On the one hand, I am integrating AI to analyze complex biological patterns and processes, which inspire innovative culinary designs that mimic natural forms and functions. On the other hand, computational design and fabrication tools have enabled me to bring to reality intricate food structures and experiences that are both aesthetically pleasing and functional. For example, in the study “The Taste of Textures: Artificial Intelligence Driven Gastronomic Design and Crossmodal Correspondences in Living Art,” AI-assisted conceptualization and computational design were used to generate unique flavor-related textures, enhancing a multisensory bio-art dining experience. Artificial intelligence, particularly Generative AI and Diffusion Models, has become an essential tool in my processes, informing the conceptualization of biomaterials-inspired applications in gastronomy, allowing for rapid iteration and unexpected design solutions that might not emerge through traditional design workflows. In my current research, Generative AI functions not as a replacement for human creativity but as a co-creator. In The Art of Taste, for example, the workflow began with defining key biomaterial characteristics such as growth patterns, structural properties and aesthetic features, which AI then translated into design concepts that informed the visual and functional aspects of food-based structures. This method was particularly valuable when integrating biomimicry into food design, where efficiency, sustainability and sensory engagement must be considered simultaneously. Beyond conceptualization, AI also plays a critical role in predictive modeling and material behavior optimization, areas traditionally dominated by empirical experimentation. I use machine learning algorithms to analyze large datasets to anticipate material properties, such as biocompatibility and degradation rates, reducing the need for extensive experimental trials. This aligns with the principles of material efficiency in natural systems, where form, function and material are inseparable and respond dynamically to environmental conditions. Historically, pioneers like Frei Otto and Antoni Gaudí relied on biomimicry through manual modeling and geometric principles to enhance material efficiency. Today, computational tools expand upon these approaches, enabling us to integrate AI-driven methodologies into gastronomy and design. Bridging nature, computational creativity and material science helped me explore new possibilities for designing food experiences that are inspired by biological processes and also optimized through AI-driven workflows, sustainability-focused material selection and enhanced structural performance. Ultimately, this intersection of disciplines and methods opens up a new frontier in gastronomy where food is not only consumed but experienced as an interactive, sensory and adaptive entity that evolves in response to its environment, just as biological systems do.