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NSF awards $20 million to build AI models that predict scientific discoveries and technological advancements is sponsored by National Science Foundation (NSF). This grant supports the creation of large language models (LLMs) intended to help predict and strategically direct funding to scientific discoveries and technological advancements. The research aims to build 'chronological' models to identify disruptive advances.
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NSF awards $20 million to build AI models that predict scientific discoveries and technological advancements | University of Chicago News NSF awards $20 million to build AI models that predict scientific discoveries and technological advancements UChicago-led research team to create an AI-driven “global observatory and virtual laboratory” Prof. James Evans is building a treasure map.
Buried underneath layers of data, he believes, are golden discoveries that could help us solve some of the world’s biggest problems—from climate change to cancer research.
The National Science Foundation has awarded the research team, led by Evans, a $20 million grant to create first-of-their-kind large language models (LLMs) intended to help predict—and strategically direct funding to—scientific discoveries and technological advancements. In partnership with the Allen Institute for AI , the team also includes University of Chicago researchers Prof. Ufuk Akcigit, Prof. Ian Foster and Ben Blaiszik.
“We're trying to help the government and researchers anticipate what are new and important things in science and technology,” said Evans, the Max Palevsky Professor in the Department of Sociology and Data Science at UChicago and director of the Knowledge Lab . “And how they can allocate their resources to focus on the most impactful and probable things.
” LLMs, like Chat GPT-4, are multilayered neural networks—meaning they are designed to “think like humans. ” To produce helpful, “humanlike” responses, these models analyze everything on the internet to predict what information should come next. However, according to Evans, these models don’t have a great sense of time.
“Current models like ChatGPT use the web, mixed together, as data. As such, they don’t have a sense of what occurred in 2023 that was surprising with respect to 2022,” Evans said. “They don't know what things were surprising or radical.
” By mapping funded research proposals, scientific papers, and their resulting patents and products, the team plans to build models that are “chronological. ” These time-aware models will hopefully allow researchers to predict or recognize disruptive advances the moment they occur. These models will also identify how such discoveries and inventions change the landscape to reveal new, follow-on opportunities.
Policymakers could then use this data to guide funding and talent toward these potential discoveries. Funding—like time and attention—is limited. In the U.S., the majority of science funding is distributed by the government, who, according to Evans, tends to fund research that is widely expected to yield high-value results.
Nevertheless, Evans likens this risk-averse strategy to bunting down the first base line. “We can’t just afford to get on base,” he said. “Major advances and opportunities—we're only going to get to some of those things within our lifetime by swinging for fast balls, for improbable opportunities.
” By guiding policymakers and the public to research areas with high potential (which might have been overlooked by human researchers and referees), the team hopes to diversify our science portfolio—encouraging funders to invest in a healthy mix of risky and non-risky research, and across a wide variety of risks.
Building upon these same models, the research team will also construct a “virtual laboratory” to simulate potential outcomes in the worlds of science and technology. For example, what happens if we fund a certain area of research? Or enact a particular policy?
Or partner with a particular country? The project will be built and tested over the course of five years, in stages, though the team expects to see insights relatively soon. “Science and technology are the engine which drives human flourishing,” Evans said.
“And we need to flex our complete scientific and technological imagination to manage and lead it. ” To learn more about the project and related opportunities, visit the Knowledge Lab website. Get more with UChicago News delivered to your inbox.
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According to the current listing, eligibility includes: Research teams, including university researchers, in partnership with other institutions like the Allen Institute for AI. Confirm the full requirements in the official notice before applying.
The current listing shows $20,000,000 (awarded to the University of Chicago and partners as an example). Verify award ceilings, matching requirements, and allowable costs in the official notice.
NSF awards $20 million to build AI models that predict scientific discoveries and technological advancements is funded by National Science Foundation (NSF). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Svane Family Foundation Culture Forward Grants is a $5 million grant initiative from the Svane Family Foundation that supports arts and culture projects attracting families, students, and young professionals to Downtown San Francisco. The program is open to individual artists, artist collectives, and arts and culture organizations. Applications opened January 7, 2025, and remain open on a rolling basis through 2027, with projects reviewed and awarded quarterly. The next application deadline is 11:59 PM on March 1, 2026. Applicants may submit one application per quarterly grant cycle and are eligible to reapply in subsequent cycles. Interested applicants should review the grant guidelines and watch the application tutorial before submitting through the Svane Family Foundation Submission Manager.
PCORI Cycle 2 2026 Methods Funding Announcement specifically prioritizes Methods to Improve the Use of Artificial Intelligence (AI) and Machine Learning (ML) in Patient-Centered Comparative Effectiveness Research (CER). The program funds studies addressing high-impact methodological gaps, with AI/ML topics including applications of AI/ML to augment or transform research methodologies or processes and approaches using AI/ML to enhance health communication. Additional priority areas include Methods to Support Use of Real-World Data in Multi-Site Patient-Centered CER and Methods to Improve Study Design. Awards provide up to $750,000 in direct costs for up to 3 years from a total program budget of $12 million. Applicants must address PCORI Foundational Expectations for Partnerships in Research, ensuring patients and stakeholders meaningfully contribute lived experience. Letter of Intent deadline is April 28, 2026, with full applications due September 1, 2026.
The Culture Forward Grants program is a $5 million initiative by the Svane Family Foundation supporting arts and culture projects that attract families, students, and young professionals to Downtown San Francisco. Awards of up to $100,000 are available to individual artists, collectives, and arts and culture organizations on a rolling quarterly basis through 2027. Applicants must be 501(c)(3) public charities or partner with a qualifying fiscal sponsor. Applications are reviewed and awarded quarterly, and applicants may reapply each cycle. The program is designed to give culture makers the freedom to think boldly and innovate without prescribed expectations.
TCUP lists eight funding tracks and roughly $10.3M a year, but the October 14, 2026 deadline applies to only three of them — CHAI, Pre-TI, and TCUP Partnerships — and each carries a restriction that disqualifies most applicants. Here is the track-by-track math.
Read articleNSF 26-513 makes roughly $100 million available for up to 10 State and Regional AI Infrastructure Hubs at $4M to $12M each over five years. One award per state or multi-state region. One proposal per organization. And NSF is not buying you GPUs — it funds the coordination, the workforce and the faculty training, while the compute has to come from partners you have to already have.
Read articleAs of September 12, NSF had obligated $6.3 billion across 6,200 grants versus $8.1 billion and 8,600 last year. AHRQ has made 61 awards. Judge Allison Burroughs ordered the government to report by September 28 on whether IES will obligate $180 million before it expires. Here is what actually happens to the money on October 1 — and what it means for your FY2027 application.
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