Grant 23EnVUNU_2
1 → partial; dissent: 1 → unverifiable, 1 → confirmed
Our claim
entire record- Grantee
- University of Birmingham
- Name
- ARIA TA1.1: Hyper-optimised Tensor Contraction for Neural Networks Verification
- Currency
- GBP
- Date
- June 2024
- Notes
- [Safeguarded AI TA1.1] Hyper-optimised Tensor Contraction for Neural Networks Verification. Lead(s): Stefano Gogioso, Mirco Giacobbe. Institutions: Hashberg Ltd / University of Birmingham. Status: active.
Source evidence
1 src · 3 checks- Grantee
- Hashberg Ltd / University of Birmingham
- Focus Area
- TA1.1
- Name
- Hyper-optimised Tensor Contraction for Neural Networks Verification
- Description
- Hashberg Ltd / University of Birmin
NoteDeterministic match: grantee, name matched in source snapshot (48 rows)
NoteQUA-650 retro-scan: The source is about the Safeguarded AI programme, which is a specific programme within ARIA, not ARIA itself as the grantor organization. Per QUA-648, programmes and initiatives within an organization count as MISMATCHES from the parent organization.
NoteWhile the source confirms that TA1 exists within the Safeguarded AI programme and that the programme is active (with recent updates mentioned), it does not contain specific information about the individual grant record being verified. The source discusses programme-level decisions and technical areas but does not list individual funded projects or grants with their identifiers, names, dates, or grantee information. The record cannot be confirmed or contradicted based on the provided source text.