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Superalignment Fast Grants is a grant from OpenAI, in partnership with Eric Schmidt, that funds technical research on the alignment and safety of superhuman AI systems. The program distributes $10 million total, with individual awards ranging from $100,000 to $2 million for academic labs, nonprofits, and independent researchers.
Graduate students may apply for a one-year $150,000 OpenAI Superalignment Fellowship ($75,000 stipend plus $75,000 in compute). Eligible research directions include weak-to-strong generalization, interpretability, scalable oversight, and adversarial robustness. No prior alignment experience is required.
Applications closed February 18.
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# Superalignment Fast Grants | OpenAI * Foundation(opens in a new window) * Foundation(opens in a new window) Try ChatGPT(opens in a new window)Login * Superalignment Fast Grants * Join us in this challenge # Superalignment Fast Grants Apply by February 18(opens in a new window)Further program details(opens in a new window) We’re launching $10M in grants to support technical research towards the alignment and safety of superhuman AI systems, including weak-to-strong generalization, interpretability, scalable oversight, and more.
We believe superintelligence could arrive within the next 10 years. These AI systems would have vast capabilities—they could be hugely beneficial, but also potentially pose large risks. Today, we align AI systems to ensure they are safe using reinforcement learning from human feedback (RLHF).
However, aligning future superhuman AI systems will pose fundamentally new and qualitatively different technical challenges. Superhuman AI systems will be capable of complex and creative behaviors that humans cannot fully understand. For example, if a superhuman model generates a million lines of extremely complicated code, humans will not be able to reliably evaluate whether the code is safe or dangerous to execute.
Existing alignment techniques like RLHF that rely on human supervision may no longer be sufficient. **This leads to the fundamental challenge: how can humans steer and trust AI systems much smarter than them? ** This is one of the most important unsolved technical problems in the world.
But we think it is solvable with a concerted effort. There are many promising approaches and exciting directions, with lots of low-hanging fruit. We think there is an enormous opportunity for the ML research community and individual researchers to make major progress on this problem today.
As part of our Superalignment project, we want to rally the best researchers and engineers in the world to meet this challenge—and we’re especially excited to bring new people into the field.
## Superalignment Fast Grants In partnership with Eric Schmidt, we are launching a $10M grants program to support technical research towards ensuring superhuman AI systems are aligned and safe: * We are offering $100K–$2M grants for academic labs, nonprofits, and individual researchers.
* For graduate students, we are sponsoring a one-year **$150K OpenAI Superalignment Fellowship:** $75K in stipend and $75K in compute and research funding. * No prior experience working on alignment is required; we are actively looking to support researchers who are excited to work on alignment for the first time. * Our application process is simple, and we’ll get back to you within four weeks of applications closing.
* Apply by February 18(opens in a new window) With these grants, we are particularly interested in funding the following research directions(opens in a new window): * **Weak-to-strong generalization**: Humans will be weak supervisors relative to superhuman models. Can we understand and control how strong models generalize from weak supervision? * **Interpretability**: How can we understand model internals?
And can we use this to e.g. build an AI lie detector? * **Scalable oversight**: How can we use AI systems to assist humans in evaluating the outputs of other AI systems on complex tasks? * Many other research directions, including but not limited to: **honesty**, **chain-of-thought faithfulness**, **adversarial robustness**, **evals and testbeds**, and more.
For more on the research directions, FAQs, and other details, see our Superalignment Fast Grants page(opens in a new window). ## Join us in this challenge **We think new researchers could make enormous contributions! ** This is a young field with many tractable research problems; outstanding contributions could not just help shape the field, but be critical for the future of AI.
There has never been a better time to start working on alignment.
Leopold Aschenbrenner, Jan Leike, Sherry Lachman, Aleksander Madry, Chris Clark, Collin Burns, Pavel Izmailov, Nat McAleese, William Saunders, Bobby Wu, Lisa Pan, Janine Korovesis, Ilya Sutskever, Elie Georges, Kayla Wood, Kendra Rimbach, Thomas Degry, Ruby Chen Disrupting malicious uses of AI by state-affiliated threat actors Security Feb 14, 2024 Building an early warning system for LLM-aided biological threat creation Publication Jan 31, 2024 Democratic inputs to AI grant program: lessons learned and implementation plans Safety Jan 16, 2024 * Explore ChatGPT(opens in a new window) * Pricing(opens in a new window) * Download(opens in a new window) * Documentation(opens in a new window) * Developer Forum(opens in a new window) * Foundation(opens in a new window) * Help Center(opens in a new window) (opens in a new window)(opens in a new window)(opens in a new window)(opens in a new window)(opens in a new window)(opens in a new window)(opens in a new window)
Based on current listing details, eligibility includes: Academic labs, nonprofits, and individual researchers are eligible for grants. For graduate students, there is a one-year $150K OpenAI Superalignment Fellowship. No prior experience working on alignment is required. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates $100K–$2M (grants), $150K (fellowship) Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
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Academic Grant Program (NVIDIA) is sponsored by NVIDIA. NVIDIA's Academic Grant Program seeks proposals from full-time faculty members at accredited academic institutions who are using NVIDIA technology to advance work in Simulation and Modeling, Data Science, and Robotics and Edge AI. Proposals should incorporate pretrained models from ai.nvidia.com and/or make extensive use of NVIDIA software distributions.
This NOFO provides an opportunity to all FY 2018 NIST SBIR Phase I awardees to submit a Phase II application following completion of Phase I. This NOFO provides instructions for FY 2019 NIST SBIR Phase II application preparation and submission requirements. In Phase II, work from Phase I that exhibits potential for commercial application is further developed. Phase II is the R&D or prototype development phase. To apply for a Phase II award, each Phase I awardee will be required to submit a comprehensive application outlining the proposed research and a detailed plan to commercialize the final product. Each NIST Phase II award is for up to $400,000 and up to a 24-month period of performance. One year after completing the Phase II R&D activity, the awardee shall be required to report on its commercialization activities. Up to an additional $6,500 may be requested for Technical and Business Assistance (TABA); see Section 5.11 for more information about TABA. Funding Opportunity Number: 2019-NIST-SBIR-02. Assistance Listing: 11.620. Funding Instrument: CA. Category: ST. Award Amount: Up to $400K per award.
Local Government Cybersecurity Grant Program (Florida) is sponsored by Florida Digital Service. This Florida state grant program enhances cybersecurity resilience in local governments, with a priority focus on fiscally constrained rural areas. Rather than issuing direct funding, the Florida Digital Service will procure cybersecurity solutions directly on behalf of awarded applicants. The grant supports new or expanded capabilities in preventing, detecting, responding to, and recovering from cyber threats.