Artificial Intelligence and the Generative Science of Food Formulation

Abstract

Food formulation requires balancing taste, nutrition, sustainability, and cost. Traditionally, new foods have emerged through empirical experimentation, expert intuition, and iterative refinement. Artificial intelligence is advancing rapidly across food science, yet most applications remain isolated prediction and optimization tasks rather than parts of a broader scientific framework. Here we define a unified framework for the generative science of food formulation, in which digital food representations enable artificial intelligence to predict, discover, generate, organize, simulate, and optimize. We illustrate this framework through sustainability and nutrition, where generative artificial intelligence transforms environmental and nutritional metrics from post hoc evaluation criteria into explicit design objectives. Finally, we identify the data, models, benchmarks, and automation that will establish computational food design as a rigorous scientific discipline. Together, these advances are transforming food formulation into a generative science.

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