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Superalignment Fast Grants
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This announcement reflects OpenAI's institutional effort to mobilize the broader research community on long-term alignment challenges, part of their Superalignment initiative launched in mid-2023.
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Summary
OpenAI launched a $10M grants program in December 2023 to fund technical research on aligning superhuman AI systems, covering areas like weak-to-strong generalization, interpretability, and scalable oversight. The program offers $100K–$2M grants for academic labs, nonprofits, and individual researchers, plus a $150K fellowship for graduate students, explicitly welcoming researchers new to alignment.
Key Points
- •OpenAI allocated $10M (in partnership with Eric Schmidt) for grants ranging $100K–$2M to support superalignment research across academia, nonprofits, and individuals.
- •Key funded research directions include weak-to-strong generalization, interpretability, scalable oversight, and other approaches to aligning superhuman AI.
- •A $150K OpenAI Superalignment Fellowship targets graduate students ($75K stipend + $75K compute/research funding).
- •No prior alignment experience required; program explicitly aims to bring new researchers into the field.
- •Motivated by the core challenge: current RLHF-based alignment methods may be insufficient for AI systems smarter than human supervisors.
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| Page | Type | Quality |
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| OpenAI | Organization | 62.0 |
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Superalignment Fast Grants \| OpenAI
December 14, 2023
[Safety](https://openai.com/news/safety-alignment/)
# Superalignment Fast Grants
[Apply by February 18(opens in a new window)](https://airtable.com/appnIXmOlWAJBzrJp/paghnoKL6EHiKmKbf/form) [Further program details(opens in a new window)](https://openai.notion.site/Superalignment-Fast-Grants-and-OpenAI-Generalization-Prizes-fd12c66a286a4cbc9dc0f2fef1c62e92)
Justin Jay Wang ✗ DALL·E
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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](https://openai.com/index/instruction-following/) 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](https://openai.com/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
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