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Grant: Carnegie Mellon University — Robust AI Unlearning Techniques (Coefficient Giving → Carnegie Mellon University)

Verdictconfirmed95%
1 check · 4/9/2026

Deterministic match: grantee, amount, date matched in source snapshot (2714 rows)

Our claim

entire record
Name
Carnegie Mellon University — Robust AI Unlearning Techniques
Amount
$584,108
Currency
USD
Date
May 2025
Notes
[Navigating Transformative AI] Open Philanthropy recommended a grant of $584,108 over two years to Carnegie Mellon University to support the development of robust unlearning techniques for AI. This research will be led by Professors Virginia Smith and Steven Wu. This grant was fexpand[Navigating Transformative AI] Open Philanthropy recommended a grant of $584,108 over two years to Carnegie Mellon University to support the development of robust unlearning techniques for AI. This research will be led by Professors Virginia Smith and Steven Wu. This grant was funded via a request for proposals for projects related to technical AI safety research. This falls within our focus area of potential risks from advanced artificial intelligence.

Source evidence

1 src · 1 check
confirmed95%deterministic-row-match · 4/9/2026
Name
Carnegie Mellon University — Robust AI Unlearning Techniques
Grantee
Carnegie Mellon University
Focus Area
Navigating Transformative AI
Amount
$584,108.00
Date
May 2025

NoteDeterministic match: grantee, amount, date matched in source snapshot (2714 rows)

Case № 4ARV-TA6imFiled 4/9/2026Confidence 95%
Source Check: Grant: Carnegie Mellon University — Robust AI Unlearning Techniques (Coefficient Giving -> Carnegie Mellon University) | Longterm Wiki