Collaborative Research: BIO-AI:Diet Declassified: Using AI-enabled multidimensional diet q — NSF Award to University of Chicago (I
Despite centuries of study, scientists still lack the tools to accurately describe what animals eat in a way that captures the true complexity of their diets. Most existing approaches force species into broad, oversimplified categories such as "carnivore" or "omnivore" that obscure meaningful ecological differences and
| Award title | Collaborative Research: BIO-AI:Diet Declassified: Using AI-enabled multidimensional diet q |
|---|---|
| Award ID | 2534129 |
| Awardee | University of Chicago |
| City | CHICAGO |
| State | IL |
| Amount obligated | $655,434 |
| Principal investigator | Graham Slater |
| Program | Evo Patterns & Processes |
| Start date | 07/01/2026 |
| Abstract | Despite centuries of study, scientists still lack the tools to accurately describe what animals eat in a way that captures the true complexity of their diets. Most existing approaches force species into broad, oversimplified categories such as "carnivore" or "omnivore" that obscure meaningful ecological differences and limit our understanding of how diet has powered the evolution of life on Earth. This project addresses that fundamental gap by developing a new framework for measuring the diets o |
| Source | NSF Awards |
$799/mo
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