models and most demanding workloads. "AI is the engine of modern science -- and large, open models for America's researchers will ignite the next industrial revolution," said Jensen Huang, founder and CEO of NVIDIA. "In collaboration with NSF and Ai2, we're accelerating innovation with state-of-the-art infrastructure that empowers U.S. scientists to generate limitless intelligence, making it America's most powerful and renewable resource." The contributions will support research teams from the University of Washington, the University of Hawaii at Hilo, the University of New Hampshire and the University of New Mexico. The public-private partnership investment in U.S. technology aligns with recent initiatives outlined by the White House AI Action Plan, which supports America's global AI leadership. "The models are part of the national research infrastructure -- but we can't build the models without compute, and that's why NVIDIA is so important to this project," said Noah Smith, senior director of natural language processing research at Ai2. Driving some of the fastest-growing applications in history, today's large language models (LLMs) have many billions of parameters, or internal weights and biases learned in training. LLMs are trained on trillions of words, and multimodal LLMs can ingest images, graphs, tables and more. But the power of these so-called frontier models can sometimes be out of reach for scientific research when the parameters, training data, code and documentation are not openly available. "With the model training data in hand, you have the opportunity to trace back to particular training instances similar to a response, and also more systematically study how emerging behaviors relate to the training data," said Smith. NVIDIA's partnership with NSF to support Ai2's OMAI initiative provides fully open model access to data, open-source data interrogation tools to help refine datasets, as well as documentation and training for early-career researchers -- advancing U.S. global leadership in science and engineering. The Ai2 project -- supported by NVIDIA technologies -- pledges to make the software and models available at low or zero cost to researchers, similar to open-source code repositories and science-oriented digital libraries. It's in line with Ai2's previous work in creating fully open language models and multimodal models, maximizing access. "Winning the AI Race: America's AI Action Plan" was announced in July by the White House, supported with executive orders to accelerate federal permitting of data center infrastructure and promote exportation of the American AI technology stack. The OMAI initiative aligns with White House AI Action Plan priorities, emphasizing the acceleration of AI-enabled science and supporting the creation of leading open models to enhance America's global AI leadership in academic research and education.

NVIDIA, NSF invest $150M in open AI to turbocharge US science

The partnership supports the Open Multimodal AI Infrastructure to Accelerate Science (OMAI) project, led by the Allen Institute for AI (Ai2). NSF will contribute $75 million, with NVIDIA providing $77 million in advanced technology and resources, including NVIDIA HGX B300 systems built with Blackwell Ultra GPUs and the NVIDIA AI Enterprise software platform. These state-of-the-art systems are designed to accelerate model training and inference for the largest and most demanding workloads. "Bringing AI into scientific research has been a game changer," said Brian Stone, performing the duties of the NSF director. "NSF is proud to partner with NVIDIA to equip America's scientists with the tools to accelerate breakthroughs. These investments are not just about enabling innovation; they are about securing U.S. global leadership in science and technology and tackling challenges once thought impossible." OMAI will create a fully open suite of multimodal large language models trained on scientific data and literature.

NSF and Nvidia partner develop fully open AI models to lead US science innovation - SiliconANGLE

NSF and Nvidia partner develop fully open AI models to lead US science innovation The U.S. National Science Foundation today announced a new partnership with Nvidia Corp. to develop artificial intelligence models designed to advance scientific research across the country. The collaboration will support the NSF Mid-Scale Research project known as Open Multimodal Infrastructure to Accelerate Science, or OMAI. The project will be led by the Allen Institute for AI, or Ai2, which will build a national, fully open AI ecosystem to accelerate both scientific discovery and the science of AI itself. Ai2, well-known for its work on multimodal AI large language models, will bring its expertise to develop domain-specific LLMs trained on scientific literature. These models are intended to enable researchers to process and analyze research faster, generate code and visualizations and connect emerging insights with past discoveries. As part of this public-private investment, NSF is contributing $75 million, and Nvidia is investing $77 million, all directed to Ai2 to lead this effort. The initiative aligns with priorities outlined in the White House AI Action Plan to deliver on AI-enabled science innovation and ensure the U.S. remains a global leader in open AI model development. "This is a lasting national asset," said Noah A. Smith, senior director of natural language processing research at Ai2 and professor at the University of Washington. "The AI infrastructure and the know-how that we're building will advance both science and the science of AI, securing America's leadership in innovation for decades to come," The OMAI models will be fully open, meaning their training data, code and evaluation methods will be transparent and reproducible -- setting a new standard for openness in AI for science. Ai2 says it plans to continuously stream in new scientific literature to keep the models current, ensuring that they reflect the latest discoveries across fields. Customization will also be central. Though general-purpose models work well for conversational use, scientific applications often require more domain-specific alignment. "We at Ai2 are not believers in general-purpose, one-size-fits-all when it comes to AI," said Smith. "We believe that customization is going to play a key role, especially in high-stakes areas like science." Nvidia will provide its cutting-edge HGX B300 systems, high-performance AI infrastructure designed to accelerate model training and deployment at scale, along with Nvidia AI Enterprise, the company's cloud-native software tools, libraries and frameworks for AI development and deployment. This support is aimed at transforming massive datasets into actionable scientific intelligence faster than ever. The NSF said the investment represents a first-of-its-kind leap in AI infrastructure for the foundation's scientific mission. "This marks the first time that NSF is making a major investment in the software infrastructure needed to power AI-driven science," said Tess DeBlanc-Knowles, special assistant for artificial intelligence at NSF. "We see this investment as arriving at a critical moment. Because the question isn't if AI will transform science, it's who will lead that transformation." Ai2 will work with a scientific advisory committee to determine which research communities to prioritize in the early phases. Initial focus areas include accelerating the discovery of new materials, improving protein function prediction, and addressing known weaknesses in existing LLMs. Though the full project timeline includes a major release around 18 months in, Ai2 plans to share key artifacts like datasets and evaluations throughout the development process to maintain transparency and community engagement.