Stanford researcher Ellen Kuhl estimates that there are some 10 43 potential burger recipes in the world. And with BurgerAI , a new tool developed in her lab, artificial intelligence can now design the best one for you based on your age, taste, nutritional need, and even your sustainability goal.
But BurgerAI’s ability to suggest a great-tasting, nutritionally complex, sustainably produced burger is only part of the story. More broadly, this innovation heralds a shift for AI itself: moving AI from prediction to design.
“Most AI systems are trained to predict what already exists. We wanted AI to invent what should exist next,” explained Kuhl, a professor of mechanical engineering in the School of Engineering who now directs Stanford Bio-X , an interdisciplinary life sciences institute that brings together researchers across medicine, engineering, and the natural sciences. “BurgerAI does not ask, ‘What burger is most likely?’ It asks, ‘What burger best satisfies these important and complex objectives?’”
Food is the next big thing in the biosciences, Kuhl said, a focus that combines elements of human experience and culture, health and nutrition, and environmental impact, which are topics that inspire multidisciplinary researchers across the schools of medicine, engineering, sustainability, humanities and sustainability, and beyond.
“Food choices are some of the most consequential decisions humans make every day,” said Vahidullah Tac , a Schmidt Science postdoctoral fellow in Kuhl’s lab. “Food was an easy motivator. With one arrow, you can hit two targets – planetary health and personal health. It’s a great and impactful research area.”
As such, food proved an ideal test bed for Bio-X. Kuhl’s team has just published two papers on BurgerAI, of which Tac is the first author. The first paper introduces BurgerAI. The second paper reveals that the same mathematical principles that drive BurgerAI also underpin diffusion-based generative AI more broadly and create connections to technical fields such as materials design, physics, and engineering.
“For centuries, food design has been a matter of intuition, experience, and trial and error,” Kuhl added. “We are beginning to show that AI can transform food design into a quantitative science with applications in other important fields.”
Using 2,216 burger recipes from Food.com as a data source, BurgerAI learns patterns in ingredient combinations and quantities and then generates new burger recipes from scratch. The AI then matches those characterizations against human flavor and textural preference profiles. The results are entirely novel recipes optimized for deliciousness, sustainability, and nutrition, and personalized based on gender, age, and physical activity.
The ultimate test was not computational but culinary. The researchers served five professionally prepared, AI-designed burgers to more than 100 diners in a blinded taste test at a San Francisco restaurant. In a side-by-side comparison to a popular fast-food burger, BurgerAI’s two variations of its Delicious Burger scored the same or better in overall liking, flavor, and texture. Its Mushroom Burger reduced environmental impact by more than an order of magnitude, and its Bean Burger achieved roughly twice the nutritional score of the fast-food burger.
“AI did not just generate plausible burger recipes – it created burgers that real people enjoy,” Kuhl said. “That may sound simple, but it means the model learned what makes food appealing to the human palate and was able to navigate a design space with near-infinite possible burger combinations to find real-world solutions.”
Tac was genuinely surprised by how well the sustainable burgers performed. “We expected some trade-off between sustainability and consumer acceptance,” he said. “But we found a burger with dramatically lower environmental impact could still compete with one of the world’s most successful burgers.”
For Tac and Kuhl, BurgerAI is not really about burgers. It is a proof of concept for AI’s broader design capabilities. The same generative design framework could have implications in other consequential fields – pharmaceuticals, materials, biomolecules, and other complex systems with huge design spaces. As with food, which requires a balance of taste, nutrition, cost, and sustainability, many of society’s biggest challenges must balance competing objectives. If AI can help navigate trade-offs in recipe design, Kuhl said, it could also help discover new medicines, engineer advanced materials, and create more sustainable products.
“The burger is just the beginning,” Kuhl assured. “We see food as a model system for a much larger vision: AI as a partner in scientific and engineering discovery.”
Christopher Gardner , research professor in the Stanford Prevention Research Center at the Stanford School of Medicine was a contributing author to the BurgerAI paper. Executive Chef Justin Schneider provided burger preparation instructions, and Alice Wistar and Alex Weissman from Palate Insights conducted the taste tests. Funding for the studies was provided by the Schmidt Science Fellows in partnership with the Rhodes Trust, the Sustainability Accelerator in the Stanford Doerr School of Sustainability , Stanford Bio-X Snack Grant Program , and the National Science Foundation.