CICI: UCSS: Enabling a Safe and Directive Multi-modal Foundation Model Ecosystem for Food — NSF Award to University of California-
Rapid progress in Artificial Intelligence (AI) makes it possible to unify images, text, and sensor readings inside powerful multi-modal large language models (MLLMs). Yet researchers in areas such as food science struggle to identify which open-source models to trust and how to deploy them safely in high-stakes setting
| Award title | CICI: UCSS: Enabling a Safe and Directive Multi-modal Foundation Model Ecosystem for Food |
|---|---|
| Award ID | 2531126 |
| Awardee | University of California-Davis |
| City | DAVIS |
| State | CA |
| Amount obligated | $599,721 |
| Principal investigator | Zhe Zhao |
| Program | Cybersecurity Innovation |
| Start date | 09/01/2025 |
| Abstract | Rapid progress in Artificial Intelligence (AI) makes it possible to unify images, text, and sensor readings inside powerful multi-modal large language models (MLLMs). Yet researchers in areas such as food science struggle to identify which open-source models to trust and how to deploy them safely in high-stakes settings such as pathogen detection and nutrient-delivery design. This project establishes a secure, easy-to-use ecosystem that (i) profiles MLLMs on their effectiveness, robustness, effi |
| Source | NSF Awards |
$799/mo
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